Business Plan for the establishment, operation and ...solea.gr/wp-content/uploads/2018/03/Aswan-Solar-Plant-Business-Plan.pdf · New Aswan Heart Centre - Solar Farm Business Plan

New Aswan Heart Centre - Solar Farm Business Plan

Business Plan for the establishment, operation and

exploitation of a Solar Farm

Aswan’s Solar Plant Project Extension of Sir Magdi Yacoub Heart Hospital

Prepared by:

Evenflow SPRL

July 2017

Page 2 of 127


This document has been prepared by Evenflow SPRL with the support of Hesham El-Askary, Panagiotis Kosmopoulos and Stelios Kazadzis. Cover page credits: Top Left – Sentinel 2 image of Aswan and surrounding area (Credits: Copernicus Sentinel Data, 2017. Image captured on 11/07/2017). Top Right – Solar Panels (Credits: Michele Piacquadio). Bottom Left – Nevada Solar One parabolic trough, Boulder City, near Las Vegas, Nevada (USA) (Credits: SCHOTT AG). Bottom Right – Nile River in Aswan (Credits: Wikimedia Commons).

© Evenflow SPRL. All rights reserved

Page 3 of 127


Table of Contents 1. Executive Summary ......................................................................................................................... 9

2. Vision ............................................................................................................................................. 15

3. Methodology ................................................................................................................................. 16

4. Market Analysis ............................................................................................................................. 17

4.1. Solar energy technologies .......................................................................................................... 18

4.1.1. Photovoltaics (PV) ............................................................................................................... 18

4.1.2. Concentrated Solar Power Plants (CSPs) ............................................................................ 22

4.2. Energy landscape in Egypt ......................................................................................................... 25

4.2.1. Power generation mix ......................................................................................................... 26

4.2.2. Competent authorities ........................................................................................................ 27

4.2.3. Current and planned schemes ............................................................................................ 28

4.2.4. Companies operating in Egypt ............................................................................................ 30

4.2.5. Other projects ..................................................................................................................... 30

5. Energy Calculations ....................................................................................................................... 33

5.1. Energy requirements of the New Aswan Heart Centre ............................................................. 33

5.2. Energy input at the selected site ............................................................................................... 33

5.3. Development of scenarios based on energy needs ................................................................... 37

5.4. Overview of energy output for the different scenarios ............................................................. 41

5.5. Operational estimation of energy outputs ................................................................................ 43

6. Economic Modelling ...................................................................................................................... 46

6.1. Key assumptions ........................................................................................................................ 47

6.2. Cost structure ............................................................................................................................. 49

6.2.1. CAPEX .................................................................................................................................. 49

6.2.2. OPEX .................................................................................................................................... 50

6.2.3. Cost of electricity from the grid .......................................................................................... 51

6.3. Revenue streams ........................................................................................................................ 51

6.3.1. Selling to the grid ................................................................................................................ 51

6.3.2. Avoided energy costs .......................................................................................................... 52

6.4. Model operation ........................................................................................................................ 52

6.4.1. Options and parameters ..................................................................................................... 53

6.5. Results for the different scenarios ............................................................................................. 57

6.5.1. 12MW Scenarios ................................................................................................................. 58

6.5.2. 20MW Scenarios ................................................................................................................. 61

6.5.3. 50MW Scenarios ................................................................................................................. 65

Page 4 of 127


6.5.4. Maximum Area Scenarios ................................................................................................... 68

6.5.5. Phased approach ................................................................................................................. 71

6.6. Understanding the results ......................................................................................................... 72

6.6.1. Visual comparison ............................................................................................................... 73

6.6.2. LCOE discussion ................................................................................................................... 75

6.7. Recommended scenario ............................................................................................................ 76

6.8. Exploitation strategies ............................................................................................................... 78

7. Implementation and governance.................................................................................................. 80

7.1. Implementation and roll-out strategy ....................................................................................... 80

7.2. Governance structure ................................................................................................................ 81

8. Risk assessment ............................................................................................................................ 83

8.1. Regulatory and market risks ...................................................................................................... 83

8.2. Risks from theft .......................................................................................................................... 83

8.3. Risks from natural elements ...................................................................................................... 83

8.4. Procurement risks ...................................................................................................................... 83

8.5. Operations and maintenance risks ............................................................................................ 84

8.6. Health and safety risks ............................................................................................................... 84

9. Way Forward ................................................................................................................................. 86

10. References ................................................................................................................................ 87

11. Annexes ..................................................................................................................................... 90

11.1. Annex I: Energy calculations for the various scenarios ............................................................ 90

11.2. Annex II: Full series of graphs for individual scenarios .......................................................... 107

11.3. Annex III: Comparative overview of solar technologies ........................................................ 126

Table of Figures Figure 1: The main strategies for the achievement of Net-Zero Energy .............................................. 15

Figure 2: Methodology for the elaboration of the business plan ......................................................... 16

Figure 3: Growth in electricity generation capacity of renewable energy sources, 2004-2016. Data

from REN21, 2017a ............................................................................................................................... 17

Figure 4: Cell efficiency records (NREL 2015) ....................................................................................... 22

Figure 5: The mix of electricity production from different energy sources, 2000-2014; data from

World Bank Databank ........................................................................................................................... 26

Figure 6: The structure of competent authorities in Egypt’s energy sector relevant to solar power up

to 2015. ................................................................................................................................................. 27

Figure 7: The structure of competent authorities in Egypt’s energy sector relevant to solar power by

2018. ..................................................................................................................................................... 27

Figure 8: The solar energy potential in Egypt in kWh/m2 ..................................................................... 34

Page 5 of 127


Figure 9: Mean hourly solar energy input to the PVs and CSPs per month for the specific Aswan's

solar farm .............................................................................................................................................. 35

Figure 10: Mean monthly solar energy input to the PVs and CSPs in hourly, daily and monthly time

horizons (in kWh/m2) ............................................................................................................................ 36

Figure 11: The specific area in Aswan that the potential solar farm will be placed ............................. 38

Figure 12: Mean monthly mirrors performance in kWh/m2 ................................................................. 39

Figure 13: Analytical monthly mean energy output distribution for a 12MW CSP (left) and a 12MW

PV (right) ............................................................................................................................................... 42

Figure 14: Monthly mean energy output distribution .......................................................................... 43

Figure 15: A robust, scalable and flexible economic modelling tool .................................................... 46

Figure 16. Indicative capital costs for PV and CSP projects. ................................................................. 49

Figure 17: Selection of scenario and main parameters for each phase ............................................... 53

Figure 18: General settings of the economic model ............................................................................. 54

Figure 19: Parameters related to PV scenarios ..................................................................................... 55

Figure 20: Khamaseen related parameters........................................................................................... 56

Figure 21: Price-related parameters ..................................................................................................... 56

Figure 22: Tariff-related parameters .................................................................................................... 57

Figure 23: Financing parameters (example) ......................................................................................... 57

Figure 24: CAPEX and OPEX graphs for 12MW scenarios ..................................................................... 59

Figure 25: Break-even analysis for 12MW solutions with storage ....................................................... 60

Figure 26: Break-even analysis for 12MW PV solutions without storage............................................. 61

Figure 27: Comparison of 20MW solutions’ costs and revenues (CSP only vs hybrid) ......................... 63

Figure 28: Break-even analysis for different 20MW solutions ............................................................. 64

Figure 29: Comparison of 50MW solutions’ costs and revenues (CSP only vs hybrid) ......................... 66

Figure 30: Break-even analysis for different configurations of hybrid 50MW solutions ...................... 67

Figure 31: Break-even analysis for the 4 hybrid solutions covering the whole area ............................ 70

Figure 32: Analysis of phased scenario ................................................................................................. 72

Figure 33: Radar Diagrams for 50MW solutions ................................................................................... 74

Figure 34: Radar Diagrams for max. area solutions .............................................................................. 75

Figure 35: Economic charts for the recommended scenario ................................................................ 77

Figure 36: Exploitation Options for the off-site solar farm (©Evenflow SPRL)..................................... 78

Figure 37: The proposed governance structure of Aswan Heart Center’s solar farm. ......................... 81

Figure 38: Overnight capital costs, break-even analysis, lifetime revenues and annual cash flow

graphs for scenario 12MW.I, CSP PT ................................................................................................... 107


graphs for scenario 12MW.II, CSP ST .................................................................................................. 107


graphs for scenario 12MW.III, PV CS .................................................................................................. 108


graphs for scenario 12MW.IV, PV CdTe .............................................................................................. 108









Page 6 of 127



graphs for scenario 20MW.V, CSP PT (12 MW) & PV CS (8 MW) ....................................................... 111


graphs for scenario 20MW.VI, CSP PT (12 MW) & PV CdTe (8 MW) .................................................. 111


graphs for scenario 20MW.VII, CSP ST (12 MW) & PV CS (8 MW) ..................................................... 112


graphs for scenario 20MW.VIII, CSP ST (12 MW) & PV CdTe (8 MW) ................................................ 112










graphs for scenario 50MW.V, CSP PT (12 MW) & PV CS (38 MW) ..................................................... 115


graphs for scenario 50MW.VI, CSP PT (12 MW) & PV CdTe (38 MW) ................................................ 115


graphs for scenario 50MW.VII, CSP ST (12 MW) & PV CS (38 MW) ................................................... 116


graphs for scenario 50MW.VIII, CSP ST (12 MW) & PV CdTe (38 MW) .............................................. 116


graphs for scenario 50MW.IX, CSP PT (10 MW) & PV CS (40 MW) .................................................... 117


graphs for scenario 50MW.X, CSP PT (10 MW) & PV CdTe (40 MW) ................................................. 117


graphs for scenario 50MW.XI, CSP ST (10 MW) & PV CS (40 MW) ..................................................... 118


graphs for scenario 50MW.XII, CSP ST (10 MW) & PV CdTe (40 MW)................................................ 118


graphs for scenario Max Area.I, CSP PT (45 MW) ............................................................................... 119


graphs for scenario Max Area.II, CSP ST (35 MW) .............................................................................. 119


graphs for scenario Max Area.III, PV CS (86 MW) ............................................................................... 120


graphs for scenario Max Area.IV, PV CdTe (97 MW) .......................................................................... 120


graphs for scenario Max Area.V, CSP PT (12 MW) & PV CS (62 MW) ................................................. 121


graphs for scenario Max Area.VI, CSP PT (12 MW) & PV CdTe (70 MW)............................................ 121


graphs for scenario Max Area.VII, CSP ST (12 MW) & PV CS (56 MW) ............................................... 122


graphs for scenario Max Area.VIII, CSP ST (12 MW) & PV CdTe (63 MW) .......................................... 122

Page 7 of 127



graphs for scenario Max Area.IX, PV CS (12 MW) with storage ......................................................... 123


graphs for scenario Max Area.X, PV CdTe (12 MW) with storage ...................................................... 123


graphs for scenario Max Area.XI, PV CS (20 MW) with storage ......................................................... 124


graphs for scenario Max Area.XII, PV CdTe (20 MW) with storage .................................................... 124


graphs for scenario 2Phase, CSP PT (12 MW) in the first year + PV CS (50 MW) in the sixth year .... 125

Table of Tables Table 1: Mean monthly solar energy input values to the PV and CSP systems .................................... 37

Table 2: Full overview of scenarios ....................................................................................................... 41

Table 3: Monthly mean energy consumption ....................................................................................... 42

Table 4: Overview of cost assumptions for the economic model ........................................................ 48

Table 5: Summary table for 12MW with storage solutions .................................................................. 61



Table 8: Summary table for Max. area solutions .................................................................................. 71

Table 9: 12 MW scenario ...................................................................................................................... 90

Table 10: 20 MW scenario .................................................................................................................... 91

Table 11: Max area scenario ................................................................................................................. 94

Table 12: 50 MW scenario .................................................................................................................. 101

Table 13: Mirrors energy output......................................................................................................... 104

Table 14: Comparative overview of solar technologies ...................................................................... 126

Page 8 of 127


Sentinel-2 image of Aswan and surrounding area

(Credits: Copernicus Sentinel Data, 2017. Image

captured on 11/07/2017)

Page 9 of 127


1. Executive Summary The Magdi Yacoub Heart Foundation has proposed the development of the New Aswan Heart Centre.

This state-of-the-art heart hospital will offer excellent-quality, free-of-charge medical services to the

Egyptian people, placing a strong focus on the underprivileged. As an integral part of its vision, the

Centre’s design enables the highest sustainability performance and targets Net-Zero Energy. To

achieve this, the development of an off-site solar farm is being currently explored.

The proposed off-site solar farm will leverage the very significant solar energy potential of the Aswan

region, which presents a unique opportunity to ensure energy self-sufficiency for the New Aswan

Heart Centre and the residential area around it, but also to supply energy to the greater region. The

decision regarding what type of solar farm to build in order to deliver this vision is not an easy one.

The global market for solar energy exploitation is changing dynamically, and significant technological

developments are improving the performance and reducing the costs of photovoltaics (PV) and

concentrated solar power plants (CSP).

Governments across the globe are seizing this opportunity by launching new solar plant projects that

will reduce dependence on fossil fuels and lead towards greener, sustainable development. In this

context, the Egyptian government is taking concrete steps towards increasing the production of

energy from renewable resources, as exemplified in its Vision 2030. In that regard, the vision of Sir

Magdi Yacoub for the development of the New Aswan Heart Centre and its off-site solar farm is

completely aligned with the future sustainable development of the region.

In this context, the raison d'être and aspiration of this work is to provide the necessary evidence and

rigorous analysis that will allow informed decision-making with regards to the strategies for the

implementation of the off-site solar farm.

A detailed market analysis has been carried out which reviews the solar generation technologies

analysed in this study and examines the energy landscape in Egypt. Together with this background

research, consultations with key actors from the competent Egyptian authorities have allowed the

collection of up-to-date pricing data on the capital (CAPEX) and operating costs (OPEX) of solar plants,

applicable as much as possible to the specific conditions of the Aswan Region.

Page 10 of 127


In parallel, the study team has performed a series of detailed calculations of the exact energy output

that different PV and CSP systems would produce on the designated site for the off-site solar farm.

Designated site for the off-site solar farm

The starting point of this analysis was the calculation of the energy input for the region, using a 15-

year radiation climatology from EUMETSAT's Satellite Application Facility on Climate Monitoring (CM

SAF). This provided a clear perspective on annual variability, and a sense of the actual average

potential, as well as the possible natural deviations from year to year. The calculations also took into

account the local aerosol and cloud effect, thus incorporating the effects of Khamaseen dust storms.

Mean Solar Energy input to PVs and CSPs for the specific site in Aswan

http://www.eumetsat.int/website/home/index.html

http://www.cmsaf.eu/EN/Home/home_node.html


Page 11 of 127


This allowed for the calculation of the energy output of a given solution (PV, CSP or combined), with

a view to covering the reported energy requirements of the New Aswan Heart Centre and its

adjacent residential area (amounting annually to 22,427 MWh).

Analytical monthly mean energy output distribution for a 12MW CSP (left) and a 12MW PV (right)

Equipped with up-to-date financial data and accurate energy calculations, the study team adopted a

completely unbiased approach, i.e. without any preference to one technology over the others, to

specific coverage of the designated area or any other such consideration, with the aim of identifying

a set of optimal options for the off-site solar farm. To that end, the following fundamental principles

were considered in developing a large set of scenarios:

▪ 100% Green Operation for the New Aswan Heart Centre: Meeting this condition can be

achieved either by installing CSP solutions or PV with battery storage. Thus, the selection of

scenarios relies on whether this condition is met or not, and through which technological

solution this is carried out.

▪ Use of the available land: The designated area extends over 1.26 km2 which can be used for

the deployment of a solar farm. A range of land use options have been considered.

▪ Nominal power: Different levels of nominal power1 have been evaluated, allowing the direct

comparison of PV and CSP solutions, and helping to identify exploitation options.

▪ Economic performance: Whilst the development of the off-site solar farm is motivated by a

strong vision for 100% energy self-sufficiency and an overall contribution to the sustainable

development and well-being of the area, the economic performance of the various scenarios

is essential for potential investors.

The economic and energy-related performance of the developed scenarios was tested and projected

using a robust, scalable and flexible economic modelling tool, developed specifically for this work.

1 Nominal power (expressed in MW or MWp for “megawatt peak”) refers to the ‘nameplate’ capacity of photovoltaic systems or devices. It is determined by measuring the electric current and voltage in a circuit, while varying the resistance under laboratory conditions. This should not be confused with the output of a system, measured in MWh (megawatt hours).

The total solar energy input potential for PV technologies was estimated at 2,440 kWh/m2

(horizontal panels), 2,569 kWh/m2 (at 24° inclination) and 3,593 kWh/m2 for sun-tracking systems.

For CSP technologies the input energy was calculated to be 2,568 kWh/m2. These results are in

very good agreement with other recent studies (Fraunhofer ISE, 2016).

Page 12 of 127


The authors have analysed numerous scenarios, making use of single-technology or hybrid solutions

(CSP and PV), respecting the local conditions (in terms of costs, energy potential and solar farm

schemes in Egypt) and observing the requirement for 100% coverage of the New Aswan Heart Centre’s

energy needs.

A dedicated economic modelling tool has been developed

The performance of each scenario is visualised in a series of graphs, allowing for their comparison.

Radar diagrams enabling the visual comparison of different scenarios

Meeting the 100% energy requirements coverage objective can be achieved either by CSP solutions

with thermal storage or PV solutions with batteries. However, the high cost of PV batteries and their

very significant OPEX, renders them financially unfeasible. On the other hand, PV without storage

solutions are the cheapest and most compact (i.e. a larger solar farm can be placed in the given site).

Not covering

Energy needs

Page 13 of 127


In this context, this study concludes that the most viable approach is to combine the best features

of CSP and PV solutions within a hybrid configuration. In such hybrid scenarios, the CSP ensures 24h

- 100% green energy production, whereas the energy produced by PVs is sold to the grid, enabling a

sustainable operation (in financial terms) of the solar farm.

Thus, following a traceable chain of reasoning, built on a set of assumptions and the collection of up-

to-date information, the authors have concluded that the best option for the development of the off-

site solar farm would be a hybrid configuration of 50MW (or more), whereby 12MW CSP covers the

site’s energy requirements and a larger PV plant (over 38MW) produces energy sold to the grid.

Solar tower technology is recommended for the CSP part, as it utilises robust 14h storage (for which

the costs in the literature are better-trusted than for parabolic trough with the same storage). For the

PV part, the authors recommend CdTe as it is comparatively cheaper than CS, and in addition, it yields

more energy for the same size of area.

Key charts for a recommended 50 MW hybrid scenario (12MW CSP ST and 38 MW PV CdTe)

The report concludes with a discussion of different exploitation strategies, considering the vision of

the New Aswan Heart Centre and the possibility that it will be deployed in more than one phases.

Nonetheless, the decision on the adoption of these strategies (including a phased approach) is driven

by the specific objectives of the future investors. This report aspires to provide adequate and reasoned

arguments to inform and substantiate these strategies, towards the implementation of the off-site

solar farm. A number of key actions for the implementation and roll-out strategy of the solar farm

have been identified and a governance structure has been suggested. These should be pursued on

the way forward in close coordination with commercial vendors and the competent Egyptian

authorities.

Page 14 of 127


Ko

m O

mb

o S

ola

r p

ow

er p

lan

t, A

swan

, Egy

pt

(Cre

dit

s: E

gyp

t O

il a

nd

Ga

s)

Page 15 of 127


2. Vision Inspired by its driving principles to provide life-saving care, advance medical innovations and train a

new generation of Egyptian doctors and nurses, the Magdi Yacoub Heart Foundation is committed to

the development of the New Aswan Heart Centre. This state-of-the-art heart hospital will offer

excellent-quality, free-of-charge medical services to the Egyptian people, placing a strong focus on the

underprivileged. Its visionary design and operational principles promote the optimisation of the care

experience and the maximised collaboration between researchers and caregivers, in a socially

responsible and environmentally sustainable manner. In doing so, the New Aswan Heart Centre

aspires to become a global icon, for excellent, personalised healthcare, open to the people of Egypt.

As an integral part of its vision, the Centre’s design enables the highest sustainability performance

and targets Net-Zero Energy. The latter will be pursued through the implementation of a passive

design approach to conserve energy use, coupled with active design strategies (e.g. efficient lighting)

to minimise energy use. The clinching factor towards Net-Zero energy is the generation of energy

achieved through the connection of the New Aswan Heart Centre to an off-site solar farm.

Figure 1: The main strategies for the achievement of Net-Zero Energy2

The development of the off-site Solar Farm will leverage the very significant solar energy potential

of the Aswan region, which presents a unique opportunity to ensure energy self-sufficiency for the

New Aswan Heart Centre and the residential area around it, but also to contribute to the energy grid

of the greater region.

In this context, Evenflow SPRL together with experts Dr Hesham El-Askary3, Panagiotis Kosmopoulos4

and Stelios Kazadzis5, have developed a dedicated business plan presented in this report.

2 Inspired by a graph in Foster+Partners, Architectural Report for the New Aswan Heart Centre 3 Professor of Remote Sensing and Earth System Science at the Schmid College of Science and Technology 4 Senior Researcher at National Observatory of Athens and founder at Solea http://solea.gr/ 5 Senior scientist at World Radiation Centre (PMOD/WRC)

http://solea.gr/

Page 16 of 127


3. Methodology The overall methodology used to develop the business plan for the off-site Solar Farm enabling the

Net Zero Energy Scheme for the New Aswan Heart Centre is summarised in the graph below.

Figure 2: Methodology for the elaboration of the business plan

Thus, the development of the business plan has relied on

I. the analysis of the energy requirements of the New Aswan Heart Centre (including the

residential area)

II. a detailed state-of-the-art analysis of the available solar energy technologies, driving the

development of different scenarios (in terms of PV, CSP or mixed plants)

III. an in-depth study of the current energy landscape in Egypt, including the existing or planned

schemes under which solar energy projects can be carried out and the pricing/cost conditions

IV. the execution of a dedicated series of calculations6 on the precise energy yield of different

solar systems in the designated area

V. the performance of rigorous economic analysis, estimating the CAPEX and (i.e. set-up costs)

and OPEX (i.e. running costs) for the different scenarios

The overarching objective driving the execution of these steps, was the identification of the optimal

scenario for the development of the off-site Solar Farm in the designated site. It must be noted that

the economic model can be used as a decision support tool, whereby the results of different

scenarios (i.e. different sets of parameters/assumptions) can be projected and compared. Following

on from this, it is recommended that actual quotes be obtained from companies (on the cost side) and

from the competent governmental authorities (on the revenue side, i.e. price for electricity sold on

the grid). The current set of assumptions is presented in Chapter 6.

The information used or generated across each of the aforementioned steps in order to develop the

assumptions driving the economic model has been a result of extensive desk research. A

6 Note: the UK format for decimals (full-stop) and thousand separators (comma) has been adopted in this report.

Page 17 of 127


comprehensive list of references is presented in Chapter 10. In addition, and given the dynamic nature

of the energy landscape in Egypt, the study team has systematically sought to overcome any data

uncertainties, by enhancing or validating its results and findings through interviews with highly-

standing officials in the competent Egyptian authorities. In that respect, the study team has sought

the guidance of representatives from the Ministry of Electricity and Renewable Energy (MoERE), the

New & Renewable Energy Authority (NREA), and the Electricity Transmission Company (EETC).

The exchanges within the study team and with the external experts have allowed the development of

an indicative and concise roadmap for the implementation of the off-site solar farm, highlighting the

key governance, partnerships and risk considerations to be taken into account.

Additional information on the methodology is presented in the relevant parts of the business plan.

4. Market Analysis Global consent to limit greenhouse gas (GHG) emissions was established by the Paris Climate Accord

in 2015. The global energy sector is a clear priority target for leaders: it accounts for 41% of all GHG

emissions (IEA, 2012a) and is set to expand significantly due to rapid population growth and

urbanisation in developing countries.

Use of coal accounts for 72% of the energy sector’s emissions (IEA, 2012a). Although it is the dominant

fuel – contributing to meeting 40% of the world’s energy needs (IEA, 2012b) – its emissions are

nonetheless significantly oversized. Rebalancing the global energy mix towards renewables is

essential to avoid the brunt of the damage that global warming has the potential to cause. There is

a need to phase out coal and other fossil fuels in favour of renewables, which account for a slim 18,3%

of energy consumption (UN, 2017).

Figure 3: Growth in electricity generation capacity of renewable energy sources, 2004-2016. Data from REN21, 2017a

There are strong positive indications that renewables are already growing in importance in the

generation of electricity. REN21 (2017a) shows exponential increases in power generation from wind

and solar in the past decade (see Figure 3). Total installed capacity of solar PV increased from 2 GW

in 2004 to 303 GW in 2016, with its share of the global power generation mix increasing from a mere

0.05% in 2005 to 3.7% in 2015. CSP is more limited in size, yet it demonstrates a similar trajectory.

Total capacity grew from 0.2 GW in 2005 to 4.8 GW in 2016, marking an increase in its share of the

global power mix from 0.01% to 0.08%. Since 2013, more capacity is added each year from renewable

sources than from fossil fuels.

0

200

400

600

800

1000

1200

Inst

alle

d g

lob

al c

apac

ity

(GW

)

Hydropower

Wind power

Solar power

Page 18 of 127


There have been two main drivers responsible for the extraordinary performance of solar and wind

power. Firstly, solar and wind technologies have been and continue to realise efficiency

improvements, economies of scale and production optimisation (IRENA, 2015b), making solar and

wind power increasingly cost-effective. In 2016 alone, prices of solar PV modules fell by an estimated

29% (REN21, 2017a). Secondly, governments increasingly support renewables through a variety of

policy tools. REN21 (2017a) tracks this progress annually: 173 countries had renewable energy targets

by the end of 2015, compared to 45 in 2004. 146 countries have various policies to support renewable

power generation.

A decade ago, government support was mostly limited to China and developed countries, where

current renewable capacity is concentrated. However, developing countries are expected to follow:

increasing government support along with the need for expanded capacity to meet increasing energy

demand is creating new markets for renewable energy in developing countries (REN21, 2017b).

Continued strong growth in solar and wind power is projected in the future. A detailed compilation

of estimates was made by REN21 (2017b), showing a variation across reports and upward revisions

from year to year. The most recent scenarios project that PV solar capacity will reach to between

413 GW and 3,725 GW by 2030.

Africa, with high solar irradiance and a massive land mass, is especially well positioned to benefit

from continued growth in solar power generation. The Intergovernmental Panel on Climate Change

(IPCC, 2012) identified that the potential for solar power in Africa totals ~5,000 EJ/year, a considerable

portion of the total global potential for electricity generation from all renewable sources – 12,000

Ej/year.

4.1. Solar energy technologies

In view of completeness, this section provides a concise overview of the main solar energy

technologies available. Solar energy technologies can be categorised in two broad categories: (i)

Photovoltaics and (ii) Concentrated Solar Power systems. Both are currently used in utility scale solar

projects across the world.

4.1.1. Photovoltaics (PV)

Photovoltaic solar cells are constructed from semiconducting materials, most commonly from silicon.

A weakness of PV modules is that their performance is expected to decrease over time due to

degradation. Degradation rate depends on the environmental conditions and the technology of the

module. However, with the advances in PV technology their life span is extending and can reach 40

years. They are generally limited in size, hence each one may only deliver a limited amount of power

under fixed current-voltage conditions (Smets et al., 2016). Typically, they are combined into modules

of about 40 cells; the modules are in turn assembled into PV arrays up to several meters on a side.

Each panel absorbs solar energy and creates power by converting sunlight into electricity. This is

possible due to the separation of loose electrons of the material from sunlight energy and their

redirection into electrical current. Solar panels are only one component of a PV system. Thus, a

number of other components consisting the Balance of System (BOS) of a PV system are also

necessary. PV systems modular system design allows easy expansion, when power demands change

(Smets et al., 2016). To get the most from solar panels, it is necessary that they point towards the

direction that captures the maximum amount of sunlight. To this end, an important feature of PV

technology is the mounting structure used to place the solar modules. The three most common

mounting structures to build solar arrays are: (i) fixed-tilt system, (ii) 1-axis tracker system and (ii) 2-

Page 19 of 127


axis tracker system. In this analysis two mounting types are considered: (i) fixed-tilt and (ii) 2-axis

tracker.

Fixed tilt horizontal/

inclined

▪ Solar panels are placed at a fixed angle, either horizontally or inclined, at the optimum tilt.

▪ Inclination at the optimal angle might be necessary to ensure that the panels are pointed to the Sun.

▪ Simple in construction, easy to design and maintain.

2-axis tracker

▪ Automatically adjust the positions of the PV array so that the PV modules consistently keep track of the Sun throughout the day.

▪ Allows for optimum solar energy levels due to their ability to follow the Sun vertically and horizontally.

