By: Ramy Essam - Uni Kassel€¦ · By: Ramy Essam ramy_essam@hotmail.com June 18, 2014 Ramy...

By: Ramy Essam ramy_essam@hotmail.com

Ramy Essam-APV June 18, 2014 1

Under Supervision of:

Prof. Dr. Mohammed Fawzy Elrefaie

Prof. Dr. Dirk Dahlhaus

1. Introduction & Objective

2. Methodology & Procedure

3. Modeling

4. Simulation & Results

5. Conclusion

6. Future Recommendations

7. Summary

8. Questions & Answers

Ramy Essam-APV June 18, 2014 2

Outline

Source: www.ise.fraunhofer.de

Definition:

Agro-photovoltaic (APV) is the concept of combining power generated from PV and to enhance Agriculture productivity simultaneously

Aim of work:

The PV integration on farm land concept is used to increase land productivity and economic profitability with minimal negative interactions and positive optimal interactions

Objective of the study:

Evaluation of technical and economical feasibility under Egyptian climate conditions

1. Introduction & Objective

Ramy Essam-APV June 18, 2014 3

Identify the Problem & Search for

Solutions

1. Define Technical Model Variables

2. Classification of Plants

Run the Simulation

Interpretation of results & Conclusion

2. Methodology & Procedure

Ramy Essam-APV June 18, 2014 4

• History of APV applications

• Literature review

• Lessons learned: Fraunhofer ISE/In-house research

• Literature experimental shading studies

• Radiance Software

Sources: 1- Fraunhofer ISE; 2- M. Guggenmos; 3- www.revolutionenergymaker.com; 4- University of Montpellier

Prof. A. Goetzberger (early 80s) published preliminary results of research. Putting it into practice:

Bavaria (since 2010):

Manfred Guggenmos: practical experiments for vegetables under PV.

Northern Italy (2011): three APV-prototypes have been installed, but no scientific support to date.

South of France (2009): University of Montpellier installed APV testing facility.

2.1. History of APV

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2. Methodology & Procedure

Source: www.ise.fraunhofer.de

Plant growth conditions are a subject to change with APV implementation

Evaluation according to ecological indicator values of plants.

Ecological indicators

Interpretation against field of reference

3. Modeling

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3.1. Modeling- Agriculture Aspects

Figure (1): Biomass Yield as a Function of Relative Light Availability (PAR)

Plants react differently on shading

Response to shading of crops in arid regions

3. Modeling

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3.1. Modeling- Agriculture Aspects

0

20

40

60

80

100

120

140

20 30 40 50 60 70 80 90 100 110

Bio

mas

s yi

eld

[%

]

Photosynthetic Active Radiation (PAR) [%]

PLUS

ZERO

MINUS

Figure (2): Classification of Egypt’s most relevant economic plants in agriculture

PLUS category: Shading tolerant, crops are benefited from shade

ZERO category: No significant effect on yield

MINUS category: Shading sensitive, crops are badly influenced by shade

3. Modeling

Ramy Essam-APV June 18, 2014 8

3.1. Modeling- Agriculture Aspects

Figure (3): APV System Technology

1 = PV module

2 = foundation of intermediate supports

3 = foundation at the edge of the field

α = surface azimuth angle

b = module width

d = row spacing

d’ = distance between supports

L= modules length

h = clear height underneath the panels

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3. Modeling 3.1. Modeling- Technical Aspects

Figure (5): Simulation of Irradiance on Ground

Inclination Angle (15°, 25°)

Height of Installation (2m, 4m & 6m)

Orientation Angle (0°, 45°)

Row Spacing Distance (1.5-6.5m)

4. Simulation & Results

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Figure (4): Side View of an APV Module System Structure

4.1. Technical Variables

Figure (6): Global Horizontal Irradiation underneath Different Installation Heights.

Increasing height shows higher uniformity of solar irradiation distribution on ground.

Installation height of 4 m is to be considered for the upcoming calculations.

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4. Simulation & Results 4.2. Technical Results

4.2.1. Global Horizontal Irradiation vs Height

Figure (7): Global Horizontal Irradiation underneath Different Orientation of Arrays.

Optimal module orientation towards South results in heterogeneous distribution of radiation on ground level.

Orientation towards 45° South-west provides homogeneously distributed Irradiation.