▪ Higher capacity factor and specific yield compared to fixed tilt or single axis trackers.

▪ More effective at capturing direct radiation. ▪ They require additional acreage to install, and the tracking systems are more

expensive. ▪ Mechanic maintenance is necessary.

Currently there exist various types of semiconductor technologies for PV solar panels. They can be

categorised into two major categories which are currently the most widely adopted: crystalline silicon

and thin film. Both technologies will be considered and an overview of the main characteristics of the

most common semiconductor technologies for the two categories is provided below (based on Smets

et al., 2016).

Crystalline silicon (sc-Si)

Crystalline silicon cells are crystalline forms of silicon either monocrystalline as a continuous crystal (the same material which is used to produce microchips), or multi-crystalline consisting of small crystals. Solar cells made of crystalline silicon are also often called first generation solar cells.

Efficiency >21%

Maturity Currently is the most mature PV technology

Advantages ▪ More efficient than the thin film solar cells ▪ High stability ▪ Ease of fabrication ▪ High reliability ▪ Proved longevity

To minimise the complexity and the number of different scenarios, we have not considered 1-axis

tracker PVs due to their lower efficiency compared to 2-axis PVs and their higher cost compared

to PVs fixed horizontally and at optimal tilt for the area under study (24 degrees). In light of the

above, the performance of the 2-axis tracking system was chosen to be simulated (with respect to

power generation) and compared with other tracking and mounting technologies directly in order

to conclude if the extra cost of the tracker returns back to comparable performance.

Page 20 of 127


▪ High resistance to heat ▪ Lower installation costs ▪ Silicon is more environmentally friendly come disposal/recycling time

compared to thin film Weaknesses ▪ Most expensive in terms of initial cost

▪ Low absorption coefficient ▪ Rigid and fairly fragile

Due to its established positioning in the market and its efficiency, crystalline silicon was selected for

evaluation in the context of the technological and economic scenarios in this study.

The second major category concerns thin-film solar cells. They are similar to normal sc-Si cells and

their operation is based on the same principle (photovoltaic effect). The only basic difference between

thin-film and sc-Si cells is the thin flexible arrangement of the different layers and the basic solar

substance used in thin-film technology (Electronic circuits, 2017). There exist three main types of thin

film solar cells, depending on the material used for P- and N-types: (i) amorphous silicon (a-Si), (ii)

cadmium telluride (CdTe), (iii) copper indium gallium deselenide (CIS or CIGS). Of the three, CdTe was

selected for analysis in this study, due to its maturity and favourable economic characteristics.

Copper Gallium Selenide (CGIS/CIS)

CGIS is a thin-film solar cell comprised by a thin layer of copper, indium, gallium and selenide on glass or plastic backing, along with electrodes on the front and back to collect current. CIS cells are Gallium-free variants of the semiconductor material.

Working principle

Photovoltaic effect

Efficiency 12%

Maturity ▪ Early deployment phase ▪ Medium scale production

Advantages ▪ Higher performance ratio than sc-Si

▪ Low cost ▪ For its construction, a much thinner film is required than of other

semiconductor materials Due to the material’s high absorption coefficient (e.g. a material that strongly absorbs sunlight)

▪ They are expected to reach silicon-like efficiencies

Weaknesses ▪ Less mature technology

https://en.wikipedia.org/wiki/Absorption_coefficient


Page 21 of 127


Cadmium Telluride (CdTe)

CGIS is a thin-film solar cell comprised by a thin layer of copper, indium, gallium and selenide on glass or plastic backing, along with electrodes on the front and back to collect current. Gallium-free variants of the semiconductor material are abbreviated as CIS cells.

Working principle

Photovoltaic effect

Efficiency ~19%

Maturity The most common thin film technology in the market

Advantages ▪ CdTe has the lowest energy payback of all mass-produced PV technologies, and can be as short as eight months in favourable locations

▪ Due to the material’s high absorption coefficient (e.g. a material that strongly absorbs sunlight), a much thinner film is required than of other semiconductor materials

▪ On a lifecycle basis, CdTe has the smallest carbon footprint, lowest water use and shortest energy payback time of all solar technologies.

Weaknesses ▪ Size limitations due to its fabrication process, maximum GW limitations due to Te scarcity

▪ Contains toxic elements. This can be addressed by recycling CdTe cells.

Concentrated photovoltaics are photovoltaic systems that supply concentrated light onto PV cells increasing PV output. Due to their lack of maturity, they were not selected for analysis within this study.

Concentrated photovoltaics (CPV)

Concentrated photovoltaics typically involve using optical light collectors to concentrate light, such as lenses or mirrors, from a larger area to a smaller area of a solar cell. They do not collect energy unless pointed directly at the Sun rather than diffuse light, meaning that this technology is limited to clear, sunny locations and that in most cases tracking is required. CPVs can be classified in three main categories depending on the sunlight concentration ratio: (i) low-concentration, (ii) medium concentration and (iii) high concentration.

Working principle

Photovoltaic effect

Efficiency 33%

Maturity Early stage, 1st commercial phase Advantages ▪ CPV uses less PV cells, thus less cost

▪ Increased efficiency than normal PVs due to sun tracking ▪ Higher daily productivity due to sun tracking

Weaknesses ▪ Concentrated sunlight might cause spots with significantly increased temperature on the surface of the solar cell causing the formation of hot

https://en.wikipedia.org/wiki/Energy_payback_time


Page 22 of 127


(overheated) spots which can hamper the functionality and the life span of the system.

▪ Makes the use of high-efficiency but expensive multi-junction cells economically viable due to smaller space requirements.

For a comparative overview of the different cell efficiencies the reader is advised to visit

https://energy.gov/eere/sunshot/downloads/research-cell-efficiency-records which maintains the

plot shown below for a range of photovoltaic technologies.

Figure 4: Cell efficiency records (NREL 2015)

4.1.2. Concentrated Solar Power Plants (CSPs)

Unlike PV technologies, Concentrating Solar Power (CSP) technologies do not use solar cells to

generate current from solar energy. Instead, CSPs use mirrors or lenses to focus (concentrate) sunlight

which is then converted into heat that creates steam and drives a turbine generating electrical power.

It is important not to confuse CSP with CPV. As mentioned in subsection 4.1.1.3, in CPV the

concentrated sunlight is converted directly to electricity using PV cells. In addition, CSP uses only the

direct component of sunlight (DNI). Another important feature of CSP plants is that they can be

equipped with a heat storage system to generate electricity when sunlight is not optimal, whether this

is due to bad weather conditions or after sunset. Solar heat generated during sunny hours can be

stored in a high thermal-capacity fluid, and released upon demand (e.g. at night or days with limited

sunlight) to produce electricity (IEA-ETSAP & IRENA, 2013). Currently the four main alternative CSP

configurations are:

• Parabolic trough systems

• Solar Power tower systems

• Compact linear Fresnel

• Dish systems

An overview of the main features of all four technologies is provided in the cards below based on,

(IEA-ETSAP & IRENA, 2013).

https://energy.gov/eere/sunshot/downloads/research-cell-efficiency-records

Page 23 of 127


Parabolic Trough (PT)

This technology uses parabolic mirrors (or lenses) with tracking systems in order to focus sunlight rays into a small beam on heat receivers (i.e. steel tubes) placed on the focal line of the mirrors. Each tube contains a fluid with heat transfer properties (working fluid), which is heated to a high temperature by the energy of the sunlight. The heat generates steam which is then utilised in a turbine to covert this energy into electricity.

Working principle

Heat energy turns to electricity through a working fluid, with an operating temperature of 350-550°C.

Efficiency 11-16% Maturity The most mature CSP technology Advantages ▪ Most developed CSP technology

▪ A small area can produce a large output of electricity when in sunny conditions

▪ High output for a low cost among CSP technologies Weaknesses ▪ Lower maximum heat than the other CSP technologies results in lower

efficiency ▪ Water is consumed due to the heat transfer fluid

Solar Power Tower (ST)

The solar power tower, also known as 'central tower' power plants, consists of a large number of flat, sun-tracking mirrors, known as heliostats, focus sunlight onto a receiver at the top of a tall tower. A heat-transfer fluid heated in the receiver is used to heat a working fluid, which, in turn, is used in a conventional turbine generator to produce electricity. Some power towers use water/steam as the heat-transfer fluid.

Working principle

Heat energy turns to electricity through a working fluid, with an operating temperature of 250-656°C.

Efficiency 7-20% Maturity Mature Advantages ▪ In principle, ST plants can achieve higher temperatures than PT and FR

systems because they have higher concentration factors. ▪ In the long run, they could provide the cheapest CSP electricity, but more

commercial experience is needed to confirm these expectations. Weaknesses ▪ The storage capacity is significantly limited by the use of steam and the cost

of pressure vessels ▪ In utility scale ST, a higher number of heliostats is needed and their distance

with the central receiver is greater. This can lead to more optical losses, atmospheric absorption, and angular deviation due to sun-tracking imperfections

▪ Regular mechanical maintenance and mirror cleaning is needed.

Page 24 of 127


Stirling dish (SD)

An SD system consists of a parabolic dish shaped concentrator (like a satellite dish) that reflects sunlight into a receiver placed at the focal point of the dish. The receiver may be a Stirling engine (i.e. kinematic and free-piston variants) or a micro-turbine. SD systems require two-axis sun tracking systems. This system does not use a heat transfer fluid, just air.

Working principle

SD exploit the geometric properties of a parabola as a 3D paraboloid. Based on the Stirling thermodynamic cycle the engine produces electricity without steam. Its operating temperature is 550-759°C.

Efficiency 12-25%

Maturity Early (demonstration phase)

Advantages ▪ High efficiency ▪ Modularity ▪ SD are good for regions with limited water availability since it is the best

technology for air cooling ▪ and offer very high concentration factors and operating temperatures

Weaknesses ▪ Relatively high electricity generation costs compared to other CSP options ▪ Regular mechanical maintenance and mirror cleaning ▪ Energy storage not yet available

Compact Linear Fresnel reflector

This technology uses long, thin and flat single axis solar array mirrors to focus sunlight onto a fixed receiver located at a common focal point of the reflectors. These mirrors are rotating, following the Sun, and are capable of concentrating the sun’s energy to approximately 30 times its normal intensity. Then, energy is transferred through the receiver into a thermal fluid (this is typically oil capable of maintaining liquid state at very high temperatures). The fluid then goes through a heat exchanger to power a steam generator.

Working principle

Heat energy turns to electricity through a working fluid. Unlike PT where a second, high heat fluid is used as a heat exchanger. The operating temperature is 390°C.

Efficiency 13% Maturity Early (pilot phase) Advantages ▪ FR compared to PT systems are the lower cost of ground-based mirrors and

solar collectors (including structural supports and assembly). ▪ Lower manufacturing and installation costs compare to PT

Weaknesses ▪ Thermal fluid reaches lower heat than PT, thus it has lower efficiency ▪ FR optical efficiency is lower than that of the PT systems (i.e. higher optical

losses) ▪ Regular maintenance, cleaning of all mirrors, is necessary

Page 25 of 127


A comparative overview of all PV and CSP technologies based on information acquired from (IRENA,

2012a), (IRENA, 2012b), (IEA, 2014), (NREL, 2012), (World Bank), and (Fraunhofer ISE, 2016) is

provided in Annex III.

For the purposes of the study, and due to their maturity, parabolic trough (PT) and solar power tower

(PT) systems were selected for analysis.

4.2. Energy landscape in Egypt

Energy consumption in Egypt has been rising at an average rate of 5,6% per year over the past

decade (APICORP, 2016), and is projected to continue rising by 5% annually into the midterm

(Eversheds, 2015). The drivers of this upward trend are: (i) a growing economy, totalling 208% in the

past decade, and (ii) a growing population, marking a 20% increase in the past decade. In total, 99%

of Egypt’s 92 M inhabitants had access to electricity in 2015 (WorldBank Databank).

The Egyptian energy sector was fully nationalised in 1962 and has since been state-led. Recently, it

has faced challenges to meet rapidly rising demand with a sufficient expansion of capacity. The

margin of the power systems generation reserve capacity, key to avoid power outages during peak

demand periods, declined from around 20% in the early 2000s to under 10% by 2013 (Vagliasindi &

Besant-Jones, 2013). The same authors noted improvements in the quality of electricity provision in

the early 2000s, including a 48% drop in distribution transformer failures between 2002 and 2008.

However, Eissa & Tian (2017) highlighted a significant problem with power outages between 2012 and

2015. The Oxford Business Group (2016) notes that power cuts during the summer of 2014 intensified

efforts to fast-track the construction of new power plants.

Oxford Business Group (2016) estimated that Egypt needs to increase its electricity generation

capacity by 5.5 GW a year through 2022 to address the production gap, which requires annual

investments totalling 5 billion USD or around 10% of the government’s annual budget. Similarly,

APICORP (2016), estimated that roughly 5 GW a year would have to be added to address current

production shortfall, amounting to a total of 43 billion USD over the 4 year period for investments (or

20% of the government’s budget) to increase power generation as well as upgrade transmission and

distribution. Given budgetary challenges this decade, the government has recognised it must

accelerate its effort to attract private capital in the energy sector.

Two major measures are being undertaken by the government to promote liberalisation. Firstly, it is

creating an enabling framework through legislation coupled with supporting measures from

government institutions. Secondly, it is reforming energy subsidies to permit electricity prices to

rise. Between 2005 and 2008, electricity prices rose by 5% each year – yet this program was

abandoned in 2009. Following President Sisi’s election in 2014, a multi-phase strategy was promptly

implemented to entirely remove energy subsidies over the next 5 years (except for liquefied

petroleum gas). The last price hike took place at the end of June 2017 – 43-55% for gasoline prices and

100% for liquefied petroleum gas – following one in early November 2016, in which fuel prices rose

35-47% (Xinhua, 2017). There are strong signs of commitment to further reform (EgyptERA, July 2017).

Enabling policy and government support, coupled with Egypt’s large size as well as its economic and

demographic growth, make the country’s energy sector an attractive business opportunity for the

private sector. Experts believe that these positive signals will significantly alter the country’s energy

landscape. Evershed (2015) predicts that by 2018 there could be 80 or more private energy generators

in Egypt, including renewables.

http://egyptera.org/Downloads/New-Tariff-2017.pdf

Page 26 of 127


4.2.1. Power generation mix

Egypt’s power mix has varied over time. In 1970, when the landmark Aswan dam was completed on

the Nile, hydropower accounted for around 60% of electricity generated (Oxford Business Group,

2016). Since then the country has primarily relied on oil and particularly on natural gas to increase

electricity generation capacity. As Egypt is Africa’s largest non-OPEC petroleum and gas producer, it

was able to use cheap raw materials to maintain a low price of electricity. As a result, natural gas

accounted for 79% of electrical capacity in 2014, as shown in Figure 5.

Despite abundant natural gas reserves, development of exploitation projects has not kept up with

increases in demand. The country has imported natural gas since 2013 to meet its needs (Egypt

Oil&Gas, 2013) and is expected to continue to do so by 2018 (Bloomberg, 2017). With these

limitations, a greater diversity of energy sources is needed to meet rising demand for electricity.

A ministerial decision in 2014 approved coal imports. By 2016, coal power already accounted for 2%

of total electricity generation. Similarly, the government has restarted its nuclear power program in

2010 with Nuclear Law No. 7/2010. A 4.8 GW power plant in El Dabaa is in its final preparatory stages.

Moreover, the country’s large potential for generation of electricity from solar and wind has recently

been recognised in the “New National Renewable Energy Strategy” drafted by the Supreme Council

for Energy. The document foresees an increase in the share of renewables in electricity production

from 12% to 20% by 2020: 12% from wind (7.2 GW), 2% from solar (1.2 GW), and the rest from

hydropower.

Figure 5: The mix of electricity production from different energy sources, 2000-2014; data from World Bank Databank

The first solar power plant tender was held in 2014 and had more than 80 accepted applications, 50%

above the target (Jäger-Waldau, 2016). By the end of 2015, 70 MW of solar PV power was already

operational, with 1.8 GW at some point in project development (Middle East Solar Industry

Association, 2016). Commitments and agreements finalised in 2015 give an indication that there is

significantly more to come: Norway’s Scatec Solar for five projects totalling 250 MW, India’s Sterling

and Wilson for several projects totalling 300 MW, a partnership between Saudi Arabia’s ACWA Power

and Abu Dhabi’s Masdar for 1.5 GW, Ireland’s Terra Solar for 2 GW, and a partnership between

0

20

40

60

80

100

120

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014Elec

tric

ity

pro

du

ctio

n (

bill

ion

kW

h)

Electricity production from oil sources

Electricity production from natural gas sources

Electricity production from hydroelectric sources

Electricity production from renewable sources, excluding hydroelectric

Page 27 of 127


Canada’s SkyPower Global and Abu Dhabi’s International Gulf Development for 3 GW (Oxford Business

Group, 2016).

4.2.2. Competent authorities

The structure of the electricity sector is in a state of transition. The roles and responsibility of several

key authorities is changing to facilitate the proliferation of an open competitive market for private

actors. These changes can be seen in Figure 6 and Figure 7, representing the structure of competent

authorities as it is in 2015 and as it will be at the end of the transition period by 2018, respectively.

Figure 6: The structure of competent authorities in Egypt’s energy sector relevant to solar power up to 2015.

The dotted line refers to the fact that the Minister of Electricity and Energy was the chairman of EgyptERA’s board.

Figure 7: The structure of competent authorities in Egypt’s energy sector relevant to solar power by 2018.

The Cabinet of Ministers is the main policy making body in the domain of energy. Since 2006, the

Supreme Council for Energy, headed by the Prime Minister, oversees strategy, policy, investment

programs and pricing for the energy sector, including for its electricity subsector. Since 2015, it

delegates tariff setting duties for the open electricity market to the Egyptian Electric Utility and

Consumer Protection Agency (EgyptERA).

The administration of energy issues is mandated to the Ministry of Electricity and Renewable Energy

(MOERE) for the most part, with a smaller role for the Ministry of Petroleum. MOERE currently owns

all public companies in the energy sector organised into an umbrella entity called the Egyptian

Electricity Holding Company (EEHC). Within EEHC, there are 16 subsidiaries including six generation

companies, nine distribution companies and the Egyptian Electricity Transmission Company (EETC).

By mid-2018, in accordance with the Electricity Law No. 87/2016, EETC is obliged to become an

independent transmission system operator, separated formally from the EEHC and other state power

generators and distributors. The state company will remain a monopolist in electricity transfer, but

must become impartial, showing with no preferential treatment to producers or consumers. Simply

Page 28 of 127


put, EETC is not allowed to refuse transfer of electricity between an independent generator and their

customers. It will also assume new responsibilities including:

• Establishing transmission regulations;

• Guaranteeing stability of the grid by purchasing ancillary services and providing stabilisation

power;

• Generating annual reports on power supply, specifically to estimate growth in demand, and

thus inform strategic energy decisions by the Cabinet of Ministers;

• Becoming responsible for power purchases from licensed producers.

EETC offers long term power purchase agreements of 25 years for solar and 20 years for wind to all

private investors. The Central Bank of Egypt guarantees all financial obligations of EETC under this

contract. However, as noted by Sharkawy & Sahran Law Firm (2015), this arrangement will change as

EETC becomes independent from the EEHC in accordance with the Ministry of Finance Guarantee Law

no. 14/2013, which is strictly limited to the EEHC. The authors note that a guarantee for an

independent EETC will have to be authorised by the Cabinet of Ministers.

There are currently six authorities with a specialised focus in the electricity sector that report directly

to the MOERE. This includes the New and Renewable Energy Authority (NREA), created in 1986 to

promote renewable sources of energy including solar power. NREA has two main roles. The first is to

lead renewable energy projects for the government, and successively operate the power plants. Its

second role is to support independent renewable energy producers.

7,600 km2 of desert were allocated in 2014 for future renewable energy projects, with all permits

for land allocation already obtained by NREA. This land is available to private actors on the basis of

preference and availability. Environmental impact assessments for these plots have already been

completed by NREA in cooperation with international consultants. Land concessions are granted in

return for 2% of total power generated by the power plant.

EgyptERA was established in 2000 by presidential decree in anticipation of energy market

liberalisation. Up to 2015, it primarily licensed companies in the power sector and monitored them.

The recent Electricity Law (see next section) significantly expands its role, granting it full independence

and greater regulatory authority. It assumes new responsibilities including:

• Establishing a dispute settlement body specifically related to the feed-in-tariff program;

• Approving change of ownership of licensed private companies active in the energy sector;

• Approving rules of commerce and settlement in the open energy market proposed by EETC;

• Setting the rules for qualifying commercial entities to make supply contracts on the open

energy market and accepting such supply contracts;

• And, crucially, setting electricity tariffs to non-qualified customers.

4.2.3. Current and planned schemes

Prime-Ministerial Decree No. 1947/2014 was passed in 2014, allowing feed-in tariffs (FiT) for

electricity producers. The second phase of the FiT programme started in 2016 . Later on in 2014, the

Encouragement of the Production of Electricity from Renewable Energy Resources (No. 203/2014), or

simply The Renewable Energy Law, was passed. This law defines several other schemes available for

the renewable energy sector of the country. Overall, these developments are intended to facilitate

and encourage participation of private actors in renewable energy projects at all scales. This can be

seen in the following descriptions:

Page 29 of 127


Competitive bidding to build renewable energy plants to be owned and operated by NREA is

open to local and foreign companies. As such, it targets companies with expertise in designing and

constructing renewable energy projects of a medium and large scale, as well as suppliers of

equipment. Electricity to be generated from these projects will be sold to EETC for a regulated

price determined by EgyptERA and approved by the Cabinet of Ministers.

Competitive bidding mechanism for build-own-operate (BOO) contracts will be organised by the

EETC and open to local and foreign investors. It targets investors with an interest in renewable

energy, and potential partners they might need with capacities to design, construct and operate

a large to medium scale facility, which they will own. The NREA will transfer state land specifically

earmarked for this use. Electricity will be sold to the EETC for a price to be agreed upon between

the owner and the EETC through a power purchase agreement spanning 25 years for solar

projects. After the project is completed and the power plant decommissioned, the ownership of

the land will be transferred back to NREA.

FiT support system is open to small wind and solar PV energy projects: those with a capacity of 50

MW or less. A range of actors are targeted, including companies, households, institutions or even

investors to build, own and operate renewable energy infrastructure. The capacity could primarily

focus on meeting own needs, with the surplus sold to the grid.

In turn, electricity is sold to EETC or to a licensed electricity distribution company. For contracts

with the EETC, the tariffs are defined in a power purchase agreement with a duration of 25 years

for solar projects, and depend on the generation capacity of the project. Long term leases of state-

owned land are available in exchange for 2% of electricity generated by the project.

Several other measures are available to support small renewable energy generators:

• Net metering allows electricity generators to draw from the grid at a time when use

surpasses generation (e.g. during night time), in exchange for electricity delivered to the

grid at other times;

• For renewable energy projects, all equipment is imported at discounted customs rate of

2%;

• A government renewable energy fund provides soft loans of 4% for projects with capacity

up to 200 kW and 8% for projects with a capacity 200 - 500 kW (although this measure is

not activated at the time of drafting this report);

• Priority access to the electrical grid.

The government’s FiT target for 2015-2017 is to have 4,300 MW of new capacity: 300 MW from

small solar systems of less than 500 kW (e.g. rooftop PVs), 2,000 MW from medium and large solar

power plants and 2,000 MW from medium and large wind plants.

Independent power production through third party access allows privately owned and operated

power producers to meet their own needs and/or to make power purchasing agreements with

qualified customers of their choosing, that is those approved by EgyptERA to do so. Compared to

the FiT scheme, this scheme targets larger investments by institutions, companies or even

investors. EETC will charge for electricity transfer services through its grid to third parties and may

not block such agreements.

The latter scheme seems to be applicable to the case of the New Aswan Heart Centre off-site

Solar Farm, and in that respect an agreement with EETC and EgyptERA shall be established.

Page 30 of 127


With much anticipation, the Egyptian Electricity Law (No. 87/2015) was passed in 2015, seven years

after being published and submitted to Parliament. It marks a milestone in the reform of the energy

sector. In effect, the law seeks to establish an open competitive energy market in parallel to a

regulated one, charting out the steps towards market liberalisation. It provides an enabling

framework to encourage private investors to enter the Egyptian energy sector traditionally dominated

exclusively by the state. It does so through:

• Introducing a simple regime for granting permission to and licensing of electricity producers,

open to locals and foreigners;

• Opens up electricity distribution to locals and foreigners;

• Restructures state monopolies of electricity production and distribution to allow for a

competitive market;

• Restructures EETC and EgyptERA to grant them independence and new stature and function;

• Streamlines regulations that apply to the sector.

Most aspects of the law will be implemented in a transitional phase of three years, with some

implemented over five years. This is a strong step in the direction of liberalising the energy market

which Sharkawy & Sarhan (2015) expect will continue.

4.2.4. Companies operating in Egypt

Driven by the high solar energy potential of Egypt and increasingly supportive government policy, a

large number of local and international companies operate in Egypt. A non-exhaustive list includes

large global companies that have the capacity to engineer, finance and operate large solar energy

projects, such as ABENGOA Solar Ventures, GDF Suez, Enel Green Power S.p.A., Total - Beltone Solar

Venture, Sinohydro Renewable Energy - Sinohydro Corpopration, TATA Power, EDF, Energies

Nouvelles, Solaredirect and ACWA Power. It also concerns engineering companies that deliver

turnkey projects such as Scatec Solar, Neon Energy and Smart Green Holding. Renewable energy

component suppliers are also present, such as Gestamp Renewables and Al-Tawakol Electrical Group.

A wide range of local companies – Cairo Solar, Onera Systems, Wadi Degla Holding – and regional

companies – The European Jordanian Renewable Energy Project LLC, ElKamel Guld New Energy,

Philadelphia Solar – also operate in Egypt.

4.2.5. Other projects

The energy outputs from the potential solar farm in Aswan was cross-validated against similar projects

in Morocco, California, China and South Africa. In Morocco, the Noor 1 CSP PT (160 MW) produces

almost 370 GWh on an annual basis covering an area of 4.5 km2. In California, a CSP ST (392 MW) uses

an area of 14.16 km2 and gives back annually 1,079 GWh. In China, a 5,600 MW PV needs land surface

of about 570 km2, while in South Africa from a 100 MW CSP ST they exploit 480 GWh, and from 96

MW and 75 MW PVs the take back energy output of about 180 and 150 GWh respectively.

The dynamically changing landscape in Egypt, necessitates the acquisition of concrete offers by

some of these companies in relation to estimated costs for the New Aswan Heart Centre off-site

solar farm. In the same vein, the active presence of a multitude of companies guarantees that

up-to-date offers in response to the scenarios developed herein can be obtained.

Page 31 of 127


Bringing the above solar farms into the Aswan's energy yield of 2,440 kWh/m2 for PV installations

and 2,568 kWh/m2 for CSP systems we found similar energy outputs.

More specifically, for the PV technologies and materials we expected and cross-validated the following

energy output potential values: 270.73 and 386.74 kWh/m2 for CSP PT and ST, and, 175.10 and 196.31

kWh/m2 for PV CS and CdTe, respectively. Under similar geographical and climatological conditions,

the mirrors performance for all technologies are dependent on the location's mean annual energy

input yield and the total losses of each technology and material.

Page 32 of 127


Parabolic Trough Power Plant Kramer

Junction, California

(Credits: Trec UK)

Page 33 of 127


5. Energy Calculations 5.1. Energy requirements of the New Aswan Heart Centre

The starting point and one of the main assumptions for the analysis is the need to partially or fully

cover the energy requirements of the New Aswan Heart Centre and the adjacent residential area.

These requirements have been provided to the study team through the dedicated report by Foster +

Partners, 2017. Thus, the energy requirements of the New Aswan Heart Centre, amount to 15,747

MWh annually, whereas those of the adjacent residential area are estimated at 6,680 MWh. The total

annual energy requirements are 22,427 MWh, which is the energy target that must be fulfilled to

achieve the coveted zero net7 energy vision for the project. It must be noted that these energy

requirements are based on the 1st stage of the new Aswan Heart Centre development and are

inclusive of the both the passive and active design.

The energy planning strategy drawn in the following, as well as the individual scenarios developed,

are constructed with reference to these energy requirements. Concerning the energy adequacy and

efficiency for the energy consumption in all time scales (from the annual to hourly-based), the study

team has pursued to cover the energy needs from the summer months and hours in this season (with

high mean solar energy yield) to the winter months in which the solar elevation is lower with an

immediate effect to the energy output/production from the solar farm. So, it was critical to build a

sufficient solar exploitation system capable to produce the required energy loads in all months of

each year.

A minimum system of 7 MW nominal power is required in order to fulfil the energy requirements

of the hospital, and an additional 3 MW system is needed for the residential area. For energy

security and unimpaired self-sufficiency, the minimum proposed solar farm must be 12 MW, with

the surplus produced energy in the fertile periods (high solar elevations near local noon and summer

months) to be made available for (sold into) the Egyptian energy grid. It is important to highlight that

a system with nominal power equal to 12 MW produces (as shown in the following sub-sections)

30,882 MWh per year (Tables 2 and 3), while the real solar energy input to the system in Aswan

reaches almost 2,568 kWh/m2 for CSP and inclined PV at 24 degrees (Table 1). In Morocco, the Noor

solar farms (CSP) produce almost 370 GWh using an area of 4.5 km2 (system's nominal power is 160

MW under 1,990 kWh/m2 local energy yield). This means that compared to other installed solar farms

in North Africa, Aswan has much higher solar energy yield with consequent higher system energy

output results.

5.2. Energy input at the selected site

Aswan is a region in southern Egypt with very high solar energy potential and its exploitation is critical

for the local sustainable development through an efficient energy planning and a gradual

independence from fossil fuels. Equitable access to energy is a basic requisite for economic

development and an important condition to galvanise economic activity. Aswan has conditions for

the largest production of renewable energy in Egypt (Figure 8) and as a result there has been

significant market traction for the region’s solar power in a growing export market for clean energy.

7 For a definition of Zero Net Energy see here

http://netzerofoundation.org/docs/A%20Common%20Definition%20for%20Zero%20Energy%20Buildings_0.pdf

Page 34 of 127


Figure 8: The solar energy potential in Egypt in kWh/m2

The solar energy potential in Egypt in kWh/m2. The Direct Normal Irradiance (DNI) applies to the Concentrated Solar Power

plant technologies. Aswan presents a mean solar energy potential of 2,440 kWh/m2 in terms of Global Horizontal Irradiance

(GHI) and 2,568 kWh/m2 for DNI. [Map produced by Solea]

Solar power at surface is measured in W/m2 and consists of the direct, diffuse and total radiation. The

total radiation is the sum of the direct and diffuse radiation components, called Global Horizontal

Irradiance (GHI), and it applies to the Photovoltaic (PV) installations (adjusted for the preferred

inclination). On the other hand, the direct radiation is measured at normal surface to the incoming

radiation (Direct Normal Irradiance; DNI) and it applies to the Concentrated Solar Power (CSP) plants.

The continuous incoming solar power over a specific time-period (hour-based) gives back the solar

energy in kWh/m2.

For the precise assessment of the energy output from the PV and CSP systems it is critical to know

the exact solar energy input and the total amount of the systems’ losses based on real world

applications of solar farms. In the framework of this business plan, the energy input was calculated

based on a 15-years (01/1999 - 12/2013) radiation climatology of the EUMETSAT's Satellite Application

Facility on Climate Monitoring (CM SAF), in order to have a real perspective on annual variability, and

to get a sense of the actual average potential and the possible natural deviations from year to year.

The data used have been benchmarked by ground measurements and the validation results can be

found here. The calculations have also taken into account the local aerosol and cloud effect in terms

of Aerosol Optical Depth (AOD) and Cloud Optical Thickness (COT) from the Monitoring Atmospheric

Composition and Climate (MACC) project, and the related aerosol model and the Meteosat Second

Generation (MSG) cloud products respectively. Concerning the aerosols, the main source is Saharan

dust and more specifically the Khamaseen potential dust storms that are more frequent from mid-

March through April; thus, the calculations have incorporated these fifty days (Khamaseen in Arabic

means ''fifty'') phenomenon. The validation of results was performed against ground-based

measurements from the BSRN and the results are presented in the following report link. Figure 9

presents the hourly mean solar energy input per month for the Aswan region, for: PVs with horizontal

panels, PVs with optimal south-faced inclined panels at 24 degrees, PVs with a 2-axis tracker which

follows the sun, and finally for CSP installations.

http://www.eumetsat.int/website/home/index.html


http://www.cmsaf.eu/EN/Documentation/Documentation/ValidationRep/pdf/SAF_CM_DWD_VAL_METEOSAT_HEL_1_1.pdf;jsessionid=BBE35F7FCDF6E311192AFE6575A640BD.live11293?__blob=publicationFile&v=2

http://www.cmsaf.eu/EN/Documentation/Documentation/ValidationRep/pdf/SAF_CM_DWD_VAL_METEOSAT_HEL_1_1.pdf;jsessionid=BBE35F7FCDF6E311192AFE6575A640BD.live11293?__blob=publicationFile&v=2

Page 35 of 127


Mean Solar Energy

Figure 9: Mean hourly solar energy input to the PVs and CSPs per month for the specific Aswan's solar farm

The results are in kWh/m2 and represent: the PV at horizontal plane, the PV at optimal inclination angle (24 degrees for the

specific area), the PV using 2-axis tracker for optimum GHI exploitation, and the CSP solar energy inputs.

Based on the above climatological calculations it appears that the most balanced PV installation

solution in order to exploit efficiently the solar yield is the inclined planes at 24 degrees (this is due to

the latitude of Aswan, which is at 24o North). This is because, whilst the 2-axis tracker PVs can increase

the energy potential by 47% as compared to the horizontal PV and almost 40% as compared to the 24

degrees inclined PV (Table 1), they also increase significantly the total installation cost and need

demanding maintenance and support because of the moving parts. So, the energy scenarios for the

solar farm in Aswan are based on the 24 degrees PV and CSP mature technologies.

Page 36 of 127


Hourly Mean Solar Energy

Daily Mean Solar Energy

Monthly Mean Solar Energy

Figure 10: Mean monthly solar energy input to the PVs and CSPs in hourly, daily and monthly time horizons (in kWh/m2)

The inset values in the hourly and daily plots represent the mean hourly and daily solar energy per month respectively, while

the inset values in the monthly plot represent the annual total energy.

Page 37 of 127


These solar energy potential input values are in agreement with similar studies from the Fraunhofer

Institute for Solar Energy Systems (ISE, 2016) for Egypt where they found DNI values from 2,000 to

2,500 kWh/m2.

Table 1: Mean monthly solar energy input values to the PV and CSP systems

All the results are in kWh/m2 and are provided for the three-time scales (hourly, daily and monthly) for the specific area in

Aswan. The total values are the sums of the individual mean monthly values.

5.3. Development of scenarios based on energy needs

In the framework of this business plan a set of realistic solar farm scenarios has been developed. These

taken into account the energy needs and the proposed location that covers an area of 1.26 km2 (Figure

11). The key criteria for the proposed scenarios are:

▪ the energy adequacy (zero-net-energy vision) for the whole year period in all time scales

▪ the consideration of the sustainable growth and development of the hospital and the

residential area in terms of additional expected energy needs

With these overarching criteria in mind the study team has developed different scenarios that:

Hourly Daily Monthly

PV PV@24 PV2AX CSP PV PV@24 PV2AX CSP PV PV@24 PV2AX CSP

Jan 0.20 0.26 0.36 0.26 4.78 6.32 8.57 6.23 148 196 266 193

Feb 0.24 0.29 0.41 0.29 5.71 7.02 9.74 6.90 160 197 273 193

Mar 0.29 0.33 0.44 0.31 6.98 8.00 10.63 7.36 216 248 330 228

Apr 0.32 0.31 0.42 0.30 7.66 7.33 10.02 7.14 230 220 301 214

May 0.33 0.30 0.45 0.31 7.92 7.14 10.82 7.52 246 221 335 233

Jun 0.35 0.30 0.46 0.34 8.34 7.19 11.15 8.13 250 216 334 244

Jul 0.34 0.30 0.44 0.32 8.22 7.13 10.67 7.62 255 221 331 236

Aug 0.32 0.30 0.43 0.30 7.76 7.23 10.21 7.25 240 224 316 225

Sep 0.30 0.30 0.40 0.29 7.11 7.27 9.70 6.96 213 218 291 209

Oct 0.25 0.30 0.39 0.28 6.02 7.18 9.46 6.77 187 223 293 210

Nov 0.21 0.27 0.37 0.27 5.10 6.50 8.88 6.40 153 195 266 192

Dec 0.19 0.26 0.35 0.26 4.57 6.16 8.29 6.14 142 191 257 190

Mean 0.28 0.29 0.41 0.29 6.68 7.04 9.84 7.04 203 214 299 214

Total 2,440 2,569 3,593 2,568

The total mean monthly energy input in hourly, daily and monthly time horizons is shown in Figure

10 and the analytical energy input values in Table 1. The total solar energy input potential for the

PVs is 2,440 kWh/m2, for the PVs at 24° degrees is 2,569 kWh/m2, for the sun tracker based PVs

the energy rises to 3,593 kWh/m2, and finally for the CSP technologies the input energy is 2,568

kWh/m2.

Page 38 of 127


▪ Explore the advantages of both PV and CSP technologies

▪ Allow the optimal use of the total offered area (100% coverage)

▪ Allow the theoretical CSP energy production using 100% mirror coverage (without thermal

energy storage)

▪ Explore the options around a solar farm with nominal power of 50 MW with no land or

technology limitations

▪ Accommodate the possibility for a phased approach. A specific instructive case analysed is

that of the minimum adequate solar farm for the hospital's (Phase 1) and the residential area's

energy needs (Phase 2).

Figure 11: The specific area in Aswan that the potential solar farm will be placed

The total area is 300 Feddan which corresponds to 1,26 km2. [Maps produced by Hesham El-Askary]

Page 39 of 127


Figure 12: Mean monthly mirrors performance in kWh/m2

The graphs present results for the CSP Parabolic Trough (PT) and Solar Tower (ST) systems, as well as the PV Crystalline Silicon

(CS) and Cadmium Telluride (CdTe) materials at 24 inclination angle (upper plot). Mean monthly land surface performance

for the same technologies in MWh for the Aswan's specific installation area of 1.26 km2 (lower plot).

As described earlier, the most balanced PV solution is that with inclined panels at 24 degrees. Thus,

as far as PV scenarios are concerned, the energy output is based on the following panel materials: the

Crystalline Silicon (CS) which present combined losses of the order of 29%, and the Cadmium

Telluride (CdTe) with mean losses at about 20%8. With regards to CSP technologies, the most mature

are the Parabolic Trough (PT) and the Solar Tower (ST), both of which are more efficient than PV per

surface of collectors and energy storage, but less efficient per land surface (Figure 12).

The energy output per square meter for the PV CS is 175.10 kWh/m2 and for the PV CdTe is 196.31

kWh/m2 (Table 2). For the CSPs PT and ST the energy outputs per square meter of mirrors are 270.73

and 386.74 kWh/m2 respectively (indicating the better collectors’ efficiency), while the energy outputs

per square meter of total land surface (mirrors + facilities) are 90.24 kWh/m2 for the PT and 71.10

kWh/m2 for the ST (indicating the less land surface efficiency). We also present the required area for

each scenario and technology in m2 and in percentage in brackets (%) of the total provided area (1.26

km2).

On this basis, a complete overview of the scenarios is provided in Table 2 below. The specific energy

and financial considerations around these scenarios are presented in section 5.4, 5.5 and in Chapter 6

respectively.

8 The not favourable temperature coefficient for CS has a great impact on the yield for Aswan region(the opposite applies for the CdTe technology) and this is reflected in the losses quoted here.


Minimum scenario (7+3) MW output (kWh/m2) output mirrors (kWh/m2) output (MWh) area (m2) mirrors (m2)

PV CS 7MW 175.10 175.10 17,980 102,692 (8,15%) 102,692

PV CdTe 7MW 196.31 196.31 17,980 91,597 (7,27%) 91,597

PV CS 3MW 175.10 175.10 7,706 44,012 (3,49%) 44,012

PV CdTe 3MW 196.31 196.31 7,706 39,257 (3,12%) 39,257

Scenario 12MW (Table 9)

output (kWh/m2) output mirrors (kWh/m2) output (MWh) area (m2) mirrors (m2)

CSP PT 12MW 90.24 270.73 30,822 341,475 (27,10%) 113,825

CSP ST 12MW 71.10 386.74 30,822 433,423 (34,40%) 79,682

PV CS 12MW 175.10 175.10 30,822 176,052 (13,97%) 176,052

PV CdTe 12MW 196.31 196.31 30,822 157,032 (12,46%) 157,032

Scenario 20MW (Table 10)


CSP PT 20MW 90.24 270.73 51,374 565,517 (44,88%) 188,506

CSP ST 20MW 71.10 386.74 51,374 722,667 (57,35%) 132,857

PV CS 20MW 175.10 175.10 51,374 293,420 (23,29%) 293,420

PV CdTe 20MW 196.31 196.31 51,374 261,720 (20,77%) 261,720

CSP PT 12MW + PV CS 8MW 90.24 + 175.10 270.73 + 175.10 30,822 + 20,552 341,475 + 117,368

(36,42%) 113,825 + 117,368

CSP PT 12MW + PV CdTe 8MW 90.24 + 196.31 270.73 + 196.31 30,822 + 20,552 341,475 + 104,688

(35,41%) 113.825 + 104,688

CSP ST 12MW + PV CS 8MW 71.10 + 175.10 386.74 + 175.10 30,822 + 20,552 433,423 + 117,368

(43,71%) 79,682 + 117,368

CSP ST 12MW + PV CdTe 8MW 71.10 + 196.31 386.74 + 196.31 30,822 + 20,552 433,423 + 104,688

(42,71%) 79,682 + 104,688

Scenario 50 MW (Table 12)


CSP PT 50MW 90.24 270.73 128,367 1,410,000 (111.90%)

470,000

CSP ST 50MW 71.10 386.74 128,367 1,805,000 (143.25%)

331,836

PV CS 50MW 175.10 175.10 128,367 733,550 (58.22%) 733,550

PV CdTe 50MW 196.31 196.31 128,367 654,300 (51.93%) 654,300

CSP PT 12MW + PV CS 38MW 90.24 + 175.10 270.73 + 175.10 30,822 + 97,545 341,475 + 557,498

(71.35%) 113,825 + 557,498

CSP PT 12MW + PV CdTe 38MW 90.24 + 196.31 270.73 + 196.31 30,822 + 97,545 341,475 + 497,268

(66.57%) 113,825 + 497,268

CSP ST 12MW + PV CS 38MW 71.10 + 175.10 386.74 + 175.10 30,822 + 97,545 433,423 + 557,498

(78.64%) 79,682 + 557,498

CSP ST 12MW + PV CdTe 38MW 71.10 + 196.31 386.74 + 196.31 30,822 + 97,545 433,423 + 497,268

(73.86%) 79,682 + 497,268

CSP PT 10MW + PV CS 40MW 90.24 + 175.10 270.73 + 175.10 25,686 + 102,681

284,563 + 586,840 (69.16%)

94,855 + 586,840

CSP PT 10MW + PV CdTe 40MW 90.24 + 196.31 270.73 + 196.31 25,686 + 102,681

284,563 + 523,440 (64.13%)

94,855 + 523,440

CSP ST 10MW + PV CS 40MW 71.10 + 175.10 386.74 + 175.10 25,686 + 102,681

361,186 + 586,840 (75.24%)

66,402 + 586,840

CSP ST 10MW + PV CdTe 40MW 71.10 + 196.31 386.74 + 196.31 25,686 + 102,681

361,186 + 523,440 (70.21%)

66,402 + 523,440

Page 41 of 127


Max. area scenario (Table 11)


CSP PT 45MW 90.24 270.73 113,702 1,260,000 (100%) 420.000

CSP ST 35MW 71.10 386.74 89,586 1,260,000 (100%) 231.642

CSP PT 135MW 90.24 270.73 341,106 1,260,000 (100%) 1,260,000

CSP ST 190MW 71.10 386.74 487,297 1,260,000 (100%) 1,260,000

PV CS 86MW 175.10 175.10 220,626 1,260,000 (100%) 1,260,000

PV CdTe 97MW 196.31 196.31 247,350 1,260,000 (100%) 1,260,000

CSP PT 12MW + PV CS 62MW 90.24 + 175.10 270.73 + 175.10 30,822 + 159,247

341,475 + 918,525 (100%)

113,825 + 918,525

CSP PT 12MW + PV CdTe 70MW 90.24 + 196.31 270.73 + 196.31 30,822 + 179,795

341,475 + 918,525 (100%)

113,825 + 918,525

CSP ST 12MW + PV CS 56MW 71.10 + 175.10 386.74 + 175.10 30,822 + 143,836

433,423 + 826,577 (100%)

79,682 + 826,577

CSP ST 12MW + PV CdTe 63MW 71.10 + 196.31 386.74 + 196.31 30,822 + 161,815

433,423 + 826,577 (100%)

79,682 + 826,577

CSP PV Hybrid

Table 2: Full overview of scenarios

5.4. Overview of energy output for the different scenarios

For each of the scenarios presented above, the energy output has been calculated. The starting point

is the calculation of the temporal energy distribution for CSP and PV systems. Figure 13 describes the

temporal energy distribution of a 12 MW system using CSP (left) and PV (right) technologies. In both

cases the actual annual mean energy output is 30,822 MWh. For a 20 MW system (Figure 14), the

corresponding energy outputs are presented using only PV or CSP and a combination of them (in

proportion of 12 MW for CSP and 8 MW for PV). For combined solutions, one must highlight the

bridging of the gap between the different energy distribution of the CSP and PV exploitation

technologies.

Thus, based on the above calculations, the specific project's energy requirements and the available

land in Aswan (1.26 km2), the analytical energy outputs for a variety of possible scenarios (See Annex

I, tables 9 - 13) is calculated. Table 9 shows the analytical energy outputs of the 12 MW scenario, while

in Table 10 the 20 MW scenario is divided into 20 MW CSP or PV system and into a hybrid solution

with 12 MW CSP (there is a constructional limitation of 10 MW) and 8 MW PV. In Table 11 the full area

of 1.26 km2 was assumed to be covered with CSP (with and theoretically without energy storage

facilities) or PV. Table 12 presents 50 MW scenarios without land limitation. Finally, Table 13 shows

the analytical mirrors performance (without storage facilities, batteries, etc.) for the CSP and PV

technologies and materials.

Page 42 of 127


Figure 13: Analytical monthly mean energy output distribution for a 12MW CSP (left) and a 12MW PV (right)

The intraday distribution is in local time, while the total energy production in both technologies is 30,822 MWh.

Concerning the system and calculation assumptions, for the PV calculations a realistic efficiency value

of 12% has been used alongside a spatial coverage of 80% and material combined losses of 29% and

20% for CS and CdTe respectively (PVGIS-CMSAF). For the CSP, the energy storage facilities have been

considered (for a required capacity of 14 hours which ensures full self-sufficiency) and its heat losses

(land-weighted required total and mirrors area in all tables), the losses by shading, incidence angle

modifier, the end losses and the peak optical efficiency (Eck et al., 2014; Ouali et al., 2015). For the

solar farm's nominal power, the actual system power performance in MW has been used instead of

MWp, where the peak power rating on a solar system represents the most power that it would

produce under ideal conditions for solar production. Finally, the energy outputs for Aswan have been

cross validated with similar solar farm projects in Morocco, California, Spain, China and Southern

Africa as presented in sub-section 4.2.5. For all the max area scenarios, we used as a base the total

land surface of 1.26 km2, while for the 50 MW scenarios we assumed no land limitation with potential

extensions to the east of the initial proposed area (Figure 11). Finally, for the 2-Phase scenario we

calculated the minimum energy production based on the estimated and model simulated (DOE)

monthly mean energy requirements of the hospital and the residential area, presented below for

reference in Table 3.

Table 3: Monthly mean energy consumption

http://www.power-technology.com/projects/noor-ouarzazate-solar-complex/

https://www.nrel.gov/csp/solarpaces/project_detail.cfm/projectID=62

https://www.nrel.gov/csp/solarpaces/project_detail.cfm/projectID=3

http://www.huawei.com/en/all-products/Solar/References/Panzhihua

http://www.prnewswire.com/news-releases/south-africa-department-of-energy-awards-100-mw-solar-thermal-power-project-to-consortium-led-by-solarreserve-and-acwa-power-300017523.html

http://www.prnewswire.com/news-releases/south-africa-department-of-energy-awards-100-mw-solar-thermal-power-project-to-consortium-led-by-solarreserve-and-acwa-power-300017523.html

Page 43 of 127


Figure 14: Monthly mean energy output distribution

Presents results for the cases of a 12MW CSP or PV system (upper plot), and a 20MW system (lower plot) using exclusively

CSP or PV technologies, and a synergy of them at proportions 12 and 8MW for CSP and PV respectively.

5.5. Operational estimation of energy outputs

Electricity producing systems use different quantities of solar radiation: The Direct Normal Irradiance

(DNI) is applicable to Solar Thermal Power Plants while the Global Horizontal Irradiance (GHI) to

Photovoltaic systems. The energy source for any stand-alone photovoltaic (PV) system or

Concentrated Solar Power (CSP) plant is the solar insolation available at the location of the installation.

The performance of such systems is directly affected by the amount of insolation available to the

system. As described in Section 4.1, PV systems enable direct conversion of global horizontal

irradiance (GHI) into electricity through semi-conductor devices, while CSP systems generate solar

power by using mirrors or lenses to concentrate a large area of sunlight, or solar thermal energy, onto

a small area. Electricity is generated when the concentrated light is converted to heat, which drives a

heat engine connected to an electrical power generator or powers a thermo-chemical reaction. Heat

storage in molten salts allows some solar thermal plants to continue to generate after sunset and adds

https://en.wikipedia.org/wiki/Solar_power

https://en.wikipedia.org/wiki/Solar_power

https://en.wikipedia.org/wiki/Solar_thermal_energy

https://en.wikipedia.org/wiki/Electricity

https://en.wikipedia.org/wiki/Heat_engine

https://en.wikipedia.org/wiki/Power_generator

https://en.wikipedia.org/wiki/Thermochemical

Page 44 of 127


value to such systems when compared to photovoltaic panels. For the design, implementation and

efficient operation of these systems, the weather-dependent production plays a key role and

determines the balance between production and demand.

The need for improved solar energy forecasting is increasing as more solar farms come online

worldwide. With an increasing share of the energy portfolio for many electrical utility companies,

incorporating the highly variable power output from solar arrays into the grid is becoming increasingly

difficult. Accurate predictions of the irradiance received at individual PV (where GHI is needed) or CSP

installations (where DNI is needed) are vital. Utilities require these predictions in the nowcasting

(minutes to 1-2 hours ahead) and forecasting (1-2 days ahead) time scales with real-time high

temporal frequency (every 5-15 minutes) to perform load balancing properly. Such long- and short-

term forecasting services are very important for grid operators in order to guarantee the grid stability

and for those power plants that can be considered manageable, such as CSPs.

Forecasting services are related with the weather forecasts (every 3-6 hours for 1-2 days ahead)

provided by the WRF, while the nowcasting services are related to very high temporal resolution (a

forecast every 10 or 15 minutes), so automatic atmospheric/weather data acquisition and processing

is a major requirement in order to apply these techniques. Since the launch of Earth observing

satellites, such as MSG, nowcasting techniques have also been developed from an image processing

point of view. The main advantage of these techniques is the possibility to monitor a lot of

meteorological information in almost real time. This high value information is used as input to

radiative transfer models based on image processing techniques that in the end calculates solar

radiation related parameters.

For the above energy forecast requirements, the Solar Energy Nowcasting SystEm (SENSE) developed

by SOLEA (www.solea.gr), produces state-of-the-art solar energy applications and is based on the

synergy of Neural Networks (NN), Radiative Transfer (RT) simulations and real-time satellite (clouds

movement) and CAMS9 based retrievals (aerosol and Khamaseen forecast). A NN is trained on a large-

scale (2,5 million record) look-up table (LUT) of radiative transfer simulations to convert satellite cloud

and aerosol products directly into solar radiation spectra. As a result, SENSE is capable of producing

maps, databases and time series of spectrally-integrated irradiances of the order of 105 pixels (that

represents a 10 X 10 degree region) within 1 minute. The Solar Energy Nowcasting SystEm (SENSE)

comes to unite the multifarious local and regional solar energy needs and sustainable development

policies with the nowadays available capacities and state-of-the-art technologies. Thus, SENSE

supports the optimal solar energy exploitation in support of these regional needs and for active and

effective integration of these technologies to the national sustainable development economies and

strategies. The quantification of the clouds’ and aerosols’ impact on the solar energy potential

guarantees the reliability of the real-time, nowcasting and forecasting energy results. With the use of

developed and improved EO real time and climatology services, products and data bases, SENSE is

able to deliver solutions addressing the needs of relevant stakeholders and decision makers like

Ministries of Electricity and Renewable Energies, Electric Power Transmission Operators and Solar

Energy investors from the private sector.

In the context of the New Aswan Heart Centre, the level of accuracy and timeliness enabled by SENSE,

is critical not only for the execution of energy calculations presented herein, but also for the operation

of the off-site solar farm through its reliable nowcasting and forecasting capabilities.

9 https://atmosphere.copernicus.eu/

https://en.wikipedia.org/wiki/Photovoltaic

http://www.wrf-model.org/index.php

http://www.solea.gr/

https://atmosphere.copernicus.eu/

Page 45 of 127


Ivan

pah

So

lar

Elec

tric

Gen

erat

ing

Syst

em

so

lar

tow

er

(Cre

dit

s: B

usin

essw

ire.

com

)

Page 46 of 127


6. Economic Modelling At the core of this business plan lies the development of an economic model that can be used as a

source of strategic guidance, shedding light on the financial and energy-related parameters of the

various scenarios for the off-site solar farm (see Table 2 for an overview of all scenarios). The

development of these scenarios has been done in a completely unbiased manner, i.e. without any

preference to one technology over the others, to specific coverage of the designated area or any other

such consideration. Instead, driven by the aim to identify the optimal option for the off-site solar

farm, the study team has developed and tested different hypotheses built on the fundamental

principles listed below:

▪ 100% Green Operation for the New Aswan Heart Centre: Meeting this condition can be

achieved either by installing CSP solutions or PV with storage. Thus, the selection of scenarios

relies on whether this condition is met or not, and through which technological solution this

is carried out.

▪ Use of the available land: The designated area extends over 1.26 km2 which can be used for

the deployment of the solar farm. A range of land use options have been considered.

▪ Nominal power: Different levels of nominal power have been considered, allowing the direct

comparison of PV and CSP solutions, and helping to identify exploitation options.

▪ Economic performance: Whilst the development of the off-site solar farm is motivated by a

strong vision for 100% energy self-sufficiency and overall contribution to the sustainable

development and well-being of the area, the economic performance of the various scenarios

is essential for potential investors.

Taking these fundamental principles into account, and considering the four most widely deployed

solar power technologies (i.e. PV CS, PV CdTe, CSP PT and CSP ST) and their possible combinations, the

economic modelling tool has been developed in a robust, scalable and flexible manner.

▪ Robust: The model is built in a manner that allows the automatic projection of results based

on a concrete set of parameters and key assumptions. Tuning the parameters and changing

the assumptions can be easily accomplished without impeding the operation of the model.

▪ Scalable: The model can be easily scaled to include additional scenarios, extend over a wider

period, and introduce additional dependencies and calculations.

▪ Flexible: An additional layer of sophistication with regards to the calculated parameters and

their visualisation can be easily accommodated.

Figure 15: A robust, scalable and flexible economic modelling tool

Page 47 of 127


For each scenario generated by the study team and incorporated into the economic modelling tool,

the financial and energy performance is projected and visualised in a semi-automated way. The

outputs of the tool rely on the definition of a set of key assumptions in relation to the input values

for the various parameters (e.g. costs of the different technologies, electricity consumption costs,

etc.). A thorough discussion on these assumptions is provided in the subsection below.

6.1. Key assumptions

In deciding the most accurate set of parameters for the economic modelling of the various scenarios,

the study team has performed extensive background research and has consulted as much as possible

representatives of the competent authorities in Egypt (in particular NREA and MOERE). Thus, the team

has striven to identify up-to-date prices for the different types of solar technologies, applicable if

possible to the case of Egypt and validated against multiple sources. In this effort, it has become

apparent that the landscape of solar projects shows high complexity, lack of transparency, limited

information on “younger” technologies (i.e. CSP) and at times biases towards certain solutions. In

this regard, it is important to recognise (IRENA, 2014) that the total installed costs of solar power

technologies vary significantly by country and region. Moreover, when the Levelised Cost of Electricity

(LCOE) is considered, no single “true” value for a given technology can be defined, as the LCOE

depends on the installed and O&M costs, economic life and efficiency factors which are technology-,

project- and site-specific (IRENA, 2014).

In this complex landscape, the study team has concluded that the safest way to navigate is to pursue

a consolidation of information between well-trusted sources such as the various IRENA reports (2014;

2016a; 2016b) (especially the most recent ones) and a recent (December 2016) report on the

“Electricity cost from renewable energy technologies in Egypt” by Fraunhofer ISE (2016). The findings

in these reports have been further cross-validated with other recent sources including Lazard’s

Levelized Cost of Energy Analysis (Lazard, 2016), and reports by NREL (2016b; 2016c).