Conclusion: Homogeneity of radiation is very important for crop cultivation ( simultaneous ripening, etc.) therefore, modules should have to be installed:

High

Not towards South

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4. Simulation & Results 4.2. Technical Results

4.2.2. Global Horizontal Irradiation vs Orientation angle

Figure (8): Photovoltaic Electric Yield

𝑷𝑽𝑬𝒓𝒆𝒍 𝐝; 𝜶 =𝐆𝐭

𝐝;𝜶 ∗𝐃 (𝐝𝐞𝐠𝐫𝐞𝐞 𝐨𝐟 𝐬𝐮𝐫𝐟𝐚𝐜𝐞 𝐜𝐨𝐯𝐞𝐫𝐚𝐠𝐞)

𝐆𝐭 𝟏.𝟓;𝟎 ∗𝐃 (𝐎𝐏𝐓𝐈𝐌𝐀𝐋 𝐝𝐞𝐠𝐫𝐞𝐞 𝐨𝐟 𝐬𝐮𝐫𝐟𝐚𝐜𝐞 𝐜𝐨𝐯𝐞𝐫𝐚𝐠𝐞)

∗ 𝟏𝟎𝟎

Orientation of array in an APV system towards 45° south-west. Electricity yield decreases by less than 5 % due to this suboptimal orientation.

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4. Simulation & Results 4.2. Technical Results

0

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40

60

80

100

120

1 2 3 4 5 6 7

PV

E [

%]

Row Spacing Distance [m]

Summer-South Winter-South

Summer-Southwest Winter-Southwest

4.2.3. Photovoltaic Electric Yield

Figure (9): Photosynthetically Active Radiation on Ground between modules

𝑷𝑨𝑹𝒓𝒆𝒍 𝒅 =𝐆𝐡𝐨𝐫

𝐝;𝛂;𝐮𝐧𝐝𝐞𝐫 𝒎𝒐𝒅𝒖𝒍𝒆

𝐆𝐡𝐨𝐫 𝐮𝐧𝐬𝐡𝐚𝐝𝐞𝐝 𝒂𝒓𝒆𝒂

∗ 𝟏𝟎𝟎

Photosynthetic active radiation in winter South-west oriented is higher than in South oriented.

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4. Simulation & Results 4.2. Technical Results

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7

PA

R [

%]

Row Spacing Distance [m]

Summer-South Winter-South

Summer-Southwest Winter-Southwest

4.2.4. Photosynthetic Active Radiation

Figure (10): Biomass Yield of APV south and 45°-Southwest oriented modules

45° South-west facing system and 25° inclination angle is a good regime to measure the effect of changing row spacing distance on the three categorized crops.

Slight differences, but only for winter crops.

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4. Simulation & Results 4.2. Technical Results

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7

BM

E [

%]

Row Spacing Distance [m]

PLUS-Summer

PLUS-Winter

ZERO-Summer

ZERO-Winter

MINUS-Summer

MINUS-Winter0

20

40

60

80

100

120

140

1 2 3 4 5 6 7B

ME

[%

]

Row Spacing Distance [m]

PLUS-Summer

PLUS-Winter

ZERO-Summer

ZERO-Winter

MINUS-Summer

MINUS-Winter

Standard Orientation: South Standard Orientation: 45° South-west

4.2.5. Biomass Yield

Figure (11): Land Equivalent Ratio

𝐋𝐄𝐑 =𝑩𝑴𝑬𝐀𝐏𝐕

𝑩𝑴𝑬𝒎𝒐𝒏𝒐+

𝑷𝑽𝑬𝐀𝐏𝐕

𝑷𝑽𝑬𝒎𝒐𝒏𝒐

It is a quantitative approach for determining productivity of APV, it measures the total output per unit area.

LER for summer crops of PLUS category increased by 80 % productivity at optimum row spacing of 2.9 m.

LER for the other two categories are in the range of 30 to 60 % higher in productivity compared to mono-cultivation.

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4. Simulation & Results 4.2. Technical Results

0,8

1

1,2

1,4

1,6

1,8

2

1 2 3 4 5 6 7

LE

R

Row Spacing Distance [m]

PLUS-Summer PLUS-Winter

ZERO-Summer ZERO-Winter

4.2.6. Land Equivalent Ratio

Ramy Essam-APV June 18, 2014 17

4. Simulation & Results 4.3. Technical & Economical Input Parameters

Technology Parameters Unit PVoff APVoff APVon

Operating Lifetime [a] 25 25 25

Surface Area [ha] 0.5 0.5 0.5

Investment Cost * [€/kWp] 1,210 1,700 1,700

Module Width [m] 1 1 1

Row Spacing Modules [m] 1.5 2.5 2.5

Rated Capacity of Module [W/m2] 2054 2054 2054

Installed Capacity ** [kWp] 676.5 410 410

Power Generation Yield *** [kWh/m2.a] 1,7901 1,7001 1,7001

PV System Power Generation [kWh/a] 1,210,935 697,205 697,205

Financial Parameters

Debt Percentage [%] 90 90 90

Equity Percentage [%] 10 10 10

Loan Repayment Time 5 [a] 10 10 10

Weighted Average Cost of Capital (WACC) [%] 7.23 7.79 7.51

Cost of Equity [%] 31.75 37.38 34.56

Beta Factor [-] 2 2.5 2.25

Annual Current Output Reduction [%] 0.21 0.21 0.21

Price of Electricity [€/kWh] 0.146 0.146 0.0697

Annual Operating Expenses

(as a percentage of investment)