The main focus was set on identifying the applicable values for the total installed costs and the O&M

costs, as they are the ones affecting mostly the final output of each scenario. The results of this

analysis are shown on Table 4 below followed by a discussion on each of the selected values.


Table 4: Overview of cost assumptions for the economic model

Total Installed Cost (USD/W) O&M cost

Tech

IRENA

(2014/

2016)

Fraunhofer

2016

Value

in

2016

Reduction

by 2020

Value

used in

EVF

model6

IRENA Fraunhofer

2016

Value

in

2016

Reduction

by 2020

Value

used

in EVF

model

PV CS 1.2 –

1.91 1.3 - 1.6 1.43 30%5 0.98 10-187 26 269 15.0%10 22.1

PV CdTe 1.2 –

1.91 1.3 - 1.6 1.33 30%5 0.91 10-187 26 269 15.0%10 22.1

CSP PT 3.5-7.32 2.9 - 4.5 NA 30%5 NA 0.028 0.02 0.02 15.0%10 0.017

CSP PT

with

storage

6.4 -102 4.6 - 5.9 6.7054 30%5 4.693 0.038 0.02 0.02 15.0%10 0.025

CSP ST

with

storage

7.6 -

10.72 NA 7.6054 33%5 5.703 0.038 0.02 0.02 15.0%10 0.025

Notes:

(1) Values taken from IRENA, 2016a

(2) Values taken from IRENA, 2014

(3) Values resulting from the combination of IRENA and Fraunhofer ISE sources. They are taken closer to

the lower end of the provided range as the Fraunhofer source provides values for Egypt, and other

sources (e.g. NREL, 2016b) provide similar values for other markets. CdTe tends to be cheaper than CS

and thus such a small difference has been incorporated.

(4) Values derived by combining the available data from IRENA 2014 with those of Fraunhofer ISE 2016.

Thus, the relative reduction in price for CSP PT with 8h storage has been calculated. This ratio is then

assumed to apply for 14h CSP PT and 14h CSP and thus, using the relevant values in Table 6.2 of IRENA

2014 the projected values for 2016 are provided.

(5) According to IRENA 2014, from 2011-2014 installed costs have fallen by 37% so it is safe to assume at

least 30% reduction towards 2020. Other reports have even higher expected reductions for the same

timeframe. Similarly, for CSP ST a greater reduction has been proposed according to more recent data

by IRENA10.

(6) The model produced by Evenflow (EVF) is running from 2020 onwards. Thus, all values inserted in the

model apply for that date. This includes O&M costs which in the model are taken as constant and not

further reduced on a year by year basis.

(7) Values taken from IRENA 2016b. They correspond to the US market for 2015. For PVs the values are

given in terms of USD/kWp.

(8) IRENA 2014 provides a range of 0.02-0.04 USD/kWh (for 2014) which encompasses all miscellaneous

costs (incl. insurance). CSP PT without storage corresponds to the lower end of this spectrum while CSP

PT and CSP ST with storage are found in the middle.

(9) The values in this column are taken in line with Fraunhofer ISE 2016 as they seem to reflect the situation

in Egypt more accurately.

(10) A more modest – compared to total installed costs and other reports – reduction has been envisaged

for O&M costs.

10 See for example https://costing.irena.org/media/10597/Solar-and-Wind-Cost-Reduction-Potentials-CEM-15-March-2016.pdf. This source provides a longer discussion of cost reduction drivers for each technology.

https://costing.irena.org/media/10597/Solar-and-Wind-Cost-Reduction-Potentials-CEM-15-March-2016.pdf

https://costing.irena.org/media/10597/Solar-and-Wind-Cost-Reduction-Potentials-CEM-15-March-2016.pdf

Page 49 of 127


6.2. Cost structure

In understanding the economic performance of each scenario, it is important to construct a complete

picture of the different types of costs considered. Thus, the main cost drivers for each scenario include

capital costs (CAPEX) incurred at the start of the project and entailing the bulk of the investment, and

operation & maintenance costs (OPEX) which are recurrent over the lifetime of the project. In

addition, the model considers the cost of electricity from the grid applicable to the cases when the

energy produced by the solar farm does not cover the operational needs of the hospital and residential

area (night time for PVs, Khamaseen, scenarios with less than 100% energy requirement coverage).

6.2.1. CAPEX

The capital costs considered in the model include the total installed costs for the purchase and

installation of the selected solar power solution and, in the case of PVs, the potential purchase of

batteries for energy storage. The capital costs of any PV system comprise two main components: (i)

the module which converts sunlight to electricity and (ii) the Balance Of System (BOS) which

encompasses all other components and services required to make the PV system operational,

including inter alia labour costs, inverter, permits, supply chain costs, etc. Similarly, for CSPs there are

costs associated to the main components including the solar field, the receiver, the heat transfer

system, the thermal storage and the power block (NREL, 2016a).

The Evenflow economic model addresses total installed costs as a “bundled” number that ranges as

function of the technology type and the nominal power of a given solution (e.g. CSP PT 50MW).

However, it must be noted that future reductions are driven more strongly by reductions in specific

components (e.g. BOS). For reference, the figure below (adapted from IRENA 2014 and IRENA 2016a)

presents an indicative breakdown of installed costs for utility-scale PV and CSP projects.

Figure 16. Indicative capital costs for PV and CSP projects.

For PV scenarios with storage the cost of batteries’ purchase and installation is placed at 300 USD/Wh

(Lazard, 2016; IRENA, 2015a11). It must be noted that in the case of PV with storage scenarios the initial

investment cost rises significantly12.

11 See for example figures 20 and 21 in the quoted report. 12 See figure ES-4 in NREL, 2016a.

Page 50 of 127


6.2.2. OPEX

Whilst operation and maintenance costs are significantly lower than the initial investment associated

with the purchase and installation of a given solution (i.e. total installed costs), they do impact its

annual performance. Maintenance costs are associated to general site inspections, cleaning of the

systems, checking of the various components (inverters, mounting/tracking, storage), etc13. These

costs can comprise up to 45% of the total O&M (IRENA, 2016b). Operation costs include inter alia land

lease (when applicable), local taxes, site security and administration costs. In the case of CSP the values

found in the literature for O&M include by default the cost of thermal storage. In contrast, for PVs the

storage options (i.e. batteries) shall be taken into account separately. Thus, as discussed in the

technical note below for PV scenarios including storage, an OPEX cost associated to the batteries must

be taken into account. For the purpose of this model, the assumption on PV battery OPEX is placed at

8.5 USD/kWh/year which corresponds to the value given by (Lazard, 2016) taking into account a

reduction of 15% by 2020 (in line with the assumed reductions of other OPEX costs).

13 For a thorough overview of PV system maintenance see SolarABCS, 2013

Technical note on PV batteries

The use of batteries in PVs differs from the use of batteries in other common battery applications.

For PV systems, the key technical considerations are that the battery experience a long lifetime

under nearly full discharge conditions. Common rechargeable battery applications do not

experience both deep cycling and being left at low states of charge for extended periods of time.

The key function of a battery in a PV system is to provide power when other generating sources

are unavailable, and hence batteries in PV systems will experience continual charging and

discharging cycles. All battery parameters are affected by battery charging and recharging cycle.

In many battery types, including lead acid batteries, the battery cannot be discharged below a

certain level or permanent damage may be done to the battery. In many types of batteries, the

full energy stored in the battery cannot be withdrawn (in other words, the battery cannot be fully

discharged) without causing serious, and often irreparable damage to the battery. The Depth of

Discharge (DOD) of a battery determines the fraction of power that can be withdrawn from the

battery. For example, if the DOD of a battery is given by the manufacturer as 25%, then only 25%

of the battery capacity can be used by the load. In the case of New Aswan, ideally, a battery bank

should be sized to be able to store power for 5 days of autonomy during Khamaseen or cloudy

weather. If the battery bank has smaller than 3-days capacity, it is going to cycle deeply on a

regular basis and the battery will have a shorter life. The charging/discharging rates affect the

rated battery capacity. If the battery is being discharged very quickly (i.e., the discharge current is

high), then the amount of energy that can be extracted from the battery is reduced and the battery

capacity is lower. This is because the necessary components for the reaction to occur do not

necessarily have enough time to move to their necessary positions. Only a fraction of the total

reactants is converted to other forms, and therefore the energy available is reduced. Alternatively,

when the battery is discharged at a very slow rate using a low current, more energy can be

extracted from the battery and the battery capacity is higher. Therefore, the capacity of batteries

should include the charging/discharging rate. A common way of specifying battery capacity is to

provide the battery capacity as a function of the time required to fully discharge (note that in

practice the battery often cannot be fully discharged). As a result, the PV systems with storage

presents some major issues for demanding energy consumptions which in return could cause a

reduced capacity and batteries’ lifetime, with a direct financial impact (see storage OPEX).

Page 51 of 127


6.2.3. Cost of electricity from the grid

As discussed earlier, one of the fundamental principles for the development and operation of the off-

site solar farm is that of securing the independence from the grid. Nonetheless, the need to connect

to the grid and draw energy cannot be 100% overcome. That is because for PV scenarios the default

configuration is without storage, and due to the Khamaseen affecting PV and CSP scenarios alike.

Therefore, it has been imperative to identify the tariff for buying electricity from the grid. To that end,

the study team has consulted with NREA who pointed to the applicable prices from EgyptERA14.

According to this, the off-peak tariff is 22.12 USD/MWh (applicable to 30% of the daily consumption),

whilst the peak time tariff is 33.13 USD/MWh (applicable to 70% of the daily consumption). It must

be noted that these tariffs are regularly revised by the competent Egyptian authorities.

6.3. Revenue streams

There are two major revenue streams associated with the operation of the off-site solar farm. The

first entails the provision of energy to the grid against an agreed price (USD/kWh). Clearly the volume

of this revenue is directly tied to the amount of energy “sold” on the grid, over and above the coverage

of the energy requirements of the hospital and the residential area. The second corresponds to the

costs avoided in the case of solutions with storage. In other words, when operating on 100%15 green

energy (this primarily applies to CSP solutions but, in principle, to PV with batteries too), there is no

need to draw energy from the grid. The details for these two streams are discussed in the following.

6.3.1. Selling to the grid

One of the main drivers for the development of the off-site solar farm is the use of the produced

energy towards covering (partially or fully) the requirements of the New Aswan Heart Centre and its

adjacent residential area. Nonetheless, given the very high energy output potential of the region and

the size of the designated area, the perspective of selling a considerable, additional amount of energy

to the grid has been studied.

The calculation of the associated revenue is straightforward; one needs to multiply the “excess”

energy by the price (USD/kWh) applicable to this project. As discussed in section 4.2.3, different

schemes apply in Egypt, for each of which different price for energy sold to EETC can be expected. The

case of the off-site solar farm associated with the New Aswan Heart Centre, seems to fall either under

a modified version of the “Competitive bidding mechanism for build-own-operate (BOO) contracts”,

or the “Independent power production through third party access”. In either case, the price will be

defined in agreement with EETC and EgyptERA within a Power Purchase Agreement (PPA).

In the course of preparing this business plan, Evenflow and its experts have consulted with Egyptian

authorities’ representatives, who advised that a feasible price would amount to 0.0382 USD/kWh.

Three key points must be underlined:

14 Table of prices accessible here http://egyptera.org/en/t3reefa.aspx. The relevant section is medium voltage consumers. At the time of writing the exchange rate was 0.056 USD per Egyptian pound. 15 Excluding a 2.74% of the total energy requirements drawn to cover the needs of the hospital and the residential area in the occurrence of Khamaseen.

http://egyptera.org/en/t3reefa.aspx

Page 52 of 127


▪ This price is significantly lower than those foreseen in the FiT scheme (0.0788 – 0.084

USD/kWh).

▪ As new projects are procured or launched, not only in Egypt but in the global market, and

“feed-in” prices are reduced in correlation to reduced investment and operation costs (for

both CSPs and PVs), this price might be also reduced by the time the project kicks-off. Thus,

the quoted price should be seen as an assumption that should be further substantiated in

direct contact with Egyptian authorities.

▪ Given the lack of available data on prices for energy produced in existing CSP projects in Egypt,

and the absence of any indication towards differentiated treatment of CSP vis-à-vis PV, the

study team has assumed that this price applies equally to CSPs and PVs.

In addition, wheeling charge costs have been calculated based on input data by NREA (0.00492

USD/kWh). These are calculated for each scenario based on the annual amount of energy supplied to

the grid.

6.3.2. Avoided energy costs

The operation of the off-site solar farm enables the partial or complete independence from energy

supply coming from the grid (depending on the selected scenario). Thus, a significant cost associated

with paying for energy produced by exploitation of fossil fuel and distributed in the EETC grid can be

avoided. The volume of the avoided costs depends on the selected scenario; thus, PV solutions ensure

energy self-sufficiency for a few hours per day (unless coupled with batteries), whilst CSP solutions

can guarantee 24 hours supply of solar energy (thanks to the thermal storage) over the whole year.

Therefore, recalling that the weighted average cost of electricity from the grid is 29.83 USD/MWh16,

the avoided costs for scenarios completely covering the energy requirements of the site this amounts

to approximately USD 669,000.

6.4. Model operation

The model projects the economic performance of each of the 3717 defined scenarios (PV, CSP and

hybrid) over a period of 30 years. The annual energy output in each case is used to calculate the

amount of energy available for supply to the grid, after meeting the energy requirements of the New

Aswan Heart Centre and its residential area. Having calculated the initial costs of purchasing and

installing the solar farm (CAPEX), the model accounts for annual costs (OPEX and costs for purchasing

electricity from the grid at night or during Khamaseen events) and annual revenues (selling to the grid

and avoiding energy costs). The resulting annual balance as well as the overall profitability over the

30-year period is presented in dedicated graphs for each scenario.

16 This is based on data found on http://egyptera.org/en/t3reefa.aspx and assuming that 30% of the daily consumption is off-peak, while 70% is at peak prices. 17 There are 32 basic scenarios (at 12, 20 and 50 MW, plus the Max. Area set) and four “minimal” options. In this report, a final “Phased” scenario has been indicatively analysed; many other combinations are possible.

http://egyptera.org/en/t3reefa.aspx

Page 53 of 127


6.4.1. Options and parameters

Further to the selection of a pre-built scenario, the model can be configured by adjusting the following

parameters and options:

▪ Phases 1/2/3: "Duration", "Coverage": These options determine the start of the modelling

period (set by default to 2020), and the duration of each phase (for phased approaches), as

well as the extent to which the Aswan energy requirements are covered in each phase.

Figure 17: Selection of scenario and main parameters for each phase

Phased-approach functionality

The model allows for the adoption of a three-phase approach, designed to offer a view on a

gradual and cumulative investment approach, instead of one large investment spanning the 30-

year timeframe. Thus, the model allows for the selection of scenarios that observe a potential

phased-approach in the development of the New Aswan Heart Centre itself. It must be noted that

at this point only a specific set of scenarios is meaningful for the phased approach. For example,

one can unbundled options of the hybrid scenarios (e.g. 12 MW CSP in Phase 1 followed by 20 or

50 MW PV in Phase 2). All other options are reaching specific boundaries (e.g. area of the

designated site). Nonetheless, the phased approach functionality is operational and could include

additional scenarios for each phase in the future.

Page 54 of 127


▪ Start Year: The model start year is set by default to 2020. This choice entails assumptions

associated with the expected reduction in capital and O&M costs, and therefore if another

start year is set, adjustments in the input prices must be made.

▪ Aswan energy requirements for Hospital/Residential: These values determine the

requirements for Aswan's hospital and residential areas.

▪ Electricity consumption scaling: This factor can be applied to model the effect of increased

energy requirements year-to-year, expressed as a percentage increase with respect to the

previous year. This value is not set by default.

Figure 18: General settings of the economic model

▪ Include savings from energy costs avoided?: By covering the needs of Aswan's hospital and

residential facilities through solar power, the project effectively annuls the cost of purchasing

electricity in order to cover those requirements. This saving is considered to be a benefit of

the project, reflected as a form of revenue or avoided cost. This parameter includes or

excludes the avoided costs from the revenues of the project.

There is a set of parameters connected with the inclusion of storage systems for the PV scenarios. PV

technology requires a storage system in the form of batteries in order to be able to supply energy

during darkness or storms. CSP, by its nature, first converts solar radiation into thermal energy in the

form of molten salt or oil, before conversion to electrical energy becomes possible (via steam

turbines). This means that CSP systems can readily store energy in thermal form during the

intermediate step. PV, on the other hand, generates electrical energy directly from the light of the

sun, and this can only be stored in battery systems, which are rather expensive. It must be noted that

the feasibility in practice of operating such a large storage system is questionable. Nonetheless, given

recent projects being announced whereby large-scale use of batteries is planned and the potential of

cost breakthroughs this option has been provided.

Page 55 of 127


▪ "Include PV storage?": Enabling this option includes the price of such systems in the model

output, and thus allows PV-based systems to operate 24/7. Note that if this option is selected,

storage OPEX for PV should also be activated. This is done by default but it should be de-

activated in the case of a hybrid scenario.

▪ "Cost of PV batteries": This has been set according to the best information available to the

study team (see 6.2.1).

▪ "Avg. night energy required": This defines the size of the batteries required to power the

Aswan Heart Centre's hospital and residential areas.

▪ "Electricity consumption at night (as % of annual total)": This parameter is used to calculate

the cost of purchasing electricity from the grid at night in case no PV storage is selected.

▪ "Include storage OPEX for PV?" / "Cost of storage OPEX for PV" / "Proportion of energy

stored in battery over 1 year": These 3 parameters control the inclusion of storage OPEX in

the model, and include factors determining its cost. This has been set according to the best

information available to the study team. PV storage is selected by default but it should be de-

activated in the case of a hybrid scenario.

Figure 19: Parameters related to PV scenarios

Page 56 of 127


▪ Number of days of required grid coverage during Khamaseen events: A certain quantity of

grid-drawn energy is required every year to account for the potential missing sunlight during

Khamaseen storms. The assumption of 10 full days (out of the 50 on average over the period)

has been taken, based on the rule-of-thumb of approximately one full day a week of outage,

with most events only lasting for a few hours during the day.

Figure 20: Khamaseen related parameters

▪ "Total installed cost", "Operations and maintenance (O&M)": Prices for the installation (total

installed cost, which includes purchasing and all initial deployment costs) and operations and

maintenance (O&M) of the various technological options (PV CS and CdTe, CSP PT and ST)

have been sourced from the literature. They are expressed in USD/W (fixed by nominal/peak

power) for total installed cost. For O&M, they are expressed in USD/W (nominal) for PV and

USD/Wh (variable by output) for CSP (see 6.2.2).

Figure 21: Price-related parameters

Page 57 of 127


▪ "Tariffs for selling electricity to the grid", "Tariffs for purchasing electricity from the grid",

“Wheeling charges”: These options determine the cost of selling electricity to the grid and

buying power from the grid (in cases of PV without storage, and for covering Khamaseen

outages).

Figure 22: Tariff-related parameters

▪ Financing parameters: A series of options related to the inclusion of financing for the initial

capital is available. This includes:

o the share of equity which allows for a portion of the total cost to be covered by

investment in exchange for equity

o the annual interest rate on the loan and its lifetime

Figure 23: Financing parameters (example)

Having selected the desired scenario and the corresponding parameters, the results for its economic

and energy-related performance are plotted in a series of graphs and presented in relevant tables.

The section below provides a comprehensive overview of the actual results for the different bundles

of scenarios.

6.5. Results for the different scenarios

There are five “families” of scenarios, three of which are defined by their nominal power (12MW,

20MW and 50MW), one by maximising the output in the given site (i.e. filling up the available area

with PV, CSP or combinations thereof) and one deployed in a phased approach. The analysis of the

results for each family follows below, while the complete series of graphs for each individual scenario

is found in Annex II.

Page 58 of 127


6.5.1. 12MW Scenarios

This family of scenarios includes 4 scenarios with output of 30,822 MWh/year, enough to cover the

energy requirements of the hospital and the adjacent residential area (amounting to 22,423

MWh/year), but also to compensate for potential installation failures or other impediments to the

optimal performance of the solar farm. Thus, while a 10MW solar farm would suffice for the quoted

needs it is considered prudent to allow for a slightly higher capacity. This family of scenarios serves

also as a showcase for the main characteristics of the different technological options. Thus, it already

becomes clear that:

▪ PV solutions are cheaper than CSP ones given the lower CAPEX and OPEX costs

(notwithstanding PV with storage options). This is reflected in the graphs below (Figure 24).

▪ CSP options are the only viable solution towards satisfying the 100% green energy production,

since the cost of purchasing and maintaining/operating PV batteries is very high (Figure 24).

▪ Seen from a purely financial perspective, only the PV without storage solutions succeed in

breaking even in a reasonable timeframe (best for CdTe with 21 years) – but they don’t satisfy

the energy requirements of the hospital (see Figures 25 and 26).

PV CS without storage (CAPEX)

PV CS with storage (CAPEX)

CSP PT (CAPEX)

CSP ST (CAPEX)

PV CS without storage (OPEX)

PV CS with storage (OPEX)

Page 59 of 127


CSP PT (OPEX)

CSP ST (OPEX)

Figure 24: CAPEX and OPEX graphs for 12MW scenarios

CSP PT

CSP ST

Page 60 of 127


PV CS with storage

PV CdTe with storage

Figure 25: Break-even analysis for 12MW solutions with storage

PV CS without storage

Page 61 of 127


PV CdTe without storage

Figure 26: Break-even analysis for 12MW PV solutions without storage

Table 5 below summarises the findings for this family of scenarios.

Scenario Initial

Capital

Investment

Total

Annual

Cost

Total

Annual

Revenues

Total

Annual

Cash

Flow

Break

Even Point

LCOE Total

Output

USD K USD K USD K USD K years USD/kWh MWh/year

I - CSP PT 56,320 832 990 157 >30 0.236 30,822

II - CSP ST 61,141 832 990 157 >30 0.253 30,822

III - PV CS (with storage)

23,760 38,453 990 -37,463 N/A 1.287 30,822

IV - PV CdTe (with storage)

22,920 38,453 990 -37,463 N/A 1.284 30,822

Table 5: Summary table for 12MW with storage solutions


This family of scenarios includes 8 scenarios with output of 51,374 MWh/year, enough to cover the

energy requirements of the hospital and the adjacent residential area, but also supply additional

energy to the grid. Beyond the 4 single technology scenarios, this family includes 4 hybrid solutions,

whereby a 12MW CSP is coupled with an 8MW PV option. On studying the results of these hybrid

solutions, it becomes quickly apparent that:

Page 62 of 127


▪ The advantages of each of the two technologies are well-exploited. Thus, the 12MW CSP

solutions ensure complete coverage of the site’s energy requirements all year long. The

additional energy produced by the relatively cheaper PV solutions is then supplied to the grid

ensuring an additional revenue that improves the financial perspective of the solution (as

compared to CSP-only options). This is reflected in the graphs below (Figure 27).

▪ Despite a distinct improvement of the economic performance of the hybrid solution, the

break-even point is reached beyond the 30 years projected in the model. This is because the

total annual revenue from selling to the grid and avoiding costs amounts to approx. USD 1.8

million whereas the combined initial investment for the solar farm is close to USD 65 million

with an annual OPEX of close to USD 1.1 million. As before, the PV solutions without storage

have a very good break-even profile but they don’t satisfy the condition of independence from

the grid (Figure 28).

▪ Seen from an LCOE perspective, the best options for this family of scenarios are the hybrid

ones (see Table 6) [notwithstanding the PV without storage which don’t satisfy energy

requirements].

CSP PT (CAPEX)

CSP PT (Annual Cash Flow)

Page 63 of 127


Hybrid: 12MW CSP PT and 8MW PV CS (CAPEX)

Hybrid: 12MW CSP PT and 8MW PV CS (Annual Cash Flow)

Figure 27: Comparison of 20MW solutions’ costs and revenues (CSP only vs hybrid)

20 MW PV CdTe (without storage)

Page 64 of 127


20 MW CSP ST

Hybrid: 12MW CSP PT and 8MW PV CS

Hybrid: 12MW CSP ST and 8MW PV CdTe

Figure 28: Break-even analysis for different 20MW solutions

Page 65 of 127



Scenario Initial

Capital

Investment

Total

Annual

Cost

Total

Annual

Revenues

Total

Annual

Cash Flow

Break

Even

Point

LCOE Total

Output


I - CSP PT 93,867 1,447 1,775 328 >30 0.237 51,374

II - CSP ST 101,902 1,447 1,775 328 >30 0.255 51,374

III - PV CS

(without storage)

19,600 754 1,574 820 23 0.054 51,374

IV - PV CdTe

(without storage)

30,200 754 1,574 820 22 0.051 51,374

V - CSP PT (12) + PV

CS (8)

64,160 1,110 1,775 665 >30 0.151 51,374

VI - CSP PT (12) +

PV CdTe (8)

63,600 1,110 1,775 665 >30 0.150 51,374

VII - CSP ST (12) +

PV CS (8)

68,981 1,110 1,775 665 >30 0.160 51,374

VIII - CSP ST (12) +

PV CdTe (8)

68,421 1,110 1,775 665 >30 0.159 51,374



This family of scenarios has been developed in response to the potential intention of the investors to

build a 50MW solar plant. It includes 12 scenarios: 4 correspond to single-technology solutions18 and

8 to hybrid solutions (either 10MW CSP and 40MW PV, or 12MW CSP and 38MW PV). Analysing the

results for the individual scenarios allows the following observations:

▪ As with the 20MW family, here too, the hybrid solutions are the most performant. Thus,

despite the higher initial investment related to the size of the solar farm, the sheer volume of

energy sold onto the grid allows for a better economic performance (Figure 29).

▪ By comparing the two hybrid configurations (i.e. 12+38 vs 10+40 where in both cases we look

at CSP ST+PV CdTe) it becomes clear that the latter has a better LCOE (0.094 vs 0.086) and

break-even perspective (34 years vs 32 years). This is due to a smaller investment required on

CSPs and a larger amount of energy available for selling to the grid (Figure 30 and Table 7).

▪ As before, the PV-only solutions (without storage) have the best break-even profile, but they

don’t satisfy the energy requirements of the New Aswan Heart Centre.

18 It must be noted that 50MW CSP solutions do not actually fit in the available area. They are presented with the aim to highlight the comparative advantages of each solution and reflect on the optimal scenario.

Page 66 of 127


CSP PT and CSP ST (Annual Cash Flow)

Hybrid: 12+38 (Annual Cash Flow)

Hybrid: 10+40 (Annual Cash Flow)

Figure 29: Comparison of 50MW solutions’ costs and revenues (CSP only vs hybrid)

Page 67 of 127




Figure 30: Break-even analysis for different configurations of hybrid 50MW solutions

Page 68 of 127



Scenario Initial

Capital

Investment

Total

Annual

Cost

Total

Annual

Revenues

Total

Annual

Cash Flow

Break

Even

Point

LCOE Total

Output


I - CSP PT 234,668 3,751 4,716 965 >30 0.238 128,367

II - CSP ST 254,756 3,751 4,716 965 >30 0.256 128,367

III - PV CS

(without storage)

49,000 1,795 4,515 2,720 18 0.053 128,367

IV - PV CdTe

(without storage)

45,500 1,795 4,515 2,720 16 0.051 128,367

V - CSP PT (12) + PV

CS (38)

93,560 2,152 4,716 2,564 >30 0.092 128,367

VI - CSP PT (12) +

PV CdTe (38)

90,900 2,152 4,716 2,564 >30 0.090 128,367

VII - CSP ST (12) +

PV CS (38)

98,381 2,152 4,716 2,564 >30 0.096 128,367

VIII - CSP ST (12) +

PV CdTe (38)

95,721 2,152 4,716 2,564 >30 0.094 128,367

IX - CSP PT (10) +

PV CS (40)

86,134 2,068 4,716 2,648 >30 0.086 128,367

X - CSP PT (10) + PV

CdTe (40)

83,334 2,068 4,716 2,648 >30 0.083 128,367

XI - CSP ST (10) +

PV CS (40)

90,151 2,068 4,716 2,648 >30 0.089 128,367

XII - CSP ST (10) +

PV CdTe (40)

87,351 2,068 4,716 2,648 >30 0.086 128,367


6.5.4. Maximum Area Scenarios

This family of scenarios includes 8 scenarios that correspond to single-technology or hybrid solutions

covering the whole available area, and thus producing the maximum energy output possible for each

solution. Many interesting observations can be made:

Page 69 of 127


▪ The deployment of different technologies towards filling up the available area has a direct

impact on the overall energy output for each scenario. Thus, PV-only solutions19 yield a

significantly larger output (86MW for CS and 97MW for CdTe) compared to CSP solutions

(45MW for PT and 35MW for ST) given that they don’t require thermal storage which covers

a significant portion of the available area.

▪ This discrepancy in terms of how much area is required for the deployment of each technology

applies to hybrid scenarios too. Thus, the optimal hybrid configuration in terms of energy

output is 82MW composed by 12MW CSP PT and 70MW PV CdTe. Thanks to this larger output,

this is the hybrid scenario with the best break-even profile and LCOE (Figure 31 and Table 8).

▪ The initial investment of these full scenarios ranges from approx. USD 100 million for PV only

to approx. USD 120 million for hybrid solutions and up to USD 210 million for CSP PT.

74MW (12MW CSP PT and 62MW PV CS)

82MW (12MW CSP PT and 70MW PV CdTe)

19 At this point it is important to underline that even for solutions with storage presented in Table 8, we have assumed that the batteries cover a negligible area.

Page 70 of 127


68MW (12MW CSP ST and 56MW PV CS)

75MW (12MW CSP ST and 63MW PV CdTe)

Figure 31: Break-even analysis for the 4 hybrid solutions covering the whole area


Scenario Initial

Capital

Investment

Total

Annual

Cost

Total

Annual

Revenues

Total

Annual

Cash Flow

Break

Even

Point

LCOE Total

Output


I - 45MW - CSP PT 211,201 3,312 4,156 844 >30 0.241 113,702

II - 35MW - CSP ST 178,329 2,590 3,234 644 >30 0.256 89,586

III - 86MW - PV CS

(with storage)

96,280 41,022 8,240 -32,782 N/A 0.225 220,626

IV - 97MW - PV CdTe

(with storage)

100,270 41,397 9,261 -32,136 N/A 0.204 247,350

Page 71 of 127


V - 74MW - CS PT

(12) + PV CS (62)

117,080 2,986 7,073 4,087 28 0.079 190,069

VI - 82MW - CSP PT

(12) + PV CdTe (70)

120,020 3,264 7,858 4,594 26 0.074 210,617

VII - 68MW - CSP ST

(12) + PV CS (56)

116,021 2,777 6,484 3,707 >30 0.085 174,658

VIII - 75MW - CSP ST

(12) + PV CdTe (63)

118,471 3,021 7,171 4,150 28 0.079 192,637

Table 8: Summary table for Max. area solutions

6.5.5. Phased approach

As discussed in section 6.4, the economic model allows for the projection of scenarios that are

implemented through a phased approach. Thus, to complete the picture, it is instructive to look at the

gradual deployment of a 62MW scenario, consisting of 12MW CSP PT and 50MW PV CS. For the

purpose of this configuration, the first phase involves the deployment of the 12MW CSP PT and the

second, starting after 6 years, the deployment of the 50MW PV CS. Analysing the results allows for

the following observations:

▪ A strong insight on the main drivers of annual revenues is made possible. Thus, whilst in the

first phase (CSP-only) the primary driver is the avoided costs thanks to the 100% coverage of

energy requirements, the second phase revenues are led by the energy sold to the grid thanks

to the PV installation.

▪ Similarly, a good understanding of the main drivers regarding energy output can be achieved.

The CSP-produced energy covers the site’s requirements from the offset (marked with orange

colour), whilst the additional energy produced in phase 2 by the PV is made available to the

grid (yellow curve).

▪ These two observations combined highlight the investment possibilities in such a scenario,

but also further solidify the relevance of the hybrid approach. The initial driver being the

coverage of the site’s requirements, followed by subsequent investment in PVs in order to

boost the economic viability of the solar farm as reflected in the overall break-even profile

(Figure 32).

Revenue drivers

Page 72 of 127


Energy drivers

62MW (12MW CSP ST and 50MW PV CS)

Figure 32: Analysis of phased scenario

The “minimal” 7+3MW system (described in Section 5.1) has also been examined (and is present in

the economic model as a selectable option). Its performance, however, is extremely poor due to the

high costs of batteries and storage OPEX described in Section 6.2.2 above, and since it does not meet

the minimum 12MW required for unimpaired energy self-sufficiency, it has not been analysed further.

6.6. Understanding the results

The starting point in the development of scenarios was the objective to cover the energy requirements

of the New Aswan Heart Centre and its adjacent residential area. Meeting this objective can be

achieved either by CSP solutions with thermal storage or PV solutions with batteries. However, the

high cost of PV batteries and their very significant OPEX, renders them financially unfeasible. On the

other hand, PV without storage solutions are the cheapest and most compact (i.e. a larger overall solar

farm can be placed in the given site).

In this context, the most viable approach is to combine the best features of CSP and PV solutions

within a combined, hybrid configuration. In such hybrid scenarios, the CSP ensures a 24h 100% green

energy production, whereas the energy produced by PVs is sold to the grid.

Page 73 of 127


These observations are in line with other authors’ conclusions20 in recent publications. In fact, a large

number of scientific papers and articles can be found where the importance and economic

performance of hybrid solutions is underlined.

Before distilling these observations into concluding which scenario is the recommended one, it is

important to comment on the comparison between CSP parabolic trough and CSP solar tower

technologies. The main advantage of the former is that it allows expansion of the solar farm in a

straightforward way, whereas for solar towers this becomes much more complex. On the other hand,

the costs quoted in the literature for solar towers with 14h storage are more reliable than those for

parabolic trough with equivalent storage capacity.

6.6.1. Visual comparison

A series of “radar” diagrams is provided below to enable the visual comparison of the various options.

These diagrams visualise the performance of each scenario against the other scenarios in its group

against four key parameters, (i) the annual energy output, (ii) the initial investment required, (iii) the

annual cash flow, and (iv) the LCOE, which is correlated to the other three but also tightly connected

to the break-even perspectives. The ideal performance for each of these parameters is visualised by

lines extended all the way to the corners (i.e. for LCOE and initial investment, the poles have been

20 See for example Green et al., 2015; Hlusiak et al., 2014, and articles on http://helioscsp.com/concentrated-

solar-power-csp-cost-forecasts-undervalue-benefit-to-future-grid-balancing/ and

http://spie.org/newsroom/6018-photovoltaics-and-concentrating-solar-power-why-hybridization-makes-sense

The synergy between CSP and PV is lucrative on many levels

▪ Energy requirements coverage: The PV can provide electricity in the daytime (either to cover

hospital requirements or to sell to the grid) and when it declines, the CSP with storage enters

into operation and covers peak time requirements (a minima; it can of course cover as well

the complete day).

▪ Installation cost optimisation: The CSP solutions are significantly more expensive in terms of

CAPEX. By deploying just as much of a CSP portion as needed for the site’s energy

requirements and complementing this with cheaper PV solutions, the overall installation cost

is optimised.

▪ Energy output: CSP solutions are more performant in terms of energy output; however, due

to the area required for the deployment of the storage facilities, smaller CSP-only as compared

to PV-only plants can be deployed. Thus, the hybrid solution enables a pragmatic approach

whereby the available area in the designated site is optimally exploited.

▪ Annual revenues: Owing to the fact that large PV-only plants can be deployed in a given area,

the additional energy produced can be sold to the grid yielding larger annual revenues and

rendering the economic profile of the hybrid solutions more profitable.

▪ Overall profitability: Thanks to the increased annual revenues and the relatively reduced

installation cost, the hybrid scenarios have a better overall profitability, reflected in their

break-even profiles and their LCOE values.

http://helioscsp.com/concentrated-solar-power-csp-cost-forecasts-undervalue-benefit-to-future-grid-balancing/

http://helioscsp.com/concentrated-solar-power-csp-cost-forecasts-undervalue-benefit-to-future-grid-balancing/

http://spie.org/newsroom/6018-photovoltaics-and-concentrating-solar-power-why-hybridization-makes-sense

Page 74 of 127


switched, such that initial investment ranked 5 refers to the lowest value in the collection). In this way

the shapes with the largest area represent the most desirable options. It is worthwhile reiterating that

the results are relative to the other scenarios in the same family (i.e. 50MW or Max. Area).

For some of the scenarios, an additional “stamp” has been clearly inserted in order to underline either

excessive land use (i.e. for 50MW CSP scenarios) or failure to cover the New Aswan Heart Centre’s

energy requirements (i.e. for PV-only solutions without storage).

Figure 33: Radar Diagrams for 50MW solutions

Excessive Area

Not covering

Energy needs

Excessive Area

Page 75 of 127


Figure 34: Radar Diagrams for max. area solutions

Note: The comparison between radar diagrams can be done only within the same family of scenarios (i.e. either between

two 50MW options, or between two max. area options) but not across families.

6.6.2. LCOE discussion

The levelised cost of electricity (LCOE) is widely used as a way to compare power plants of different

generation and cost structures. Fraunhofer, 2016 includes a dedicated appendix presenting the

methodology on LCOE calculation. In practice, one forms the sum of all accumulated costs for installing

Not covering

Energy needs

Page 76 of 127


and operating a plant and, subsequently, comparing this figure to the sum of the annual power

generation. The formula giving the LCOE is provided below:

𝐿𝐶𝑂𝐸 =𝐼0 + ∑

𝐴𝑡(1 + 𝑖)𝑡

𝑛𝑡=1

∑𝑀𝑡,𝑒𝑙

(1 + 𝑖)𝑡𝑛𝑡=1

I0 denotes the investment expenditures in USD

At the annual total costs in USD in year t

Mt,el the produced quantity of electricity in the respective year provided in kWh

i denotes the real interest rate in % (in practice the Weighted Average Cost of Capital for Egypt is considered here)

n is the economic operational lifetime in years

t is the year of lifetime (1, 2, …, n)

Applying this formula to the various scenarios discussed in this chapter provides valuable insights for

the comparison of the different options. In that respect, analysing the relevant column in the summary

table of each of the previous subsections (6.5.1 – 6.5.4), it becomes clear that:

▪ There is a correlation between the break-even point and the LCOE value; the smaller the LCOE

the sooner the scenario breaks even.

▪ The hybrid scenarios, bridge the best of two worlds, by combining the reduction of initial

investment costs to the overall energy output and subsequently increasing the profitability of

the proposed solution.

These observations alongside the cash-flow projections, solidify the analysis made herein. It must be

also noted that the LCOE values of the single-technology scenarios developed in this work, are in very

good agreement (albeit projected in some cases) with the current literature (see for example Lazard,

2016).

6.7. Recommended scenario

The results for one of the scenarios (50MW) following this recommendation are presented below.

Considering all these observations and comments, the authors consider that the best option for

the off-site solar farm providing energy to the New Aswan Heart Centre is the deployment of a

hybrid solution composed of CSP ST and PV CdTe. The former would ensure coverage of the

hospital’s and residential area’s requirements whilst the latter would allow for maximal energy

output in the designated area and thus highest possible annual revenue. The exact choice of power

for each component of this scenario is dictated by two main parameters: (i) if the developers want

just enough energy for the site’s requirements (i.e. CSP 10MW) or slightly higher to anticipate

future needs and potential underperformance due to installation failures (i.e. 12MW); (ii) available

initial capital enabling either up to 50MW overall solutions or larger ones filling up the

corresponding space with PVs.

Page 77 of 127


50 MW.IIX - CSP ST (12) + PV CdTe (38)

Figure 35: Economic charts for the recommended scenario

Page 78 of 127


6.8. Exploitation strategies

In light of the discussion of the results for the different scenarios, and considering the recommended

solution, it is constructive to explore the range of exploitation strategies. In the context of this report,

this term refers to the exploitation of solar farm in close connection to its contribution to the

development of the New Aswan Heart Centre and its potential to contribute to the sustainable

development of the greater region. In that respect, it is instructive to study the three main dimensions

in this context, i.e. what can be exploited, how is this executed, and who is the beneficiary. These are

shown in the “exploitation cube” below.

Figure 36: Exploitation Options for the off-site solar farm (©Evenflow SPRL)

As seen in the figure above, the main exploitation modalities include

▪ Coverage of energy requirements: The baseline assumption in this plan is that investors and

developers will exploit solar energy to ensure 100% green coverage of the energy

requirements of the hospital and the adjacent residential area. For this, 10MW CSP plants

would suffice (but 12MW CSPs are instructed – see previous discussions). However, with the

main advantage of CSP being its relatively cheap thermal storage, it might become interesting

in the future to use the additional energy produced by larger CSPs to “replace” fossil fuel

consumption in the greater region. This would clearly benefit the local energy consumers, the

Egyptian government (in meeting its 2030 vision targets) and the local community as a whole.

▪ Selling to the grid: As discussed in several parts of this plan, selling additional energy to the

grid is one of the main revenue drivers, rendering the operation of the off-site solar farm

financially viable. This is particularly achieved through the deployment of PV solutions – ideally

in hybrid configurations (lower CAPEX and larger nominal power for a given area). In this vein:

o The gained revenues could be exploited to cover a part of the operational costs of the

Hospital, further solidifying the important contribution of the off-site solar farm.

o Another option would be to sell energy to private customers (instead of the EETC),

potentially achieving better selling prices and supporting the green operation not only

of the hospital but also of businesses in the region.

These exploitation strategies are fully in line with the results presented in the previous section. The

authors consider that once the profile of investors is known, these modalities can be studied in greater

depth.

Page 79 of 127


Ivanpah Solar Electric Generating System solar tower

(Credits: Businesswire.com)

Page 80 of 127


7. Implementation and governance The implementation of the off-site solar farm requires a number of steps, taking strongly into account

the development of the New Aswan Heart Centre itself. Thus, once the key decisions on the

exploitation strategies of the off-site solar farm are made in coordination with the eventual investors

and the desired solution is selected (see sections 6.6-6.8 above), the implementation schedule and

the roll-out strategy needs to be laid out. In the discussion below, a first attempt to highlight some

key actions has been made followed by a suggested governance structure. It is underlined, however,

that this description is by no means exhaustive; it simply serves as a first input towards the definition

of the implementation plan of the off-site solar farm.

7.1. Implementation and roll-out strategy

The first step going forward requires the collection of offers by companies able to develop and

operate the off-site solar farm. A combination of best value-for-money, relevant experience in the

specific conditions (environmental and bureaucratic) of Egypt, and trustworthy track-record should

guide the selection process. This is a critical step because it will provide accurate data on the CAPEX

and OPEX costs by different vendors, thus allowing for an additional level of precision in the economic

modelling. It is recommended that the assessment of the companies’ offers and the subsequent

development of the specific business plan (with the newly acquired “ground truth”) is supported by a

small team of independent experts and technical advisors. A concrete implementation roadmap

composed of a detailed description of the points made below and a well-defined timeline shall be

prepared. To that end, the applicability of a phased-approach shall be assessed taking into

consideration the various arguments presented herein and the investment strategy.

In parallel, the authors advise the engagement of the competent government authorities, towards

clarifying the specific vision (informed by the selected exploitation strategies) driving the development

of the off-site solar farm in the context of the New Aswan Heart Centre. Throughout the engagement

of the key governmental actors, two main aspects shall be emphasised, (i) the need to attract their

interest and support through a clear communication of the project’s expected impact and value

proposition, and (ii) the need to proceed with agreements on the exact costs (for selling to and buying

from the grid), taxes, etc. Furthermore, the following key actions21 shall be pursued in coordination

with relevant Egyptian government authorities:

21 This part is informed by EgyptERA, 2014 “Renewable energy – Feed-in tariff projects’ regulations.”

Page 81 of 127


▪ Evaluation (NREA and EETC)

o The project addresses the competent departments for an initial evaluation

▪ Land acquisition (Aswan Governorate)

o The project concludes a usufruct agreement with the Aswan Governorate (land is

returned upon decommission of the plant)

▪ Licenses (EgyptERA and EETC)

o Temporary generation license is obtained from EgyptERA

• Site measurements are conducted for a technical study

• Project funding committed (agreement on financial closure)

o Permanent generation license is obtained after previous steps are completed, and a

final signing of contracts including power purchasing agreement (EETC or third party)

With a concrete business plan and technical feasibility analysis for the specific scenario of the off-site

solar farm in place, the construction of the power plant shall commence, extending over a period of

about 18 months from the temporary generation license date. To that end, the procurement of

materials and construction contracts shall be undertaken. The commissioning and commercial

operation can be launched once the operational structure is established and the necessary staff hired

(or contracted).

7.2. Governance structure

The proposed governance structure of the Aswan Heart Centre solar farm is graphically displayed in

the figure below and described within this section.

Figure 37: The proposed governance structure of Aswan Heart Center’s solar farm.

The governance level is composed of an executive board for the solar farm (to be formed), the

executive board of the Aswan Heart Centre and Sir Magdi Yacoub. The two boards and Sir Magdi

Yacoub will make strategic decisions concerning the solar farm.

It is important that the solar farm has its own implementation layer with a focus on and expertise in

operating a solar power plant. Generation of electricity differs significantly from the core business

Page 82 of 127


of the New Aswan Heart Hospital, and thus requires a standalone focus in the governance structure.

The general manager and technical manager of the solar farm will directly report to the heads of the

two boards and Sir Magdi Yacoub concerning all issues required for them to fulfil their governance

roles: plant performance, major obstacles and occurrences, etc.

The general manager of the solar plant will oversee all internal aspects related to the functioning of

the solar farm as well as maintain relationships with key stakeholders external to the project: relevant

public agencies and potential third party buyers. The general manager will coordinate closely with the

technical manager of the solar farm, who will ensure that the plant is running at a high level of

performance and has contingency plans drafted in the case of technical failures. There will be several

groups of employees at the plant to ensure its proper functioning: control operators, monitoring and

maintenance personnel and security personnel.

The plant must also have a strong relationship with public agencies during project development and

during its operations. The NREA is instrumental in facilitating renewable energy projects and is a

source of ad hoc and technical support. Therefore, it is foreseen that interaction with this public

agency will be important during the project development stage.

The Aswan Governorate has expressed interest to provide public land under their ownership for the

solar farm. An agreement on use of this land for the lifetime of the solar plant will have to be concluded

with this public body.

If the solar farm wishes to sell a portion of the electricity it produces to external users, it must obtain

a license to generate electricity from EgyptERA. A temporary license valid for one year is needed for

the initial stages of project development, and will be replaced at the final stages of project

development by a permanent generation license. Both licenses should be issued to the hospital itself

as a legal entity and owner of the solar farm. If electricity production is solely for own use, the hospital

is exempt from obtaining this license.

If the solar farm sells to external users, it can do so by finding buyers and concluding power purchase

agreements with them. These agreements define the quantity of electricity to be delivered for a set

time period, and the tariffs that will apply. It should be noted that the buyer must be licensed – i.e.

qualified – by EgyptERA to conclude these agreements. In this scheme, the EETC will act as a service

provider where in it will charge a fee for transferring electricity from the plant to the buyer. EETC

cannot refuse to provide this service on the basis of its own bias.

In the case that the solar farm is unable to or not interested in finding a qualified user to commit to

purchasing all excess power to be generated, it has the option to conclude a power purchasing

agreement with EETC.

In both cases, EETC is tasked to provide the infrastructure to link the solar farm to the grid, assuming

the location is not considered extremely remote (established during an evaluation performed by the

EETC in the initial stages of project development).

Page 83 of 127


8. Risk assessment Failure to properly account for risks at the design and implementation phase may result in higher

costs and/or loss of electricity generation capacity due to underperformance or damage. Several

risks should be taken into account, as reviewed in this section.

8.1. Regulatory and market risks

There is a risk that tariffs used in the economic modelling within this document will be revised.

Retroactive revisions of FiT were already seen in 2014 in Italy and Spain (EY, 2014), with significant

negative effects on investors in renewable energy projects. However, once the power purchase

agreement is signed in the final stages of project realisation, this risk can be considered low.

8.2. Risks from theft

If solar farms are remote and left unguarded, they can be an attractive target for thieves. Damage can

extend from replacement costs (e.g. stolen tools and equipment) to lost production capacity (e.g. theft

of copper wiring or damage to infrastructure). Basic security measures – fencing, CCTV cameras and

night guards – will likely result in this risk being limited. It must be noted that OPEX costs considered

in the previous sections have taken security costs into account.

8.3. Risks from natural elements

Heat negatively affects PV panel efficiency. In general, high maximum temperatures can be expected

in the Sahara, and it is likely that mono- or poly-crystalline modules will not be the optimal panels of

choice due to their low optimum temperature. Thin film and CdTe modules, as well as high

concentration PV are more likely to perform better during the hottest months. CSP is also an attractive

option for desert climates. Similarly, high temperatures will also require the inverter room to be well

insulated and even cooled when needed, to avoid efficiency loses. It should also be noted that

continued global warming presents a likely risk of higher average and maximum temperatures

during the lifetime of the project, and must be factored in during the design phase.

The infrastructure of the solar plant should be able to withstand wind speeds of 120 km/h that occur

regularly during the Khamaseen. In the case of PV, appropriate mounting structures should be chosen

during the design phase. The inverter room should be insulated to avoid dust getting into the

machinery.

The facilities should include a good drainage system to avoid damage from rainwater, particularly as

there have been instances of flash floods occurring in Aswan. Although it is not likely to be a common

event, it has the potential to cause a large amount of damage. Rapid erosion of bare land can severely

impact the structural integrity of mounting structures. It is preferable to strengthen their foundations

to minimise risk.

Animals have also been known to damage solar farms. For example, rodents can damage wiring. An

inventory of local fauna would be useful to identify which animals can cause damage. A targeted pest

management strategy can minimise damage and avoid costly learning from experience.

8.4. Procurement risks

Experience of contractors with solar projects of this size can be considered a medium risk in Egypt.

It can be mitigated through contracting external experts and consultants in a supportive role, or by

Page 84 of 127


outsourcing construction aspects to a company specialised in turn key projects. The latter would be a

good option if the contractor can offer sufficient guarantees. Alternatively, contractors that

participated in recent solar projects can also be sought.

It must also be noted that construction work may suffer from delays. This can be mitigated by

diligence on the side of the project: vetting contractors through proactive research. In case all design

and construction is outsourced, the project should insist on concrete guarantees that delivery will be

timely.

8.5. Operations and maintenance risks

Once constructed, a solar farm can perform below its stated capacity due to equipment and

operational failures. It is important to have warranty on all components from the equipment

supplier and guarantees from the contractor. Performance tests during the construction phases are

generally good practice.

A professional and clear management structure should be put in place that allows for full

accountability according to industry best practice, which can be sought from consultants and experts.

Clear procedures, including restart procedures, are needed to address possible failures if they occur.

In the case the failure is related to the grid connection, a strong working relationship established with

EETC, and if possible formal commitments from them, would be instrumental to minimise down time.

There are a variety of maintenance tasks required for a solar plant. Typical activities include the

cleaning of panels and other infrastructure, maintenance of roads, etc. A proper plan must be drafted

that accounts for local conditions to ensure that the plant runs at maximum capacity. For example,

seasonal patterns in dust should be monitored to adjust cleaning frequency and maintain PV panels

or CSP mirrors clean. The importance of nowcasting and forecasting services in that respect cannot

be overstated.

Staff should be trained to take needed precautions for their own safety and to avoid damaging

equipment. Maintenance task management should be designed and preferably controlled by an

experienced operator.

8.6. Health and safety risks

Standard workplace diligence should be followed. This includes the availability of protective clothing

(steel toe boots, helmets, etc.) for relevant tasks. Isolation headphones or earplugs should be made

available for personnel that will perform tasks in the inverter room.

Page 85 of 127


Nev

ada

Sola

r O

ne

par

abo

lic t

rou

gh, B

ou

lder

Cit

y,

nea

r La

s V

egas

, Nev

ada

(USA

)

(Cre

dit

s: S

CH

OTT

AG

)

Page 86 of 127


9. Way Forward This report has presented a detailed and independent analysis of energy-related and economic

perspectives for the development of an off-site solar farm in the context of the New Aswan Heart

Centre. The findings and arguments presented herein are supported by the utilisation of a robust,

scalable and flexible economic modelling tool, developed specifically for the purpose of this work.

The authors have analysed numerous scenarios, making use of single-technology or hybrid solutions

(CSP and PV), respecting the local conditions (in terms of costs, energy potential and solar farm

schemes in Egypt) and serving the vision of the Magdi Yacoub Foundation for the development of the

New Aswan Heart Centre. Following a well-traceable reasoning – built on a set of assumptions and the

collection of up-to-date information – the authors have concluded that the best option for the

development of the off-site solar farm would be a hybrid configuration of 50MW or more, whereby

12MW CSP covers the site’s energy requirements and a larger PV plant (over 38MW) produces

energy sold to the grid. Solar tower technology is recommended for the CSP part, as it utilises robust

14h storage (for which the costs in the literature are better trusted than for parabolic trough with the

same storage). For the PV part, the authors recommended CdTe as it is relatively cheaper when

compared to CS, and in addition, it yields more energy for the same size of area.

Different exploitation strategies have been discussed in the report, considering the vision of the New

Aswan Heart Centre and the possibility that it will be deployed in more than one stages. Nonetheless,

the decision for the adoption of these strategies (including a phased approach) is driven by the specific

objectives of the eventual investors. This report, aspires to provide adequate “ammunition” to inform

and substantiate these strategies, towards the implementation of the off-site solar farm. A number of

key actions for the implementation and roll-out strategy of the solar farm have been identified. These

should be pursued on the way forward in close coordination with commercial vendors and the

competent Egyptian authorities.


10. References African Development Bank, 2012. Clean energy development in Egypt.

APICORP (Arab Petroleum Investment Corporation), 2016. Egypt’s power sector: on the right track?

APICORPO Energy Research Vol. 2 (No. 2). Available at: http://apicorp-

arabia.com/Research/EnergyReseach/2016/APICORPEnergyResearch_V02_N02_2016.pdf.

Bloomberg, 2017. Egypt to import LNG with an eye on self-sufficiency in 2018. Published 6/2/2017.

Eck, M., Hirsch, T., Feldhoff, J.F., Kretschmann, Dersch, J., Gavilan Morales, A., Gonzalez-Martinez, L.,

Bachelier, C., Platzer, W., Riffelmann, K.-J., Wagner, M., 2014. Guidelines for CSP yield analysis

– Optical losses of line focus systems; definitions, sensitivity, analysis and modelling

approaches. Energy Procedia 49: 1318-1327.

Egypt Oil&Gas Web Portal, 2013. Why is Egypt importing natural gas? February 2013 newspaper.

http://www.egyptoil-gas.com/publications/why-is-egypt-importing-natural-gas/

EgyptERA, 2014. Renewable energy – Feed-in tariff projects’ regulations.

Eissa, M.A., Tian, B., 2017. Lobatto-Milstein numerical method in application of uncertainty

investment of solar power projects. Energies 10 (43).

Electronic circuits, 2017. Thin film solar cell: Working, application, advantages, disadvantages.

Electronic Circuits and Diagram-Electronics Projects and Design.

Eversheds, Shahid Law Firm & PwC, 2015. Developing renewable energy projects: A guide to achieving

success in the Middle East.

EY, 2014. RECAI: Renewable energy country attractiveness index. Available at:

http://www.ey.com/Publication/vwLUAssets/Renewable_Energy_Country_Attractiveness_In

dex_42_-_September_2014/$FILE/EY-Renewable-Energy-Country-Attractiveness-Index-42-

September-2014.pdf.

Foster + Partners, 2017. Architectural report for the New Aswan Heart Centre.

Fraunhofer ISE, 2016. Electricity cost from renewable energy technologies in Egypt. Available at:

https://www.ise.fraunhofer.de/content/dam/ise/en/documents/publications/studies/Dec20

16_Fraunhofer-ISE_LCOE_Renewable_Energy_Technologies_EN_v20_ns.pdf.

Green, M.A., Emery, K., Hishikawa, Y., Warta, W., Dunlop, E.D., 2015. Solar cell efficiency tables

(version 46). Progress in Photovoltaics 23 (9) 1202: 805-812.

Hlusiak, M., Gotz, M., Bedoya Diaz, H.A., Breyer, C., 2014. Hybrid photovoltaic (PV) – concentrated

solar thermal power (CSP) power plants: Modelling, simulation and economics. Proceedings

from 29th European Photovoltaic Solar Energy Conference: 4034-4037.

Hoffschmidt, B., 2013. Overview of CSP technologies, markets, challenges. DLR Institute of Solar

Research, presentation at the Solar Qatar Summit, 2013.