[%] 21 21 21

Leased Land [€/a] 0 0 0

Agricultural Income [€/a] 0 6888 6888

Table (1): Input Technical and Financial Parameters for Economic Feasibility

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4. Simulation & Results 4.4. Economical Results

Results Unit PVoff APVoff APVon

Lifetime [a] 25 25 25

Total Investment Cost 10 [€] 818,565 697,000 697,000

Total Power Generation 11 [kWh] 29,557,833 17,018,146 17,018,146

Revenue on Sale of

Electricity

[€] 4,138,096 2,382,540 1,174,252

Maintenance Cost 12 [€] 409,282 348,500 348,500

Net Income Electricity [€] 2,910,249 1,337,040 128,752

Net Income Agriculture [€] 0 32,836 32,836

Total Net Revenue [€] 2,910,249 1,369,876 161,588

Present Value (PV) [€] 1,716,588 904,040 383,961

Weighted Average Cost of

Capital (WACC)

[%] 7.23 7.79 7.51

Net Present Value (NPV) [€] 898,023 207,040 -313,038

Internal Rate of Return

(IRR)

[%] 18.22 10.92 1.37

Electricity Generation Costs

(LCOE)

[€/kWh] 0.07 0.114 0.111

Table (2): Results of the Investment Analysis of an APV System in comparison with a Conventional PV System

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4. Simulation & Results 4.5. Sensitivity Analysis-Investment Cost

Figure (12): The influence of Investment cost on the NPV and IRR for APV off-grid scenario.

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800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800

IRR

[%

]

NP

V [

*10

00

€/h

a]

Investment cost [€/kWp]

NPV

IRR

Ramy Essam-APV June 18, 2014 20

4. Simulation & Results 4.6. Sensitivity Analysis-Electricity Cost

Figure (13): The influence of Electricity cost on the NPV and IRR for APV on-grid scenario.

0

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4

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8

10

12

-400

-300

-200

-100

0

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200

300

0 0,02 0,04 0,06 0,08 0,1 0,12 0,14 0,16

IRR

[%

]

NP

V [

*10

00

€/h

a]

Electricity cost [€/kWh]

NPV

IRR

APV off-grid Technology is Technically and Economically fesible.

APV off-grid scenario can compete with PV scenario by decreasing the investment cost and for APV on-grid by increasing the price of electricity (Feed-in Tariff).

In the off-grid scenario, reducing the investment cost due to relying on local material of construction. Result in APV-off grid technology could still compete with a PV system.

Coexisting of PV and plant cultivation is “theoretically” feasible in Egypt and “practically” proven elsewhere (e.g. France and Italy)

(In Egypt: only if economic framework will be established)

5. Conclusion

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P = Surface area ∗ PAPV,ha

APV-Potential in Egypt equals 123-246 GWp.

APV-Potential in Minya equals 14-29 MWp.

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6. Future Recommendations 6.1. APV Potential-Case Study in Minya

Potential Restriction 𝐏𝐀𝐏𝐕,𝐡𝐚 Surface Area P

[kWp/ha] [ha] [MWp]

Theoretical Agriculture Land 820 420 344

Technical Plants of Categories

PLUS and ZERO

820 350 287

Technical Assumption:

Sustainability of 5-10 %

of the area

820 17.5-35 14-29

Table (3): Assessment of Theoretical and Technical Potential of APV in Minya

Sekem and Fraunhofer ISE intend to kick-off a pilot project in Egypt

Recommended to Calculate:

Amount of irrigation water savings .

GHG emissions due to the replacement of APV-electricity to diesel generators in off-grid regions.

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6. Future Recommendations 6.2. Recommendation for Action

Source: Green Valley Farm, SEKEM.

Some results of the present study based only on theoretical assumptions, their validation is still pending. The three dominant uncertainties that should be examined are:

Data basis for assessing the shade tolerance of crops

Yield models of the three plant categories

Boundary conditions of the economic analysis

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6. Future Recommendations 6.3. Uncertainties and Future Work

Source: Green Valley Farm, SEKEM

Finally, the use of APV still appears to be a significant and purposeful approach to enhance the productivity of the same land area between agriculture and energy sector.

7. Summary

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Source: www.google.de/images

Thank you very

much for your attention…

8. Questions & Answers

Ramy Essam-APV June 18, 2014 26