IEA, 2012. World energy balances. IEA World Energy Statistics and Balances (database).

http://apicorp-arabia.com/Research/EnergyReseach/2016/APICORPEnergyResearch_V02_N02_2016.pdf

http://apicorp-arabia.com/Research/EnergyReseach/2016/APICORPEnergyResearch_V02_N02_2016.pdf

http://www.egyptoil-gas.com/publications/why-is-egypt-importing-natural-gas/

http://www.ey.com/Publication/vwLUAssets/Renewable_Energy_Country_Attractiveness_Index_42_-_September_2014/$FILE/EY-Renewable-Energy-Country-Attractiveness-Index-42-September-2014.pdf



https://www.ise.fraunhofer.de/content/dam/ise/en/documents/publications/studies/Dec2016_Fraunhofer-ISE_LCOE_Renewable_Energy_Technologies_EN_v20_ns.pdf

https://www.ise.fraunhofer.de/content/dam/ise/en/documents/publications/studies/Dec2016_Fraunhofer-ISE_LCOE_Renewable_Energy_Technologies_EN_v20_ns.pdf

Page 88 of 127


IEA, 2014. Technology roadmap: Solar photovoltaic energy. Available at:

https://www.iea.org/publications/freepublications/publication/TechnologyRoadmapSolarPh

otovoltaicEnergy_2014edition.pdf.

IEA-ETSAP & IRENA, 2013. Concentrating solar power. Technology Brief E10, January 2013.

IPCC, 2012. Renewable energy sources and climate change mitigation. Special Report of the IPCC.

Cambridge University Press: New York, USA.

IRENA, 2012a. Concentrated solar power. Renewable Energy Technologies: Cost Analysis Series,

Vol.1: Power Sector, Issue 2/5.

IRENA, 2012b. Solar photovoltaics. Renewable Energy Technologies: Cost Analysis Series, Vol.1:

Power Sector, Issue 4/5.

IRENA, 2014. Renewable power generation costs in 2014.

IRENA, 2015a. Battery storage for renewables: Market status and technology outlook. Available at:

http://www.irena.org/documentdownloads/publications/irena_battery_storage_report_201

5.pdf.

IRENA, 2015b. Renewable power generation costs in 2014.

IRENA, 2016a. Solar PV in Africa: Costs and markets.

IRENA, 2016b. The power to change: Solar and wind cost reduction potential to 2025.

Jäger-Waldau, A., 2016. PV status report 2016. JRC Science for Policy Report.

James, L.M., 2015. Recent developments in Egypt’s fuel subsidy reform process. The International

Institute for Sustainable Development.IEA, 2012a. CO2 emissions by product and flow. IEA

CO2 Emissions form Fuel Combustion Statistics (database).

Lazard, 2016. Levelized cost of energy analysis 10.0. Available at:

https://www.lazard.com/perspective/levelized-cost-of-energy-analysis-100/.

Middle East Solar Industry Association, 2016. Middle East solar outlook for 2016.

NREL, 2012. Residential, commercial, and utility-scale photovoltaic system prices in the United States:

Current drivers and cost-reduction opportunities.

NREL, 2016a. Advancing concentrated solar power technology, performance, and dispatchability.

NREL, 2016b. On the path to sunshot.

NREL, 2016c. US solar photovoltaic system cost benchmark: Q1-2016.

Ouali, H.A.L., Merrouni, A.A., Moussaoui, M.A., Mezrhab, A., 2015. Electricity yield analysis of a 50 MW

solar tower plant under Moroccan climate. Electrical and Information Technologies (ICEIT),

2015 International Conference.

Oxford Business Group, 2016. The report: Egypt 2016.

REN21, 2017a. Renewables 2017: Global status report. Available at: http://www.ren21.net/wp-

content/uploads/2017/06/17-8399_GSR_2017_Full_Report_0621_Opt.pdf.

https://www.iea.org/publications/freepublications/publication/TechnologyRoadmapSolarPhotovoltaicEnergy_2014edition.pdf

https://www.iea.org/publications/freepublications/publication/TechnologyRoadmapSolarPhotovoltaicEnergy_2014edition.pdf

http://www.irena.org/documentdownloads/publications/irena_battery_storage_report_2015.pdf

http://www.irena.org/documentdownloads/publications/irena_battery_storage_report_2015.pdf

https://www.lazard.com/perspective/levelized-cost-of-energy-analysis-100/

http://www.ren21.net/wp-content/uploads/2017/06/17-8399_GSR_2017_Full_Report_0621_Opt.pdf

http://www.ren21.net/wp-content/uploads/2017/06/17-8399_GSR_2017_Full_Report_0621_Opt.pdf

Page 89 of 127


REN21, 2017b. Renewables global futures report: Great debates towards 100% renewable energy.

Available at: http://www.ren21.net/wp-content/uploads/2017/03/GFR-Full-Report-

2017.pdf.

Sharkawy & Sarhan Law Firm, 2015. The new electricity law explained.

Smets, A., Jager, K., Isabella, O., van Swaaij, R., Zeman, M., 2016. Chapter 17: Introduction to PV

systems. 263-269. In: Solar Energy: The Physics and Engineering of Photovoltaic Conversion

Technologies and Systems. UIT Cambridge Ltd.: Cambridge England, 2016.

SolarABCs, 2013. PV system operations and maintenance fundamentals . Available at:

http://www.solarabcs.org/about/publications/reports/operations-

maintenance/pdfs/SolarABCs-35-2013.pdf.

UN, 2017. Progress towards the Sustainable Development Goals. Report of the Secretary-General.

Available at: http://www.un.org/ga/search/view_doc.asp?symbol=E/2017/66&Lang=E.

Vagliasindi, M., Besant-Jones, J., 2013. Chapter 6: Arab Republic of Egypt. In: Power market structure:

Revisiting policy options. The World Bank: Washington D.C. 161-174.

World Bank. CSP: Solar resource assessment. Training presentation available at:

http://www.esmap.org/sites/default/files/esmap-

files/ESMAP_IFC_RE_CSP_Training_World_Bank_Romero.pdf.

WorldBank Data. Sustainable Development Goals database. Accessed June 2017.

Xinhua, 2018. Egypt raises fuel prices as part of economic reform plan. Accessed July 2017. Available

at: http://news.xinhuanet.com/english/2017-06/29/c_136404216.htm.

http://www.ren21.net/wp-content/uploads/2017/03/GFR-Full-Report-2017.pdf

http://www.ren21.net/wp-content/uploads/2017/03/GFR-Full-Report-2017.pdf

http://www.solarabcs.org/about/publications/reports/operations-maintenance/pdfs/SolarABCs-35-2013.pdf

http://www.solarabcs.org/about/publications/reports/operations-maintenance/pdfs/SolarABCs-35-2013.pdf

http://www.un.org/ga/search/view_doc.asp?symbol=E/2017/66&Lang=E

http://www.esmap.org/sites/default/files/esmap-files/ESMAP_IFC_RE_CSP_Training_World_Bank_Romero.pdf

http://www.esmap.org/sites/default/files/esmap-files/ESMAP_IFC_RE_CSP_Training_World_Bank_Romero.pdf

http://news.xinhuanet.com/english/2017-06/29/c_136404216.htm


11. Annexes 11.1. Annex I: Energy calculations for the various scenarios

Table 9: 12 MW scenario

CSP 12MW - Energy output (MWh)

Months Monthly Daily Hourly Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan 2,318 74.78 3.12 5 0,00 0.00 0.00 0.00 2.41 2.32 1.78 1.27 0.00 0.00 0.00 0.00

Feb 2,319 82.83 3.45 6 0.00 3.25 3.08 3.55 4.50 4.90 4.33 3.60 3.12 2.22 1.99 0.00

Mar 2,739 88.35 3.68 7 4.36 5.52 6.05 6.12 6.53 7.00 6.49 6.10 5.70 5.01 4.57 4.06

Apr 2,571 85.71 3.57 8 6.88 7.58 7.90 7.48 7.64 8.21 7.75 7.53 7.40 7.30 7.04 6.78

May 2,798 90.27 3.76 9 8.14 8.64 8.93 8.26 8.30 8.95 8.52 8.38 8.37 8.60 8.32 8.14

Jun 2,928 97.59 4.07 10 8.81 9.21 9.50 8.71 8.67 9.37 8.96 8.86 8.91 9.33 9.01 8.86

Jul 2,836 91.47 3.81 11 9.10 9.46 9.76 8.91 8.84 9.57 9.16 9.08 9.16 9.65 9.31 9.18

Aug 2,698 87.03 3.63 12 9.10 9.46 9.76 8.91 8.84 9.57 9.16 9.08 9.16 9.65 9.31 9.18

Sep 2,506 83.55 3.48 13 8.81 9.21 9.50 8.71 8.67 9.37 8.96 8.86 8.91 9.33 9.01 8.86

Oct 2,519 81.27 3.39 14 8.14 8.64 8.93 8.26 8.30 8.95 8.52 8.38 8.37 8.60 8.32 8.14

Nov 2,305 76.82 3.20 15 6.88 7.58 7.90 7.48 7.64 8.21 7.75 7.53 7.40 7.30 7.04 6.78

Dec 2,285 73.70 3.07 16 4.36 5.52 6.05 6.12 6.53 7.00 6.49 6.10 5.70 5.01 4.57 4.06

Mean 2,569 84.45 3.52 17 1.75 2.62 2.31 3.55 4.50 4.90 4.33 3.60 2.61 1.48 1.00 0.00

Total 30,822 18 0.00 0.00 0.00 0.00 1.89 1.55 1.18 0.64 0.00 0.00 0.00 0.00

Page 91 of 127


PV 12MW - Energy output (MWh)


Jan 2,350 75.82 3.16 5 0.00 0.00 0.00 0.00 0.67 0.59 0.55 0.43 0.00 0.00 0.00 0.00

Feb 2,358 84.22 3.51 6 0.00 1.52 1.49 1.49 1.72 1.68 1.66 1.50 1.43 1.10 0.91 0.00

Mar 2,975 95.97 4.00 7 2.75 3.47 4.28 4.18 4.23 4.16 4.11 4.05 3.87 3.36 2.87 2.50

Apr 2,638 87.94 3.66 8 5.76 6.53 7.48 6.89 6.72 6.69 6.63 6.72 6.75 6.52 5.92 5.57

May 2,655 85.66 3.57 9 8.28 9.05 10.14 9.14 8.77 8.83 8.76 8.99 9.19 9.26 8.50 8.12

Jun 2,588 86.26 3.59 10 10.04 10.81 12.00 10.70 10.19 10.34 10.27 10.59 10.92 11.22 10.31 9.91

Jul 2,652 85.54 3.56 11 10.95 11.71 12.96 11.50 10.92 11.11 11.04 11.41 11.80 12.24 11.25 10.83

Aug 2,689 86.74 3.61 12 10.95 11.71 12.96 11.50 10.92 11.11 11.04 11.41 11.80 12.24 11.25 10.83

Sep 2,616 87.22 3.63 13 10.04 10.81 12.00 10.70 10.19 10.34 10.27 10.59 10.92 11.22 10.31 9.91

Oct 2,670 86.14 3.59 14 8.28 9.05 10.14 9.14 8.77 8.83 8.76 8.99 9.19 9.26 8.50 8.12

Nov 2,339 77.98 3.25 15 5.76 6.53 7.48 6.89 6.72 6.69 6.63 6.72 6.75 6.52 5.92 5.57

Dec 2,291 73.90 3.08 16 2.75 3.47 4.28 4.18 4.23 4.16 4.11 4.05 3.87 3.36 2.87 2.50

Mean 2,569 84.45 3.52 17 0.79 1.14 1.19 1.49 1.72 1.68 1.66 1.50 1.17 0.81 0.56 0.30

Total 30,822 18 0.00 0.00 0.00 0.37 0.55 0.48 0.42 0.31 0.00 0.00 0.00 0.00




Jan 3.864 124.65 5.19 5 0.00 0.00 0.00 0.00 4.02 3.87 2.96 2.12 0.00 0.00 0.00 0.00

Feb 3.866 138.05 5.75 6 0.00 5.42 5.14 5.92 7.50 8.16 7.21 6.00 5.20 3.70 3.32 0.00

Mar 4.565 147.26 6.14 7 7.27 9.20 10.08 10.20 10.88 11.66 10.81 10.17 9.51 8.35 7.61 6.77

Apr 4.286 142.86 5.95 8 11.46 12.63 13.17 12.46 12.74 13.69 12.92 12.54 12.33 12.17 11.74 11.30

May 4.664 150.46 6.27 9 13.57 14.41 14.89 13.78 13.83 14.92 14.20 13.96 13.95 14.34 13.87 13.58

Jun 4.880 162.66 6.78 10 14.69 15.35 15.83 14.52 14.46 15.62 14.94 14.77 14.85 15.55 15.01 14.77

Jul 4.726 152.46 6.35 11 15.18 15.77 16.26 14.86 14.74 15.95 15.28 15.13 15.26 16.09 15.52 15.30

Aug 4.497 145.06 6.04 12 15.18 15.77 16.26 14.86 14.74 15.95 15.28 15.13 15.26 16.09 15.52 15.30

Sep 4.178 139.25 5.80 13 14.69 15.35 15.83 14.52 14.46 15.62 14.94 14.77 14.85 15.55 15.01 14.77

Oct 4.199 135.45 5.64 14 13.57 14.41 14.89 13.78 13.83 14.92 14.20 13.96 13.95 14.34 13.87 13.58

Nov 3.842 128.05 5.34 15 11.46 12.63 13.17 12.46 12.74 13.69 12.92 12.54 12.33 12.17 11.74 11.30

Dec 3.808 122.85 5.12 16 7.27 9.20 10.08 10.20 10.88 11.66 10.81 10.17 9.51 8.35 7.61 6.77

Mean 4.281 140.76 5.86 17 2.92 4.36 3.85 5.92 7.50 8.16 7.21 6.00 4.35 2.47 1.66 0.00

Total 51.374 18 0.00 0.00 0.00 0.00 3.15 2.58 1.97 1.06 0.00 0.00 0.00 0.00

Page 92 of 127




Jan 3,918 126.37 5.27 5 0.00 0.00 0.00 0.00 1.12 0.98 0.91 0.72 0.00 0.00 0.00 0.00

Feb 3,930 140.37 5.85 6 0.00 2.54 2.48 2.49 2.87 2.80 2.76 2.49 2.39 1.83 1.52 0.00

Mar 4,959 159.97 6.67 7 4.58 5.79 7.13 6.96 7.05 6.93 6.84 6.75 6.44 5.60 4.79 4.17

Apr 4,397 146.57 6.11 8 9.60 10.88 12.47 11.48 11.21 11.16 11.05 11.21 11.26 10.87 9.87 9.28

May 4,426 142.77 5.95 9 13.80 15.08 16.90 15.23 14.62 14.72 14.60 14.99 15.32 15.44 14.17 13.54

Jun 4,313 143.77 5.99 10 16.74 18.03 20.00 17.84 16.99 17.24 17.12 17.66 18.20 18.70 17.19 16.52

Jul 4,420 142.57 5.94 11 18.25 19.53 21.60 19.17 18.20 18.53 18.41 19.02 19.67 20.40 18.75 18.06

Aug 4,482 144.57 6.02 12 18.25 19.53 21.60 19.17 18.20 18.53 18.41 19.02 19.67 20.40 18.75 18.06

Sep 4,361 145.37 6.06 13 16.74 18.03 20.00 17.84 16.99 17.24 17.12 17.66 18.20 18.70 17.19 16.52

Oct 4,451 143.57 5.98 14 13.80 15.08 16.90 15.23 14.62 14.72 14.60 14.99 15.32 15.44 14.17 13.54

Nov 3,899 129.97 5.42 15 9.60 10.88 12.47 11.48 11.21 11.16 11.05 11.21 11.26 10.87 9.87 9.28

Dec 3,818 123.18 5.13 16 4.58 5.79 7.13 6.96 7.05 6.93 6.84 6.75 6.44 5.60 4.79 4.17

Mean 4,281 140.75 5.86 17 1.32 1.90 1.98 2.49 2.87 2.80 2.76 2.49 1.95 1.35 0.94 0.50

Total 51,374 18 0.00 0.00 0.00 0.62 0.91 0.79 0.71 0.51 0.00 0.00 0.00 0.00

20 MW scenario



Jan 2,318 74.78 3.12 5 0.00 0.00 0.00 0.00 2.41 2.32 1.78 1.27 0.00 0.00 0.00 0.00

Feb 2,319 82.83 3.45 6 0.00 3.25 3.08 3.55 4.50 4.90 4.33 3.60 3.12 2.22 1.99 0.00

Mar 2,739 88.35 3.68 7 4.36 5.52 6.05 6.12 6.53 7.00 6.49 6.10 5.70 5.01 4.57 4.06

Apr 2,571 85.71 3.57 8 6.88 7.58 7.90 7.48 7.64 8.21 7.75 7.53 7.40 7.30 7.04 6.78

May 2,798 90.27 3.76 9 8.14 8.64 8.93 8.26 8.30 8.95 8.52 8.38 8.37 8.60 8.32 8.14

Jun 2,928 97.59 4.07 10 8.81 9.21 9.50 8.71 8.67 9.37 8.96 8.86 8.91 9.33 9.01 8.86

Jul 2,836 91.47 3.81 11 9.10 9.46 9.76 8.91 8.84 9.57 9.16 9.08 9.16 9.65 9.31 9.18

Aug 2,698 87.03 3.63 12 9.10 9.46 9.76 8.91 8.84 9.57 9.16 9.08 9.16 9.65 9.31 9.18

Sep 2,506 83.55 3.48 13 8.81 9.21 9.50 8.71 8.67 9.37 8.96 8.86 8.91 9.33 9.01 8.86

Oct 2,519 81.27 3.39 14 8.14 8.64 8.93 8.26 8.30 8.95 8.52 8.38 8.37 8.60 8.32 8.14

Nov 2,305 76.82 3.20 15 6.88 7.58 7.90 7.48 7.64 8.21 7.75 7.53 7.40 7.30 7.04 6.78

Dec 2,285 73.70 3.07 16 4.36 5.52 6.05 6.12 6.53 7.00 6.49 6.10 5.70 5.01 4.57 4.06

Mean 2,569 84.45 3.52 17 1.75 2.62 2.31 3.55 4.50 4.90 4.33 3.60 2.61 1.48 1.00 0.00

Total 30,822 18 0.00 0.00 0.00 0.00 1.89 1.55 1.18 0.64 0.00 0.00 0.00 0.00

Page 93 of 127




Jan 1,567 50.56 2.11 5 0.00 0.00 0.00 0.00 0.45 0.39 0.36 0.29 0.00 0.00 0.00 0.00

Feb 1,572 56.16 2.34 6 0.00 1.02 0.99 1.00 1.15 1.12 1.10 1.00 0.95 0.73 0.61 0.00

Mar 1,984 63.99 2.67 7 1.83 2.32 2.85 2.79 2.82 2.77 2.74 2.70 2.58 2.24 1.92 1.67

Apr 1,759 58.63 2.44 8 3.84 4.35 4.99 4.59 4.48 4.46 4.42 4.48 4.50 4.35 3.95 3.71

May 1,771 57.12 2.38 9 5.52 6.03 6.76 6.09 5.85 5.89 5.84 6.00 6.13 6.18 5.67 5.42

Jun 1,725 57.52 2.40 10 6.70 7.21 8.00 7.14 6.80 6.90 6.85 7.06 7.28 7.48 6.88 6.61

Jul 1,768 57.04 2.38 11 7.30 7.81 8.64 7.67 7.28 7.41 7.36 7.61 7.87 8.16 7.50 7.22

Aug 1,793 57.84 2.41 12 7.30 7.81 8.64 7.67 7.28 7.41 7.36 7.61 7.87 8.16 7.50 7.22

Sep 1,745 58.16 2.42 13 6.70 7.21 8.00 7.14 6.80 6.90 6.85 7.06 7.28 7.48 6.88 6.61

Oct 1,780 57.44 2.39 14 5.52 6.03 6.76 6.09 5.85 5.89 5.84 6.00 6.13 6.18 5.67 5.42

Nov 1,560 52.00 2.17 15 3.84 4.35 4.99 4.59 4.48 4.46 4.42 4.48 4.50 4.35 3.95 3.71

Dec 1,528 49.28 2.05 16 1.83 2.32 2.85 2.79 2.82 2.77 2.74 2.70 2.58 2.24 1.92 1.67

Mean 1,713 56.31 2.35 17 0.53 0.76 0.79 1.00 1.15 1.12 1.10 1.00 0.78 0.54 0.38 0.20

Total 20,552 18 0.00 0.00 0.00 0.25 0.36 0.32 0.28 0.20 0.00 0.00 0.00 0.00

CSP 12MW + PV 8MW - Energy output (MWh)


Jan 3,886 125.34 5.22 5 0.00 0.00 0.00 0.00 2.86 2.71 2.14 1.56 0.00 0.00 0.00 0.00

Feb 3,891 138.98 5.79 6 0.00 4.27 4.07 4.55 5.65 6.02 5.43 4.60 4.08 2.95 2.60 0.00

Mar 4,723 152.34 6.35 7 6.20 7.83 8.90 8.90 9.35 9.77 9.22 8.80 8.28 7.25 6.48 5.73

Apr 4,330 144.34 6.01 8 10.71 11.93 12.89 12.07 12.13 12.68 12.17 12.01 11.90 11.65 10.99 10.49

May 4,569 147.38 6.14 9 13.66 14.68 15.69 14.36 14.15 14.84 14.36 14.37 14.50 14.78 13.99 13.56

Jun 4,653 155.11 6.46 10 15.51 16.42 17.50 15.84 15.47 16.27 15.81 15.92 16.19 16.81 15.88 15.47

Jul 4,604 148.50 6.19 11 16.40 17.27 18.40 16.58 16.13 16.98 16.53 16.69 17.02 17.81 16.81 16.40

Aug 4,491 144.86 6.04 12 16.40 17.27 18.40 16.58 16.13 16.98 16.53 16.69 17.02 17.81 16.81 16.40

Sep 4,251 141.70 5.90 13 15.51 16.42 17.50 15.84 15.47 16.27 15.81 15.92 16.19 16.81 15.88 15.47

Oct 4,300 138.70 5.78 14 13.66 14.68 15.69 14.36 14.15 14.84 14.36 14.37 14.50 14.78 13.99 13.56

Nov 3,865 128.82 5.37 15 10.71 11.93 12.89 12.07 12.13 12.68 12.17 12.01 11.90 11.65 10.99 10.49

Dec 3,812 122.98 5.12 16 6.20 7.83 8.90 8.90 9.35 9.77 9.22 8.80 8.28 7.25 6.48 5.73

Mean 4,281 140.76 5.86 17 2.28 3.38 3.10 4.55 5.65 6.02 5.43 4.60 3.39 2.02 1.37 0.20

Total 51,374 18 0.00 0.00 0.00 0.25 2.25 1.87 1.47 0.84 0.00 0.00 0.00 0.00

Page 94 of 127


Table 11: Max area scenario

CSP PT 45MW - Energy output (MWh)


Jan 8,552 275.88 11.49 5 0.00 0.00 0.00 0.00 8.90 8.57 6.55 4.69 0.00 0.00 0.00 0.00

Feb 8,555 305.54 12.73 6 0.00 12.00 11.37 13.11 16.61 18.07 15.96 13.28 11.51 8.19 7.35 0.00

Mar 10,103 325.91 13.58 7 16.10 20.36 22.32 22.57 24.08 25.81 23.92 22.52 21.04 18.49 16.85 14.99

Apr 9,485 316.17 13.17 8 25.36 27.95 29.14 27.59 28.20 30.30 28.59 27.76 27.29 26.93 25.98 25.01

May 10,323 333.00 13.87 9 30.03 31.88 32.95 30.49 30.61 33.01 31.42 30.90 30.88 31.73 30.70 30.05

Jun 10,800 360.01 15.00 10 32.50 33.98 35.04 32.13 31.99 34.57 33.06 32.68 32.87 34.41 33.22 32.69

Jul 10,460 337.43 14.06 11 33.59 34.91 35.99 32.88 32.62 35.29 33.81 33.49 33.78 35.60 34.34 33.86

Aug 9,952 321.04 13.38 12 33.59 34.91 35.99 32.88 32.62 35.29 33.81 33.49 33.78 35.60 34.34 33.86

Sep 9,246 308.20 12.84 13 32.50 33.98 35.04 32.13 31.99 34.57 33.06 32.68 32.87 34.41 33.22 32.69

Oct 9,293 299.79 12.49 14 30.03 31.88 32.95 30.49 30.61 33.01 31.42 30.90 30.88 31.73 30.70 30.05

Nov 8,502 283.40 11.81 15 25.36 27.95 29.14 27.59 28.20 30.30 28.59 27.76 27.29 26.93 25.98 25.01

Dec 8,429 271.89 11.33 16 16.10 20.36 22.32 22.57 24.08 25.81 23.92 22.52 21.04 18.49 16.85 14.99

Mean 9,475 311.52 12.98 17 6.47 9.65 8.52 13.11 16.61 18.07 15.96 13.28 9.62 5.46 3.68 0.00

Total 113,702 18 0.00 0.00 0.00 0.00 6.97 5.71 4.37 2.35 0.00 0.00 0.00 0.00

CSP ST 35MW - Energy output (MWh)


Jan 6,738 217.36 9.06 5 0.00 0.00 0.00 0.00 7.01 6.75 5.16 3.70 0.00 0.00 0.00 0.00

Feb 6,741 240.74 10.03 6 0.00 9.46 8.96 10.33 13.08 14.24 12.58 10.47 9.07 6.45 5.79 0.00

Mar 7,960 256.79 10.70 7 12.68 16.04 17.58 17.79 18.97 20.33 18.85 17.74 16.58 14.57 13.28 11.81

Apr 7,473 249.11 10.38 8 19.98 22.02 22.96 21.74 22.22 23.87 22.53 21.88 21.50 21.22 20.47 19.70

May 8,133 262.37 10.93 9 23.66 25.12 25.96 24.02 24.12 26.01 24.75 24.34 24.33 25.00 24.19 23.67

Jun 8,510 283.65 11.82 10 25.61 26.77 27.61 25.31 25.21 27.24 26.05 25.75 25.90 27.11 26.18 25.76

Jul 8,242 265.86 11.08 11 26.46 27.50 28.36 25.91 25.71 27.81 26.64 26.39 26.61 28.05 27.06 26.68

Aug 7,841 252.95 10.54 12 26.46 27.50 28.36 25.91 25.71 27.81 26.64 26.39 26.61 28.05 27.06 26.68

Sep 7,285 242.83 10.12 13 25.61 26.77 27.61 25.31 25.21 27.24 26.05 25.75 25.90 27.11 26.18 25.76

Oct 7,322 236.20 9.84 14 23.66 25.12 25.96 24.02 24.12 26.01 24.75 24.34 24.33 25.00 24.19 23.67

Nov 6,699 223.29 9.30 15 19.98 22.02 22.96 21.74 22.22 23.87 22.53 21.88 21.50 21.22 20.47 19.70

Dec 6,641 214.22 8.93 16 12.68 16.04 17.58 17.79 18.97 20.33 18.85 17.74 16.58 14.57 13.28 11.81

Mean 7,466 245.45 10.23 17 5.09 7.61 6.72 10.33 13.08 14.24 12.58 10.47 7.58 4.30 2.90 0.00

Total 89,586 18 0.00 0.00 0.00 0.00 5.50 4.50 3.44 1.85 0.00 0.00 0.00 0.00

Page 95 of 127


CSP PT 135MW - Energy mirrors output (MWh)


Jan 25,656 827.63 34.48 5 0.00 0.00 0.00 0.00 26.70 25.71 19.66 14.08 0.00 0.00 0.00 0.00

Feb 25,666 916.63 38.19 6 0.00 36.00 34.10 39.32 49.82 54.20 47.89 39.85 34.54 24.58 22.05 0.00

Mar 30,310 977.74 40.74 7 48.29 61.08 66.95 67.72 72.23 77.42 71.77 67.55 63.13 55.46 50.55 44.97

Apr 28,456 948.52 39.52 8 76.09 83.86 87.41 82.76 84.59 90.90 85.78 83.29 81.87 80.80 77.95 75.02

May 30,969 999.00 41.62 9 90.10 95.65 98.84 91.46 91.83 99.04 94.25 92.69 92.63 95.18 92.10 90.14

Jun 32,401 1,080.03 45.00 10 97.51 101.93 105.11 96.38 95.98 103.72 99.17 98.04 98.60 103.22 99.67 98.07

Jul 31,381 1,012.28 42.18 11 100.76 104.72 107.97 98.64 97.87 105.88 101.43 100.46 101.33 106.81 103.02 101.59

Aug 29,857 963.13 40.13 12 100.76 104.72 107.97 98.64 97.87 105.88 101.43 100.46 101.33 106.81 103.02 101.59

Sep 27,738 924.60 38.53 13 97.51 101.93 105.11 96.38 95.98 103.72 99.17 98.04 98.60 103.22 99.67 98.07

Oct 27,880 899.36 37.47 14 90.10 95.65 98.84 91.46 91.83 99.04 94.25 92.69 92.63 95.18 92.10 90.14

Nov 25,506 850.21 35.43 15 76.09 83.86 87.41 82.76 84.59 90.90 85.78 83.29 81.87 80.80 77.95 75.02

Dec 25,286 815.67 33.99 16 48.29 61.08 66.95 67.72 72.23 77.42 71.77 67.55 63.13 55.46 50.55 44.97

Mean 28,426 934.57 38.94 17 19.40 28.96 25.57 39.32 49.82 54.20 47.89 39.85 28.86 16.38 11.03 0.00

Total 341,106 18 0.00 0.00 0.00 0.00 20.92 17.14 13.11 7.04 0.00 0.00 0.00 0.00

CSP ST 190MW - Energy mirrors output (MWh)


Jan 36,652 1,182.33 49.26 5 0.00 0.00 0.00 0.00 38.15 36.72 28.09 20.12 0.00 0.00 0.00 0.00

Feb 36,666 1,309.48 54.56 6 0.00 51.43 48.71 56.17 71.17 77.43 68.42 56.93 49.34 35.11 31.50 0.00

Mar 43,300 1,396.78 58.20 7 68.99 87.25 95.65 96.74 103.19 110.59 102.53 96.50 90.19 79.23 72.21 64.24

Apr 40,651 1,355.03 56.46 8 108.70 119.80 124.88 118.23 120.84 129.86 122.55 118.99 116.95 115.43 111.35 107.18

May 44,242 1,427.15 59.46 9 128.72 136.64 141.20 130.66 131.19 141.48 134.65 132.42 132.32 135.98 131.57 128.77

Jun 46,287 1,542.91 64.29 10 139.30 145.61 150.16 137.69 137.12 148.17 141.67 140.06 140.86 147.46 142.38 140.11

Jul 44,830 1,446.13 60.26 11 143.95 149.59 154.24 140.91 139.82 151.25 144.90 143.52 144.75 152.58 147.17 145.13

Aug 42,653 1,375.91 57.33 12 143.95 149.59 154.24 140.91 139.82 151.25 144.90 143.52 144.75 152.58 147.17 145.13

Sep 39,626 1,320.87 55.04 13 139.30 145.61 150.16 137.69 137.12 148.17 141.67 140.06 140.86 147.46 142.38 140.11

Oct 39,829 1,284.81 53.53 14 128.72 136.64 141.20 130.66 131.19 141.48 134.65 132.42 132.32 135.98 131.57 128.77

Nov 36,438 1,214.59 50.61 15 108.70 119.80 124.88 118.23 120.84 129.86 122.55 118.99 116.95 115.43 111.35 107.18

Dec 36,123 1,165.25 48.55 16 68.99 87.25 95.65 96.74 103.19 110.59 102.53 96.50 90.19 79.23 72.21 64.24

Mean 40,608 1,335.10 55.63 17 27.71 41.37 36.53 56.17 71.17 77.43 68.42 56.93 41.23 23.41 15.75 0.00

Total 487,297 18 0.00 0.00 0.00 0.00 29.89 24.48 18.72 10.06 0.00 0.00 0.00 0.00

Page 96 of 127


Max area scenario

PV CS 86MW - Energy output (MWh)


Jan 16,824 542.72 22.61 5 0.00 0.00 0.00 0.00 4.81 4.21 3.91 3.09 0.00 0.00 0.00 0.00

Feb 16,879 602.83 25.12 6 0.00 10.91 10.65 10.69 12.34 12.02 11.85 10.71 10.25 7.86 6.53 0.00

Mar 21,296 686.98 28.62 7 19.69 24.86 30.64 29.91 30.29 29.78 29.39 28.98 27.67 24.04 20.57 17.93

Apr 18,883 629.45 26.23 8 41.22 46.71 53.54 49.31 48.13 47.92 47.47 48.13 48.35 46.69 42.40 39.87

May 19,007 613.13 25.55 9 59.25 64.77 72.56 65.39 62.77 63.20 62.71 64.38 65.80 66.29 60.84 58.14

Jun 18,523 617.43 25.73 10 71.88 77.41 85.87 76.60 72.97 74.02 73.51 75.83 78.17 80.31 73.81 70.95

Jul 18,980 612.27 25.51 11 78.36 83.85 92.74 82.31 78.17 79.56 79.05 81.69 84.46 87.59 80.51 77.54

Aug 19,247 620.86 25.87 12 78.36 83.85 92.74 82.31 78.17 79.56 79.05 81.69 84.46 87.59 80.51 77.54

Sep 18,729 624.29 26.01 13 71.88 77.41 85.87 76.60 72.97 74.02 73.51 75.83 78.17 80.31 73.81 70.95

Oct 19,114 616.57 25.69 14 59.25 64.77 72.56 65.39 62.77 63.20 62.71 64.38 65.80 66.29 60.84 58.14

Nov 16,745 558.17 23.26 15 41.22 46.71 53.54 49.31 48.13 47.92 47.47 48.13 48.35 46.69 42.40 39.87

Dec 16,398 528.98 22.04 16 19.69 24.86 30.64 29.91 30.29 29.78 29.39 28.98 27.67 24.04 20.57 17.93

Mean 18,386 604.47 25.19 17 5.67 8.16 8.50 10.69 12.34 12.02 11.85 10.71 8.37 5.78 4.04 2.15

Total 220,626 18 0.00 0.00 0.00 2.66 3.91 3.41 3.03 2.19 0.00 0.00 0.00 0.00

PV CdTe 97MW - Energy output (MWh)


Jan 18,862 608.45 25.35 5 0.00 0.00 0.00 0.00 5.39 4.72 4.38 3.47 0.00 0.00 0.00 0.00

Feb 18,924 675.85 28.16 6 0.00 12.23 11.94 11.99 13.84 13.48 13.29 12.01 11.49 8.81 7.32 0.00

Mar 23,876 770.19 32.09 7 22.07 27.87 34.35 33.53 33.96 33.38 32.95 32.49 31.02 26.96 23.06 20.10

Apr 21,171 705.69 29.40 8 46.21 52.37 60.03 55.29 53.96 53.72 53.22 53.96 54.20 52.35 47.54 44.70

May 21,309 687.40 28.64 9 66.43 72.61 81.35 73.31 70.38 70.86 70.30 72.18 73.77 74.32 68.21 65.18

Jun 20,766 692.21 28.84 10 80.58 86.79 96.27 85.88 81.81 82.99 82.41 85.01 87.63 90.04 82.75 79.55

Jul 21,280 686.44 28.60 11 87.85 94.01 103.98 92.28 87.63 89.20 88.62 91.58 94.69 98.20 90.26 86.94

Aug 21,578 696.06 29.00 12 87.85 94.01 103.98 92.28 87.63 89.20 88.62 91.58 94.69 98.20 90.26 86.94

Sep 20,997 699.91 29.16 13 80.58 86.79 96.27 85.88 81.81 82.99 82.41 85.01 87.63 90.04 82.75 79.55

Oct 21,429 691.25 28.80 14 66.43 72.61 81.35 73.31 70.38 70.86 70.30 72.18 73.77 74.32 68.21 65.18

Nov 18,773 625.78 26.07 15 46.21 52.37 60.03 55.29 53.96 53.72 53.22 53.96 54.20 52.35 47.54 44.70

Dec 18,385 593.05 24.71 16 22.07 27.87 34.35 33.53 33.96 33.38 32.95 32.49 31.02 26.96 23.06 20.10

Mean 20,613 677.69 28.24 17 6.35 9.15 9.53 11.99 13.84 13.48 13.29 12.01 9.39 6.48 4.52 2.41

Total 247,350 18 0.00 0.00 0.00 2.98 4.38 3.82 3.40 2.45 0.00 0.00 0.00 0.00

Page 97 of 127


Max area scenario



Jan 12,144 391.73 16.32 5 0.00 0.00 0.00 0.00 3.47 3.04 2.82 2.23 0.00 0.00 0.00 0.00

Feb 12,183 435.12 18.13 6 0.00 7.87 7.69 7.72 8.91 8.68 8.55 7.73 7.40 5.67 4.71 0.00

Mar 15,372 495.86 20.66 7 14.21 17.94 22.11 21.59 21.86 21.49 21.21 20.92 19.97 17.36 14.84 12.94

Apr 13,630 454.33 18.93 8 29.75 33.72 38.65 35.59 34.74 34.59 34.26 34.74 34.90 33.70 30.60 28.78

May 13,719 442.56 18.44 9 42.77 46.75 52.38 47.20 45.31 45.62 45.26 46.47 47.49 47.85 43.91 41.96

Jun 13,370 445.66 18.57 10 51.88 55.88 61.98 55.29 52.67 53.43 53.06 54.73 56.42 57.97 53.27 51.21

Jul 13,700 441.94 18.41 11 56.56 60.53 66.94 59.41 56.42 57.43 57.06 58.96 60.96 63.22 58.11 55.97

Aug 13,892 448.13 18.67 12 56.56 60.53 66.94 59.41 56.42 57.43 57.06 58.96 60.96 63.22 58.11 55.97

Sep 13,518 450.61 18.78 13 51.88 55.88 61.98 55.29 52.67 53.43 53.06 54.73 56.42 57.97 53.27 51.21

Oct 13,796 445.04 18.54 14 42.77 46.75 52.38 47.20 45.31 45.62 45.26 46.47 47.49 47.85 43.91 41.96

Nov 12,087 402.89 16.79 15 29.75 33.72 38.65 35.59 34.74 34.59 34.26 34.74 34.90 33.70 30.60 28.78

Dec 11,836 381.81 15.91 16 14.21 17.94 22.11 21.59 21.86 21.49 21.21 20.92 19.97 17.36 14.84 12.94

Mean 13,271 436.31 18.18 17 4.09 5.89 6.14 7.72 8.91 8.68 8.55 7.73 6.04 4.17 2.91 1.55

Total 159,247 18 0.00 0.00 0.00 1.92 2.82 2.46 2.19 1.58 0.00 0.00 0.00 0.00



Jan 13,711 442.28 18.43 5 0.00 0.00 0.00 0.00 3.92 3.43 3.18 2.52 0.00 0.00 0.00 0.00

Feb 13,755 491.26 20.47 6 0.00 8.89 8.68 8.71 10.06 9.80 9.66 8.73 8.35 6.40 5.32 0.00

Mar 17,355 559.84 23.33 7 16.04 20.26 24.97 24.37 24.69 24.27 23.95 23.62 22.55 19.59 16.76 14.61

Apr 15,389 512.96 21.37 8 33.59 38.07 43.63 40.19 39.22 39.05 38.68 39.22 39.40 38.05 34.55 32.49

May 15,489 499.66 20.82 9 48.29 52.78 59.13 53.29 51.16 51.51 51.10 52.47 53.62 54.02 49.58 47.38

Jun 15,095 503.16 20.96 10 58.57 63.09 69.98 62.42 59.47 60.32 59.90 61.79 63.70 65.45 60.15 57.82

Jul 15,468 498.96 20.79 11 63.86 68.34 75.58 67.08 63.70 64.84 64.42 66.57 68.83 71.38 65.61 63.19

Aug 15,685 505.96 21.08 12 63.86 68.34 75.58 67.08 63.70 64.84 64.42 66.57 68.83 71.38 65.61 63.19

Sep 15,263 508.76 21.20 13 58.57 63.09 69.98 62.42 59.47 60.32 59.90 61.79 63.70 65.45 60.15 57.82

Oct 15,576 502.46 20.94 14 48.29 52.78 59.13 53.29 51.16 51.51 51.10 52.47 53.62 54.02 49.58 47.38

Nov 13,646 454.87 18.95 15 33.59 38.07 43.63 40.19 39.22 39.05 38.68 39.22 39.40 38.05 34.55 32.49

Dec 13,363 431.08 17.96 16 16.04 20.26 24.97 24.37 24.69 24.27 23.95 23.62 22.55 19.59 16.76 14.61

Mean 14,983 492.60 20.53 17 4.62 6.65 6.93 8.71 10.06 9.80 9.66 8.73 6.82 4.71 3.29 1.75

Total 179,795 18 0.00 0.00 0.00 2.17 3.18 2.78 2.47 1.78 0.00 0.00 0.00 0.00

Page 98 of 127


Max area scenario



Jan 10,968 353.82 14.74 5 0.00 0.00 0.00 0.00 3.14 2.74 2.55 2.02 0.00 0.00 0.00 0.00

Feb 11,004 393.01 16.38 6 0.00 7.11 6.94 6.97 8.05 7.84 7.73 6.98 6.68 5.12 4.25 0.00

Mar 13,884 447.87 18.66 7 12.83 16.21 19.97 19.50 19.75 19.41 19.16 18.89 18.04 15.68 13.41 11.69

Apr 12,311 410.36 17.10 8 26.87 30.46 34.91 32.15 31.38 31.24 30.95 31.38 31.52 30.44 27.64 25.99

May 12,392 399.73 16.66 9 38.63 42.23 47.31 42.63 40.92 41.20 40.88 41.97 42.90 43.22 39.66 37.90

Jun 12,076 402.53 16.77 10 46.86 50.47 55.98 49.94 47.57 48.26 47.92 49.43 50.96 52.36 48.12 46.26

Jul 12,374 399.17 16.63 11 51.09 54.67 60.46 53.66 50.96 51.87 51.53 53.26 55.06 57.10 52.49 50.55

Aug 12,548 404.77 16.87 12 51.09 54.67 60.46 53.66 50.96 51.87 51.53 53.26 55.06 57.10 52.49 50.55

Sep 12,210 407.01 16.96 13 46.86 50.47 55.98 49.94 47.57 48.26 47.92 49.43 50.96 52.36 48.12 46.26

Oct 12,461 401.97 16.75 14 38.63 42.23 47.31 42.63 40.92 41.20 40.88 41.97 42.90 43.22 39.66 37.90

Nov 10,917 363.90 15.16 15 26.87 30.46 34.91 32.15 31.38 31.24 30.95 31.38 31.52 30.44 27.64 25.99

Dec 10,691 344.86 14.37 16 12.83 16.21 19.97 19.50 19.75 19.41 19.16 18.89 18.04 15.68 13.41 11.69

Mean 11,986 394.08 16.42 17 3.69 5.32 5.54 6.97 8.05 7.84 7.73 6.98 5.46 3.77 2.63 1.40

Total 143,836 18 0.00 0.00 0.00 1.74 2.55 2.22 1.98 1.43 0.00 0.00 0.00 0.00



Jan 12,339 398.05 16.59 5 0.00 0.00 0.00 0.00 3.53 3.09 2.87 2.27 0.00 0.00 0.00 0.00

Feb 12,380 442.13 18.42 6 0.00 8.00 7.81 7.84 9.05 8.82 8.69 7.86 7.52 5.76 4.79 0.00

Mar 15,620 503.86 20.99 7 14.44 18.23 22.47 21.93 22.22 21.84 21.56 21.26 20.30 17.64 15.08 13.15

Apr 13,850 461.66 19.24 8 30.23 34.26 39.27 36.17 35.30 35.14 34.81 35.30 35.46 34.25 31.10 29.24

May 13,940 449.69 18.74 9 43.46 47.50 53.22 47.96 46.04 46.35 45.99 47.22 48.26 48.62 44.62 42.64

Jun 13,585 452.84 18.87 10 52.72 56.78 62.98 56.18 53.52 54.29 53.91 55.61 57.33 58.90 54.13 52.04

Jul 13,921 449.06 18.71 11 57.47 61.50 68.02 60.37 57.33 58.35 57.98 59.91 61.94 64.24 59.05 56.87

Aug 14,116 455.36 18.97 12 57.47 61.50 68.02 60.37 57.33 58.35 57.98 59.91 61.94 64.24 59.05 56.87

Sep 13,736 457.88 19.08 13 52.72 56.78 62.98 56.18 53.52 54.29 53.91 55.61 57.33 58.90 54.13 52.04

Oct 14,019 452.21 18.84 14 43.46 47.50 53.22 47.96 46.04 46.35 45.99 47.22 48.26 48.62 44.62 42.64

Nov 12,282 409.38 17.06 15 30.23 34.26 39.27 36.17 35.30 35.14 34.81 35.30 35.46 34.25 31.10 29.24

Dec 12,027 387.97 16.17 16 14.44 18.23 22.47 21.93 22.22 21.84 21.56 21.26 20.30 17.64 15.08 13.15

Mean 13,485 443.34 18.47 17 4.16 5.98 6.24 7.84 9.05 8.82 8.69 7.86 6.14 4.24 2.96 1.57

Total 161,815 18 0.00 0.00 0.00 1.95 2.87 2.50 2.23 1.61 0.00 0.00 0.00 0.00

Page 99 of 127


Max area scenario

CSP PT 12MW + PV CS 62MW - Energy output (MWh)


Jan 14,462 466.51 19.44 5 0.00 0.00 0.00 0.00 5.88 5.36 4.60 3.50 0.00 0.00 0.00 0.00

Feb 14,502 517.94 21.58 6 0.00 11.12 10.77 11.27 13.41 13.58 12.88 11.33 10.52 7.89 6.70 0.00

Mar 18,110 584.21 24.34 7 18.57 23.46 28.16 27.70 28.39 28.49 27.70 27.02 25.68 22.37 19.41 17.00

Apr 16,201 540.04 22.50 8 36.63 41.30 46.54 43.07 42.38 42.80 42.01 42.27 42.29 41.00 37.65 35.55

May 16,518 532.82 22.20 9 50.91 55.39 61.31 55.46 53.61 54.57 53.78 54.85 55.86 56.45 52.24 50.11

Jun 16,297 543.25 22.64 10 60.69 65.09 71.48 64.00 61.34 62.80 62.02 63.59 65.33 67.30 62.28 60.07

Jul 16,536 533.40 22.23 11 65.66 69.99 76.70 68.32 65.26 66.99 66.22 68.04 70.12 72.87 67.42 65.15

Aug 16,590 535.16 22.30 12 65.66 69.99 76.70 68.32 65.26 66.99 66.22 68.04 70.12 72.87 67.42 65.15

Sep 16,025 534.16 22.26 13 60.69 65.09 71.48 64.00 61.34 62.80 62.02 63.59 65.33 67.30 62.28 60.07

Oct 16,315 526.30 21.93 14 50.91 55.39 61.31 55.46 53.61 54.57 53.78 54.85 55.86 56.45 52.24 50.11

Nov 14,391 479.71 19.99 15 36.63 41.30 46.54 43.07 42.38 42.80 42.01 42.27 42.29 41.00 37.65 35.55

Dec 14,121 455.52 18.98 16 18.57 23.46 28.16 27.70 28.39 28.49 27.70 27.02 25.68 22.37 19.41 17.00

Mean 15,839 520.75 21.70 17 5.84 8.51 8.45 11.27 13.41 13.58 12.88 11.33 8.65 5.65 3.91 1.55

Total 190,069 18 0.00 0.00 0.00 1.92 4.71 4.01 3.37 2.22 0.00 0.00 0.00 0.00

CSP PT 12MW + PV CdTe 70MW - Energy output (MWh)


Jan 16,029 517.06 21.54 5 0.00 0.00 0.00 0.00 6.33 5.75 4.96 3.79 0.00 0.00 0.00 0.00

Feb 16,074 574.09 23.92 6 0.00 12.14 11.76 12.27 14.56 14.69 13.98 12.33 11.47 8.62 7.31 0.00

Mar 20,094 648.19 27.01 7 20.41 25.78 31.02 30.49 31.21 31.26 30.44 29.72 28.26 24.61 21.33 18.67

Apr 17,960 598.66 24.94 8 40.47 45.65 51.53 47.66 46.87 47.26 46.43 46.75 46.80 45.35 41.60 39.27

May 18,288 589.93 24.58 9 56.43 61.43 68.06 61.55 59.45 60.45 59.62 60.84 61.99 62.63 57.90 55.52

Jun 18,022 600.75 25.03 10 67.38 72.30 79.48 71.13 68.14 69.70 68.86 70.65 72.61 74.78 69.15 66.68

Jul 18,303 590.43 24.60 11 72.96 77.80 85.33 75.99 72.54 74.40 73.58 75.65 77.98 81.03 74.92 72.37

Aug 18,383 592.99 24.71 12 72.96 77.80 85.33 75.99 72.54 74.40 73.58 75.65 77.98 81.03 74.92 72.37

Sep 17,769 592.30 24.68 13 67.38 72.30 79.48 71.13 68.14 69.70 68.86 70.65 72.61 74.78 69.15 66.68

Oct 18,095 583.72 24.32 14 56.43 61.43 68.06 61.55 59.45 60.45 59.62 60.84 61.99 62.63 57.90 55.52

Nov 15,951 531.70 22.15 15 40.47 45.65 51.53 47.66 46.87 47.26 46.43 46.75 46.80 45.35 41.60 39.27

Dec 15,648 504.78 21.03 16 20.41 25.78 31.02 30.49 31.21 31.26 30.44 29.72 28.26 24.61 21.33 18.67

Mean 17,551 577.05 24.04 17 6.37 9.26 9.24 12.27 14.56 14.69 13.98 12.33 9.43 6.19 4.29 1.75

Total 210,617 18 0.00 0.00 0.00 2.17 5.07 4.32 3.66 2.42 0.00 0.00 0.00 0.00

Page 100 of 127


Max area scenario

CSP ST 12MW + PV CS 56MW - Energy output (MWh)


Jan 13,287 428.60 17.86 5 0.00 0.00 0.00 0.00 5.55 5.07 4.32 3.29 0.00 0.00 0.00 0.00

Feb 13,323 475.84 19.83 6 0.00 10.36 10.02 10.52 12.55 12.74 12.05 10.59 9.80 7.34 6.25 0.00

Mar 16,623 536.22 22.34 7 17.20 21.73 26.02 25.62 26.28 26.41 25.65 25.00 23.75 20.69 17.98 15.75

Apr 14,882 496.07 20.67 8 33.75 38.03 42.80 39.63 39.02 39.45 38.70 38.91 38.92 37.74 34.69 32.77

May 15,190 490.00 20.42 9 46.77 50.87 56.24 50.90 49.22 50.15 49.40 50.35 51.27 51.82 47.99 46.05

Jun 15,004 500.12 20.84 10 55.67 59.68 65.48 58.65 56.25 57.63 56.88 58.29 59.87 61.69 57.12 55.12

Jul 15,210 490.64 20.44 11 60.19 64.13 70.22 62.57 59.80 61.44 60.70 62.33 64.22 66.76 61.79 59.73

Aug 15,246 491.79 20.49 12 60.19 64.13 70.22 62.57 59.80 61.44 60.70 62.33 64.22 66.76 61.79 59.73

Sep 14,717 490.55 20.44 13 55.67 59.68 65.48 58.65 56.25 57.63 56.88 58.29 59.87 61.69 57.12 55.12

Oct 14,980 483.23 20.13 14 46.77 50.87 56.24 50.90 49.22 50.15 49.40 50.35 51.27 51.82 47.99 46.05

Nov 13,222 440.72 18.36 15 33.75 38.03 42.80 39.63 39.02 39.45 38.70 38.91 38.92 37.74 34.69 32.77

Dec 12,976 418.57 17.44 16 17.20 21.73 26.02 25.62 26.28 26.41 25.65 25.00 23.75 20.69 17.98 15.75

Mean 14,555 478.53 19.94 17 5.45 7.94 7.85 10.52 12.55 12.74 12.05 10.59 8.07 5.25 3.63 1.40

Total 174,658 18 0.00 0.00 0.00 1.74 4.44 3.77 3.16 2.06 0.00 0.00 0.00 0.00

CSP ST 12MW + PV CdTe 63MW - Energy output (MWh)


Jan 14,658 472.83 19.70 5 0.00 0.00 0.00 0.00 5.94 5.41 4.64 3.54 0.00 0.00 0.00 0.00

Feb 14,699 524.96 21.87 6 0.00 11.25 10.89 11.39 13.56 13.72 13.02 11.46 10.64 7.98 6.78 0.00

Mar 18,358 592.21 24.68 7 18.80 23.75 28.52 28.05 28.74 28.83 28.04 27.36 26.00 22.65 19.65 17.21

Apr 16,421 547.37 22.81 8 37.11 41.84 47.17 43.65 42.94 43.36 42.56 42.83 42.86 41.55 38.14 36.02

May 16,739 539.96 22.50 9 51.60 56.15 62.15 56.23 54.34 55.30 54.51 55.60 56.63 57.22 52.94 50.78

Jun 16,513 550.43 22.93 10 61.53 65.99 72.48 64.89 62.19 63.66 62.87 64.47 66.24 68.23 63.14 60.90

Jul 16,756 540.53 22.52 11 66.58 70.96 77.78 69.28 66.17 67.92 67.14 68.99 71.10 73.89 68.35 66.05

Aug 16,814 542.39 22.60 12 66.58 70.96 77.78 69.28 66.17 67.92 67.14 68.99 71.10 73.89 68.35 66.05

Sep 16,243 541.43 22.56 13 61.53 65.99 72.48 64.89 62.19 63.66 62.87 64.47 66.24 68.23 63.14 60.90

Oct 16,538 533.48 22.23 14 51.60 56.15 62.15 56.23 54.34 55.30 54.51 55.60 56.63 57.22 52.94 50.78

Nov 14,586 486.21 20.26 15 37.11 41.84 47.17 43.65 42.94 43.36 42.56 42.83 42.86 41.55 38.14 36.02

Dec 14,312 461.67 19.24 16 18.80 23.75 28.52 28.05 28.74 28.83 28.04 27.36 26.00 22.65 19.65 17.21

Mean 16,053 527.79 21.99 17 5.91 8.60 8.55 11.39 13.56 13.72 13.02 11.46 8.75 5.72 3.96 1.57

Total 192,637 18 0.00 0.00 0.00 1.95 4.76 4.05 3.41 2.24 0.00 0.00 0.00 0.00

Page 101 of 127





Jan 9,655 311.46 12.98 5 0.00 0.00 0.00 0.00 10.05 9.67 7.40 5.30 0.00 0.00 0.00 0.00

Feb 9,659 344.95 14.37 6 0.00 13.55 12.83 14.80 18.75 20.40 18.02 15.00 13.00 9.25 8.30 0.00

Mar 11,406 367.95 15.33 7 18.17 22.98 25.20 25.48 27.18 29.13 27.01 25.42 23.76 20.87 19.02 16.92

Apr 10,709 356.95 14.87 8 28.63 31.56 32.90 31.15 31.83 34.21 32.28 31.35 30.81 30.41 29.33 28.23

May 11,654 375.95 15.66 9 33.91 36.00 37.19 34.42 34.56 37.27 35.47 34.88 34.86 35.82 34.66 33.92

Jun 12,193 406.44 16.94 10 36.69 38.36 39.56 36.27 36.12 39.03 37.32 36.89 37.11 38.84 37.51 36.91

Jul 11,809 380.95 15.87 11 37.92 39.41 40.63 37.12 36.83 39.84 38.17 37.81 38.13 40.19 38.77 38.23

Aug 11,236 362.45 15.10 12 37.92 39.41 40.63 37.12 36.83 39.84 38.17 37.81 38.13 40.19 38.77 38.23

Sep 10,439 347.95 14.50 13 36.69 38.36 39.56 36.27 36.12 39.03 37.32 36.89 37.11 38.84 37.51 36.91

Oct 10,492 338.45 14.10 14 33.91 36.00 37.19 34.42 34.56 37.27 35.47 34.88 34.86 35.82 34.66 33.92

Nov 9,599 319.96 13.33 15 28.63 31.56 32.90 31.15 31.83 34.21 32.28 31.35 30.81 30.41 29.33 28.23

Dec 9,516 306.96 12.79 16 18.17 22.98 25.20 25.48 27.18 29.13 27.01 25.42 23.76 20.87 19.02 16.92

Mean 10,697 351.70 14.65 17 7.30 10.90 9.62 14.80 18.75 20.40 18.02 15.00 10.86 6.17 4.15 0.00

Total 128,367 18 0.00 0.00 0.00 0.00 7.87 6.45 4.93 2.65 0.00 0.00 0.00 0.00



Jan 9,789 315.77 13.16 5 0.00 0.00 0.00 0.00 2.80 2.45 2.27 1.80 0.00 0.00 0.00 0.00

Feb 9,821 350.74 14.61 6 0.00 6.35 6.20 6.22 7.18 6.99 6.89 6.23 5.96 4.57 3.80 0.00

Mar 12,391 399.71 16.65 7 11.45 14.46 17.82 17.40 17.62 17.32 17.10 16.86 16.10 13.99 11.97 10.43

Apr 10,987 366.23 15.26 8 23.98 27.18 31.15 28.69 28.00 27.88 27.62 28.00 28.13 27.17 24.67 23.20

May 11,059 356.74 14.86 9 34.47 37.68 42.22 38.05 36.52 36.77 36.49 37.46 38.28 38.57 35.40 33.83

Jun 10,777 359.24 14.97 10 41.82 45.04 49.96 44.57 42.46 43.07 42.77 44.12 45.48 46.73 42.94 41.28

Jul 11,043 356.24 14.84 11 45.59 48.79 53.96 47.89 45.48 46.29 45.99 47.53 49.14 50.96 46.84 45.12

Aug 11,198 361.24 15.05 12 45.59 48.79 53.96 47.89 45.48 46.29 45.99 47.53 49.14 50.96 46.84 45.12

Sep 10,897 363.23 15.13 13 41.82 45.04 49.96 44.57 42.46 43.07 42.77 44.12 45.48 46.73 42.94 41.28

Oct 11,121 358.74 14.95 14 34.47 37.68 42.22 38.05 36.52 36.77 36.49 37.46 38.28 38.57 35.40 33.83

Nov 9,743 324.76 13.53 15 23.98 27.18 31.15 28.69 28.00 27.88 27.62 28.00 28.13 27.17 24.67 23.20

Dec 9,541 307.77 12.82 16 11.45 14.46 17.82 17.40 17.62 17.32 17.10 16.86 16.10 13.99 11.97 10.43

Mean 10,697 351.70 14.65 17 3.30 4.75 4.95 6.22 7.18 6.99 6.89 6.23 4.87 3.36 2.35 1.25

Total 128,367 18 0.00 0.00 0.00 1.55 2.27 1.98 1.77 1.27 0.00 0.00 0.00 0.00

Page 102 of 127


50 MW scenario



Jan 7,438 239.95 10.00 5 0.00 0.00 0.00 0.00 2.13 1.86 1.73 1.37 0.00 0.00 0.00 0.00

Feb 7,463 266.53 11.11 6 0.00 4.82 4.71 4.73 5.46 5.32 5.24 4.74 4.53 3.47 2.89 0.00

Mar 9,416 303.73 12.66 7 8.70 10.99 13.54 13.22 13.39 13.16 12.99 12.81 12.23 10.63 9.09 7.93

Apr 8,349 278.30 11.60 8 18.22 20.65 23.67 21.80 21.28 21.19 20.99 21.28 21.38 20.64 18.75 17.63

May 8,404 271.08 11.30 9 26.20 28.64 32.08 28.91 27.75 27.94 27.73 28.47 29.09 29.31 26.90 25.70

Jun 8,189 272.98 11.37 10 31.78 34.23 37.97 33.87 32.26 32.73 32.50 33.52 34.56 35.51 32.63 31.37

Jul 8,392 270.70 11.28 11 34.64 37.07 41.00 36.39 34.56 35.18 34.95 36.12 37.34 38.73 35.59 34.28

Aug 8,509 274.50 11.44 12 34.64 37.07 41.00 36.39 34.56 35.18 34.95 36.12 37.34 38.73 35.59 34.28

Sep 8,281 276.02 11.50 13 31.78 34.23 37.97 33.87 32.26 32.73 32.50 33.52 34.56 35.51 32.63 31.37

Oct 8,451 272.60 11.36 14 26.20 28.64 32.08 28.91 27.75 27.94 27.73 28.47 29.09 29.31 26.90 25.70

Nov 7,404 246.78 10.28 15 18.22 20.65 23.67 21.80 21.28 21.19 20.99 21.28 21.38 20.64 18.75 17.63

Dec 7,250 233.88 9.74 16 8.70 10.99 13.54 13.22 13.39 13.16 12.99 12.81 12.23 10.63 9.09 7.93

Mean 8,129 267.25 11.14 17 2.51 3.61 3.76 4.73 5.46 5.32 5.24 4.74 3.70 2.56 1.78 0.95

Total 97,545 18 0.00 0.00 0.00 1.18 1.73 1.51 1.34 0.97 0.00 0.00 0.00 0.00



Jan 7,830 252.58 10.52 5 0.00 0.00 0.00 0.00 2.24 1.96 1.82 1.44 0.00 0.00 0.00 0.00

Feb 7,856 280.56 11.69 6 0.00 5.08 4.96 4.98 5.75 5.60 5.52 4.99 4.77 3.66 3.04 0.00

Mar 9,912 319.73 13.32 7 9.16 11.57 14.26 13.92 14.10 13.86 13.68 13.49 12.88 11.19 9.57 8.34

Apr 8,788 292.95 12.21 8 19.18 21.74 24.92 22.95 22.40 22.30 22.09 22.40 22.50 21.73 19.73 18.55

May 8,846 285.36 11.89 9 27.58 30.14 33.77 30.43 29.22 29.41 29.19 29.96 30.62 30.85 28.32 27.06

Jun 8,621 287.35 11.97 10 33.45 36.03 39.97 35.65 33.96 34.45 34.21 35.29 36.38 37.38 34.35 33.02

Jul 8,834 284.96 11.87 11 36.47 39.03 43.16 38.31 36.38 37.03 36.79 38.02 39.31 40.77 37.47 36.09

Aug 8,958 288.95 12.04 12 36.47 39.03 43.16 38.31 36.38 37.03 36.79 38.02 39.31 40.77 37.47 36.09

Sep 8,717 290.55 12.11 13 33.45 36.03 39.97 35.65 33.96 34.45 34.21 35.29 36.38 37.38 34.35 33.02

Oct 8,896 286.95 11.96 14 27.58 30.14 33.77 30.43 29.22 29.41 29.19 29.96 30.62 30.85 28.32 27.06

Nov 7,793 259.78 10.82 15 19.18 21.74 24.92 22.95 22.40 22.30 22.09 22.40 22.50 21.73 19.73 18.55

Dec 7,632 246.19 10.26 16 9.16 11.57 14.26 13.92 14.10 13.86 13.68 13.49 12.88 11.19 9.57 8.34

Mean 8,557 281.33 11.72 17 2.64 3.80 3.96 4.98 5.75 5.60 5.52 4.99 3.90 2.69 1.88 1.00

Total 102,681 18 0.00 0.00 0.00 1.24 1.82 1.59 1.41 1.02 0.00 0.00 0.00 0.00

Page 103 of 127


50 MW scenario



Jan 1,932 62.32 2.60 5 0.00 0.00 0.00 0.00 2.01 1.94 1.48 1.06 0.00 0.00 0.00 0.00

Feb 1,933 69.02 2.88 6 0.00 2.71 2.57 2.96 3.75 4.08 3.61 3.00 2.60 1.85 1.66 0.00

Mar 2,282 73.63 3.07 7 3.64 4.60 5.04 5.10 5.44 5.83 5.40 5.09 4.75 4.18 3.81 3.39

Apr 2,143 71.43 2.98 8 5.73 6.31 6.58 6.23 6.37 6.84 6.46 6.27 6.16 6.08 5.87 5.65

May 2,332 75.23 3.13 9 6.78 7.20 7.44 6.89 6.91 7.46 7.10 6.98 6.97 7.17 6.93 6.79

Jun 2,440 81.33 3.39 10 7.34 7.68 7.92 7.26 7.23 7.81 7.47 7.38 7.43 7.77 7.51 7.39

Jul 2,363 76.23 3.18 11 7.59 7.89 8.13 7.43 7.37 7.97 7.64 7.57 7.63 8.04 7.76 7.65

Aug 2,248 72.53 3.02 12 7.59 7.89 8.13 7.43 7.37 7.97 7.64 7.57 7.63 8.04 7.76 7.65

Sep 2,089 69.62 2.90 13 7.34 7.68 7.92 7.26 7.23 7.81 7.47 7.38 7.43 7.77 7.51 7.39

Oct 2,099 67.72 2.82 14 6.78 7.20 7.44 6.89 6.91 7.46 7.10 6.98 6.97 7.17 6.93 6.79

Nov 1,921 64.02 2.67 15 5.73 6.31 6.58 6.23 6.37 6.84 6.46 6.27 6.16 6.08 5.87 5.65

Dec 1,904 61.42 2.56 16 3.64 4.60 5.04 5.10 5.44 5.83 5.40 5.09 4.75 4.18 3.81 3.39

Mean 2,141 70.37 2.93 17 1.46 2.18 1.93 2.96 3.75 4.08 3.61 3.00 2.17 1.23 0.83 0.00

Total 25,686 18 0.00 0.00 0.00 0.00 1.58 1.29 0.99 0.53 0.00 0.00 0.00 0.00



Jan 9,757 314.73 13.11 5 0.00 0.00 0.00 0.00 4.54 4.18 3.50 2.64 0.00 0.00 0.00 0.00

Feb 9,782 349.35 14.56 6 0.00 8.07 7.79 8.28 9.96 10.21 9.57 8.34 7.65 5.69 4.88 0.00

Mar 12,155 392.08 16.34 7 13.07 16.51 19.59 19.34 19.92 20.16 19.48 18.92 17.94 15.64 13.66 11.99

Apr 10,920 364.00 15.17 8 25.10 28.23 31.57 29.28 28.92 29.40 28.74 28.81 28.77 27.95 25.79 24.41

May 11,202 361.35 15.06 9 34.34 37.28 41.01 37.18 36.05 36.89 36.24 36.84 37.46 37.91 35.22 33.85

Jun 11,117 370.57 15.44 10 40.59 43.44 47.46 42.58 40.94 42.10 41.46 42.38 43.47 44.84 41.64 40.23

Jul 11,227 362.17 15.09 11 43.75 46.54 50.76 45.30 43.40 44.74 44.11 45.19 46.50 48.38 44.90 43.46

Aug 11,207 361.53 15.06 12 43.75 46.54 50.76 45.30 43.40 44.74 44.11 45.19 46.50 48.38 44.90 43.46

Sep 10,787 359.56 14.98 13 40.59 43.44 47.46 42.58 40.94 42.10 41.46 42.38 43.47 44.84 41.64 40.23

Oct 10,970 353.87 14.74 14 34.34 37.28 41.01 37.18 36.05 36.89 36.24 36.84 37.46 37.91 35.22 33.85

Nov 9,708 323.61 13.48 15 25.10 28.23 31.57 29.28 28.92 29.40 28.74 28.81 28.77 27.95 25.79 24.41

Dec 9,535 307.58 12.82 16 13.07 16.51 19.59 19.34 19.92 20.16 19.48 18.92 17.94 15.64 13.66 11.99

Mean 10,697 351.70 14.65 17 4.26 6.22 6.07 8.28 9.96 10.21 9.57 8.34 6.31 4.04 2.78 0.95

Total 128,367 18 0.00 0.00 0.00 1.18 3.62 3.05 2.53 1.60 0.00 0.00 0.00 0.00

Page 104 of 127




Jan 9,762 314.91 13.12 5 0.00 0.00 0.00 0.00 4.25 3.89 3.30 2.50 0.00 0.00 0.00 0.00

Feb 9,788 349.58 14.57 6 0.00 7.79 7.52 7.94 9.50 9.68 9.12 7.99 7.37 5.51 4.70 0.00

Mar 12,194 393.35 16.39 7 12.80 16.17 19.30 19.02 19.54 19.69 19.08 18.58 17.63 15.37 13.38 11.73

Apr 10,931 364.37 15.18 8 24.91 28.06 31.50 29.18 28.77 29.15 28.55 28.67 28.67 27.82 25.60 24.20

May 11,178 360.58 15.02 9 34.36 37.35 41.21 37.32 36.13 36.87 36.28 36.94 37.60 38.02 35.25 33.84

Jun 11,060 368.68 15.36 10 40.79 43.70 47.88 42.91 41.19 42.26 41.68 42.67 43.80 45.15 41.86 40.41

Jul 11,197 361.18 15.05 11 44.06 46.91 51.29 45.73 43.75 45.00 44.43 45.58 46.94 48.81 45.23 43.74

Aug 11,206 361.48 15.06 12 44.06 46.91 51.29 45.73 43.75 45.00 44.43 45.58 46.94 48.81 45.23 43.74

Sep 10,805 360.18 15.01 13 40.79 43.70 47.88 42.91 41.19 42.26 41.68 42.67 43.80 45.15 41.86 40.41

Oct 10,995 354.68 14.78 14 34.36 37.35 41.21 37.32 36.13 36.87 36.28 36.94 37.60 38.02 35.25 33.84

Nov 9,714 323.80 13.49 15 24.91 28.06 31.50 29.18 28.77 29.15 28.55 28.67 28.67 27.82 25.60 24.20

Dec 9,536 307.61 12.82 16 12.80 16.17 19.30 19.02 19.54 19.69 19.08 18.58 17.63 15.37 13.38 11.73

Mean 10,697 351.70 14.65 17 4.10 5.98 5.88 7.94 9.50 9.68 9.12 7.99 6.07 3.92 2.71 1.00

Total 128,367 18 0.00 0.00 0.00 1.24 3.39 2.88 2.40 1.55 0.00 0.00 0.00 0.00

Table 13: Mirrors energy output

CSP PT - Energy output (kWh/m2)


Jan 20.36 0.657 0.027 5 0.000 0.000 0.000 0.000 0.021 0.020 0.016 0.011 0.000 0.000 0.000 0.000

Feb 20.37 0.728 0.030 6 0.000 0.029 0.027 0.031 0.040 0.043 0.038 0.032 0.027 0.020 0.018 0.000

Mar 24.06 0.776 0.032 7 0.038 0.048 0.053 0.054 0.057 0.061 0.057 0.054 0.050 0.044 0.040 0.036

Apr 22.58 0.753 0.031 8 0.060 0.067 0.069 0.066 0.067 0.072 0.068 0.066 0.065 0.064 0.062 0.060

May 24.58 0.793 0.033 9 0.072 0.076 0.078 0.073 0.073 0.079 0.075 0.074 0.074 0.076 0.073 0.072

Jun 25.72 0.857 0.036 10 0.077 0.081 0.083 0.076 0.076 0.082 0.079 0.078 0.078 0.082 0.079 0.078

Jul 24.91 0.803 0.033 11 0.080 0.083 0.086 0.078 0.078 0.084 0.081 0.080 0.080 0.085 0.082 0.081

Aug 23.70 0.764 0.032 12 0.080 0.083 0.086 0.078 0.078 0.084 0.081 0.080 0.080 0.085 0.082 0.081

Sep 22.02 0.734 0.031 13 0.077 0.081 0.083 0.076 0.076 0.082 0.079 0.078 0.078 0.082 0.079 0.078

Oct 22.13 0.714 0.030 14 0.072 0.076 0.078 0.073 0.073 0.079 0.075 0.074 0.074 0.076 0.073 0.072

Nov 20.24 0.675 0.028 15 0.060 0.067 0.069 0.066 0.067 0.072 0.068 0.066 0.065 0.064 0.062 0.060

Dec 20.07 0.647 0.027 16 0.038 0.048 0.053 0.054 0.057 0.061 0.057 0.054 0.050 0.044 0.040 0.036

Mean 22.56 0.742 0.031 17 0.015 0.023 0.020 0.031 0.040 0.043 0.038 0.032 0.023 0.013 0.009 0.000

Total 270.73 18 0.000 0.000 0.000 0.000 0.017 0.014 0.010 0.006 0.000 0.000 0.000 0.000

Page 105 of 127


CSP ST - Energy output (kWh/m2)


Jan 29.09 0.938 0.039 5 0.000 0.000 0.000 0.000 0.030 0.029 0.022 0.016 0.000 0.000 0.000 0.000

Feb 29.10 1.039 0.043 6 0.000 0.041 0.039 0.045 0.056 0.061 0.054 0.045 0.039 0.028 0.025 0.000

Mar 34.36 1.109 0.046 7 0.055 0.069 0.076 0.077 0.082 0.088 0.081 0.077 0.072 0.063 0.057 0.051

Apr 32.26 1.075 0.045 8 0.086 0.095 0.099 0.094 0.096 0.103 0.097 0.094 0.093 0.092 0.088 0.085

May 35.11 1.133 0.047 9 0.102 0.108 0.112 0.104 0.104 0.112 0.107 0.105 0.105 0.108 0.104 0.102

Jun 36.74 1.225 0.051 10 0.111 0.116 0.119 0.109 0.109 0.118 0.112 0.111 0.112 0.117 0.113 0.111

Jul 35.58 1.148 0.048 11 0.114 0.119 0.122 0.112 0.111 0.120 0.115 0.114 0.115 0.121 0.117 0.115

Aug 33.85 1.092 0.045 12 0.114 0.119 0.122 0.112 0.111 0.120 0.115 0.114 0.115 0.121 0.117 0.115

Sep 31.45 1.048 0.044 13 0.111 0.116 0.119 0.109 0.109 0.118 0.112 0.111 0.112 0.117 0.113 0.111

Oct 31.61 1.020 0.042 14 0.102 0.108 0.112 0.104 0.104 0.112 0.107 0.105 0.105 0.108 0.104 0.102

Nov 28.92 0.964 0.040 15 0.086 0.095 0.099 0.094 0.096 0.103 0.097 0.094 0.093 0.092 0.088 0.085

Dec 28.67 0.925 0.039 16 0.055 0.069 0.076 0.077 0.082 0.088 0.081 0.077 0.072 0.063 0.057 0.051

Mean 32.23 1.060 0.044 17 0.022 0.033 0.029 0.045 0.056 0.061 0.054 0.045 0.033 0.019 0.013 0.000

Total 386.74 18 0.000 0.000 0.000 0.000 0.024 0.019 0.015 0.008 0.000 0.000 0.000 0.000

PV CS - Energy output (kWh/m2)


Jan 13.35 0.431 0.018 5 0.000 0.000 0.000 0.000 0.004 0.003 0.003 0.002 0.000 0.000 0.000 0.000

Feb 13.40 0.478 0.020 6 0.000 0.009 0.008 0.008 0.010 0.010 0.009 0.009 0.008 0.006 0.005 0.000

Mar 16.90 0.545 0.023 7 0.016 0.020 0.024 0.024 0.024 0.024 0.023 0.023 0.022 0.019 0.016 0.014

Apr 14.99 0.500 0.021 8 0.033 0.037 0.042 0.039 0.038 0.038 0.038 0.038 0.038 0.037 0.034 0.032

May 15.08 0.487 0.020 9 0.047 0.051 0.058 0.052 0.050 0.050 0.050 0.051 0.052 0.053 0.048 0.046

Jun 14.70 0.490 0.020 10 0.057 0.061 0.068 0.061 0.058 0.059 0.058 0.060 0.062 0.064 0.059 0.056

Jul 15.06 0.486 0.020 11 0.062 0.067 0.074 0.065 0.062 0.063 0.063 0.065 0.067 0.070 0.064 0.062

Aug 15.28 0.493 0.021 12 0.062 0.067 0.074 0.065 0.062 0.063 0.063 0.065 0.067 0.070 0.064 0.062

Sep 14.86 0.495 0.021 13 0.057 0.061 0.068 0.061 0.058 0.059 0.058 0.060 0.062 0.064 0.059 0.056

Oct 15.17 0.489 0.020 14 0.047 0.051 0.058 0.052 0.050 0.050 0.050 0.051 0.052 0.053 0.048 0.046

Nov 13.29 0.443 0.018 15 0.033 0.037 0.042 0.039 0.038 0.038 0.038 0.038 0.038 0.037 0.034 0.032

Dec 13.01 0.420 0.017 16 0.016 0.020 0.024 0.024 0.024 0.024 0.023 0.023 0.022 0.019 0.016 0.014

Mean 14.59 0.480 0.020 17 0.004 0.006 0.007 0.008 0.010 0.010 0.009 0.009 0.007 0.005 0.003 0.002

Total 175.10 18 0.000 0.000 0.000 0.002 0.003 0.003 0.002 0.002 0.000 0.000 0.000 0.000

Page 106 of 127


PV CdTe - Energy output (kWh/m2)


Jan 14.97 0.483 0.020 5 0.000 0.000 0.000 0.000 0.004 0.004 0.003 0.003 0.000 0.000 0.000 0.000

Feb 15.02 0.536 0.022 6 0.000 0.010 0.009 0.010 0.011 0.011 0.011 0.010 0.009 0.007 0.006 0.000

Mar 18.95 0.611 0.025 7 0.018 0.022 0.027 0.027 0.027 0.026 0.026 0.026 0.025 0.021 0.018 0.016

Apr 16.80 0.560 0.023 8 0.037 0.042 0.048 0.044 0.043 0.043 0.042 0.043 0.043 0.042 0.038 0.035

May 16.91 0.546 0.023 9 0.053 0.058 0.065 0.058 0.056 0.056 0.056 0.057 0.059 0.059 0.054 0.052

Jun 16.48 0.549 0.023 10 0.064 0.069 0.076 0.068 0.065 0.066 0.065 0.067 0.070 0.071 0.066 0.063

Jul 16.89 0.545 0.023 11 0.070 0.075 0.083 0.073 0.070 0.071 0.070 0.073 0.075 0.078 0.072 0.069

Aug 17.13 0.552 0.023 12 0.070 0.075 0.083 0.073 0.070 0.071 0.070 0.073 0.075 0.078 0.072 0.069

Sep 16.66 0.555 0.023 13 0.064 0.069 0.076 0.068 0.065 0.066 0.065 0.067 0.070 0.071 0.066 0.063

Oct 17.01 0.549 0.023 14 0.053 0.058 0.065 0.058 0.056 0.056 0.056 0.057 0.059 0.059 0.054 0.052

Nov 14.90 0.497 0.021 15 0.037 0.042 0.048 0.044 0.043 0.043 0.042 0.043 0.043 0.042 0.038 0.035

Dec 14.59 0.471 0.020 16 0.018 0.022 0.027 0.027 0.027 0.026 0.026 0.026 0.025 0.021 0.018 0.016

Mean 16.36 0.538 0.022 17 0.005 0.007 0.008 0.010 0.011 0.011 0.011 0.010 0.007 0.005 0.004 0.002

Total 196.31 18 0.000 0.000 0.000 0.002 0.003 0.003 0.003 0.002 0.000 0.000 0.000 0.000


11.2. Annex II: Full series of graphs for individual scenarios

Scenario 12MW.I – CSP PT

Figure 38: Overnight capital costs, break-even analysis, lifetime revenues and annual cash flow graphs for scenario

12MW.I, CSP PT

Scenario 12MW.II – CSP ST


12MW.II, CSP ST

Page 108 of 127


Scenario 12MW.III – PV CS


12MW.III, PV CS

Scenario 12MW.IV – PV CdTe


12MW.IV, PV CdTe

Page 109 of 127


Scenario 20MW.I – CSP PT


20MW.I, CSP PT



20MW.II, CSP ST

Page 110 of 127




20MW.III, PV CS



20MW.IV, PV CdTe

Page 111 of 127


Scenario 20MW.V – CSP PT (12 MW) & PV CS (8 MW)


20MW.V, CSP PT (12 MW) & PV CS (8 MW)

Scenario 20MW.VI – CSP PT (12 MW) & PV CdTe (8 MW)


20MW.VI, CSP PT (12 MW) & PV CdTe (8 MW)

Page 112 of 127


Scenario 20MW.VII – CSP ST (12 MW) & PV CS (8 MW)


20MW.VII, CSP ST (12 MW) & PV CS (8 MW)

Scenario 20MW.VIII – CSP ST (12 MW) & PV CdTe (8 MW)


20MW.VIII, CSP ST (12 MW) & PV CdTe (8 MW)

Page 113 of 127


Scenario 50MW.I – CSP PT (50 MW)


50MW.I, CSP PT



50MW.II, CSP ST

Page 114 of 127




50MW.III, PV CS



50MW.IV, PV CdTe

Page 115 of 127


Scenario 50MW.V – CSP PT (12 MW) & PV CS (38 MW)


50MW.V, CSP PT (12 MW) & PV CS (38 MW)

Scenario 50MW.VI – CSP PT (12 MW) & PV CdTe (38 MW)


50MW.VI, CSP PT (12 MW) & PV CdTe (38 MW)

Page 116 of 127


Scenario 50MW.VII – CSP ST (12 MW) & PV CS (38 MW)


50MW.VII, CSP ST (12 MW) & PV CS (38 MW)

Scenario 50MW.VIII – CSP ST (12 MW) & PV CdTe (38 MW)


50MW.VIII, CSP ST (12 MW) & PV CdTe (38 MW)

Page 117 of 127


Scenario 50MW.IX – CSP PT (10 MW) & PV CS (40 MW)


50MW.IX, CSP PT (10 MW) & PV CS (40 MW)

Scenario 50MW.X – CSP PT (10 MW) & PV CdTe (40 MW)


50MW.X, CSP PT (10 MW) & PV CdTe (40 MW)

Page 118 of 127


Scenario 50MW.XI – CSP ST (10 MW) & PV CS (40 MW)


50MW.XI, CSP ST (10 MW) & PV CS (40 MW)

Scenario 50MW.XII – CSP ST (10 MW) & PV CdTe (40 MW)


50MW.XII, CSP ST (10 MW) & PV CdTe (40 MW)

Page 119 of 127


Scenario Max Area.I – CSP PT (45 MW)

Figure 62: Overnight capital costs, break-even analysis, lifetime revenues and annual cash flow graphs for scenario Max

Area.I, CSP PT (45 MW)

Scenario Max Area.II – CSP ST (35 MW)


Area.II, CSP ST (35 MW)

Page 120 of 127


Scenario Max Area.III – PV CS (86 MW)


Area.III, PV CS (86 MW)

Scenario Max Area.IV – PV CdTe (97 MW)


Area.IV, PV CdTe (97 MW)

Page 121 of 127


Scenario Max Area.V – CSP PT (12 MW) & PV CS (62 MW)


Area.V, CSP PT (12 MW) & PV CS (62 MW)

Scenario Max Area.VI – CSP PT (12 MW) & PV CdTe (70 MW)


Area.VI, CSP PT (12 MW) & PV CdTe (70 MW)

Page 122 of 127


Scenario Max Area.VII – CSP ST (12 MW) & PV CS (56 MW)


Area.VII, CSP ST (12 MW) & PV CS (56 MW)

Scenario Max Area.VIII – CSP ST (12 MW) & PV CdTe (63 MW)


Area.VIII, CSP ST (12 MW) & PV CdTe (63 MW)

Page 123 of 127


Scenario PV with Storage.I – PV CS (12 MW) with storage

Figure 70: Overnight capital costs, break-even analysis, lifetime revenues and annual cash flow graphs for scenario PVC

with Storage I, PV CS (12 MW) with storage

Scenario PV with Storage.II – PV CdTe (12 MW) with storage


with Storage II, PV CdTe (12 MW) with storage

Page 124 of 127


Scenario PV with Storage.III – PV CS (20 MW) with storage


with Storage III, PV CS (20 MW) with storage

Scenario PV with Storage.IV – PV CdTe (20 MW) with storage


with Storage IV, PV CdTe (20 MW) with storage

Page 125 of 127


Scenario 2Phase – CSP PT (12 MW) in the first year + PV CS (50 MW) in the sixth year


2Phase, CSP PT (12 MW) in the first year + PV CS (50 MW) in the sixth year


11.3. Annex III: Comparative overview of solar technologies

PVs

CSPs Most common solar panel materials Different mounting structure types

Technology

Crystalline silicon (sc-Si)

Copper Indium Gallium Selenide

Cadmium Telluride solar cells

(CdTe)

Fixed tilt horizontal/

inclined

2-axis tracker

Concentr. PV (CPVs)

Parabolic through (PT)

Solar power tower (ST)

Compact linear

Fresnel reflector

Stirling dish

Market Maturity Mature

Large scale prod.

Early deployment

phase, medium

scale prod.

Early deployment

phase; small scale

prod.

Mature Mature

Under dev. First

commercial phase

Mature Mature Early

(pilot phase)

Early (demos on projects)

Annual Capacity factor (MW)

15-25% 15-25% 15-25% 15-25% 15-25% 140% *** 25-28 (no TES**)

29-43 (7h TES) 55 (10h TES) 22-24 25-28

Annual solar to electricity efficiency (net) %

>21 +12-14%

more than sc-Si

~19 12 12 33 11-16 7-20 13 12-25

Plant peak efficiency (%)

23 12 11 23 23 43 14-20 23-35 18 30

Average system lifetime (years)

20-40 20-40 20-40 20-40 20-40 20-40 20-40 20-40 20-40 20-40

Application type On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

On grid/ Off grid

Operating Temp. (°Celcius)

N/A N/A N/A N/A N/A 400-440 350-550 250-656 390 550-750

Water req. (m^3/ MWh)

insignificant insignificant insignificant insignificant insignificant Very low 3 (wet cooling) + 0,3 (dry cooling)

2-3 (wet cooling) + 0,25 (dry cooling)

3 (wet cooling) + 0,2 dry cooling)

0,05-0,1 (mirror washing)

Storage capacity without battery

NO NO NO NO NO NO 6-13h 6-15h N/A N/A

Technology dev. risk

LOW MEDIUM MEDIUM LOW LOW MEDIUM LOW MEDIUM MEDIUM MEDIUM

Table 14: Comparative overview of solar technologies


Documents

Business Plan for the establishment, operation and ...solea.gr/wp-content/uploads/2018/03/Aswan-Solar-Plant-Business-Plan.pdf · New Aswan Heart Centre - Solar Farm Business Plan