PV GENERATION SHARE IN THE ENERGY SYSTEM AND BATTERY ... · 3 PV generation share in the energy system and battery utilisation correlation in a net zero emission world Dmitrii Bogdanov

PV GENERATION SHARE IN THE ENERGY SYSTEM AND BATTERY UTILISATION

CORRELATION IN A NET ZERO EMISSION WORLD

Dmitrii Bogdanov, Ashish Gulagi and Christian BreyerLUT School of Energy SystemsLappeenranta University of Technology, Finland

NEO-CARBON ENERGY 7th RESEARCHERS’ SEMINARJanuary 25, 2017

2 PV generation share in the energy system and battery utilisation correlation in a net zero emission worldDmitrii Bogdanov [email protected]

Agenda

MotivationMethodology and DataResults for the Energy SystemsAlternatives to 100% RESummary


Motivation

• Cutting of the greenhouse gases world wide is the only way to limit global warming and decrease level of provoked ecological problems as it was agreed at COP 21.

• All countries should transform their energy systems towards carbon-neutrality to limit global warming to 2 ºC since the preindustrial epoch.

• Renewable energy is the only sustainable solution

• PV and Wind will be the two major energy sources in the future system, however for a RE based system energy storage technologies play an extremely important role.

• Sustainability, reliability and the cost of the RE energy system depend not only on RE generation but to large extent also on the storage system configuration.

• What is the optimal storage structure for the future PV based energy system?


Agenda

MotivationMethodology and DataResults for the Energy SystemsAlternatives to 100% RESummary


MethodologySystem configuration

North America

South America

Southeast Asia

Northeast Asia

EurasiaEurope

MENA

Sub-Saharan Africa

SAARC

• Optimal RE based systems for year 2030 assumptions were calculated for the whole world divided in 9 major regions: Europe, Eurasia, Northeast Asia, Southeast Asia, Indian subcontinent, Middle East North Africa (MENA), Sub-Saharan Africa, North America and South America.

• Major regions are assumed isolated – there are no energy flows between these regions in the model but unlimited within.


MethodologyModel description

Definition of an optimally structured energy system based on 100% RE supply• optimal set of technologies, best adapted to the availability of the regions’ resources,• optimal mix of capacities for all technologies and every sub-region,• optimal operation modes for every element of the energy system, • least cost energy supply for the given constraints.

LUT Energy model, key features• linear optimization model• hourly resolution• multi-node approach• flexibility and expandability

Input data• historical weather data for: solar irradiation, wind

speed and hydro precipitation• available sustainable resources for biomass and

geothermal energy• synthesized power load data• gas and water desalination demand• efficiency/ yield characteristics of RE plants• efficiency of energy conversion processes• capex, opex, lifetime for all energy resources• min and max capacity limits for all RE resources• nodes and interconnections configuration


MethodologyFull system

Renewable energy sources• PV rooftop• PV ground-mounted• PV single-axis tracking • Wind onshore/ offshore• Hydro run-of-river• Hydro dam• Geothermal energy• CSP• Waste-to-energy• Biogas• Biomass

Electricity transmission• node-internal AC transmission• interconnected by HVDC lines

Storage options• Batteries • Pumped hydro storage• Adiabatic compressed air storage• Thermal energy storage, Power-to-Heat• Gas storage based on Power-to-Gas

• Water electrolysis• Methanation• CO2 from air• Gas storage

Energy Demand• Electricity• Water Desalination• Industrial Gas


Scenarios assumptionsFinancial assumptions (year 2030)

Technology Capex [€/kW]

Opex fix [€/(kW a)]

Opex var[€/kWh]

Lifetime [a]

PV rooftop 813 12 0 35PV fixed-tilted 550 8 0 35PV single-axis 620 9 0 35Wind onshore 1000 20 0 25Hydro Run-of-River * 2560 115.2 0.005 50Hydro dam * 1650 66 0.003 50Geothermal energy 4938 89 0 30Water electrolysis 380 13 0.001 30Methanation 234 5 0 30CO2 scrubbing 356 14 0.0013 30CCGT 775 19 0.002 30OCGT 475 14 0.011 30Biomass PP 2500 175 0.001 30Wood gasifier CHP 1500 20 0.001 40Biogas CHP 370 14.8 0.001 20MSW incinerator 5240 235.8 0.007 20Steam turbine 700 14 0 30

Technology Capex [€/(m3 a)]

Opex fix [€/(m3 a)]

Opex var[€/(m3 a)]

Lifetime [a]

Water desalination 2.23 0.096 0 30

Generation costsTechnology Energy/Power Ratio [h]Battery 6PHS 8A-CAES 100Gas storage 80*24

Efficiency [%]Battery 90PHS 85A-CAES 83Gas storage 100Water electrolysis 84CO2 scrubbing 78Methanation 77CCGT 58OCGT 43Geothermal energy 24MSW incinerator 34Biogas CHP 40Steam turbine 42CSP collector 51

* hydro power plants older than 50 years are taken into accountwith refurbishment capex of 500 €/kW for 30 years


Technology Capex [€/kWh]

Opex fix [€/(kWh a)]

Opex var[€/kWh]

Lifetime [a]

Battery 150 10 0.0002 10/20PHS 70 11 0.0002 50A-CAES 31 0.4 0.0012 40Gas storage 0.05 0.001 0 50

Technology Capex [€/(m3 h)]

Opex fix [€/(m3 a)]

Opex var[€/(m3 h)]

Lifetime [a]

Water storage 65 1 0 50

Technology Capex [€/(m3 km)]

Opex fix[€/(m3 km a)]

Opex var[kWh/(m3 km)]

Lifetime [a]

Horizontal pumping 15 2.3 0.0004 30Vertical pumping 23 2.4 0.0036 30

Technology Capex [€/(kW km)]

Opex fix [€/(kW km a)]

Opex var[€/kW]

Lifetime [a]

Transmission line 0.612 0.0075 0 50

Technology Capex [€/kW]

Opex fix [€/(kW a)]

Opex var[€/kW]

Lifetime [a]

Converter station 180 1.8 0 50

Scenarios assumptionsFinancial assumptions (year 2030)

Storage and transmission costs

WACC = 7%


Scenarios assumptionsFull load hours

Data: based on NASA (Stackhouse P.W., Whitlock C.H., (eds.), 2009. SSE release 6.0)reprocessed by DLR (Stetter D., 2012. Dissertation, Stuttgart)

• Solar resources are more evenly distributed over the planet: almost in every region FLH for PV generation exceed 1000 FLH

• In regions such as MENA, Sub-Saharan AfricaSoutheast Asia and India/SAARC solar resources are much better than wind resources.


Scenarios assumptionsPV and Wind LCOE (weather year 2005, cost year 2030)

• In the same regions: MENA, Sub-Saharan Africa, Southeast Asia and India/SAARC we can observe much lower electricity costs for year 2030 assumptions than for wind

• In such regions solar PV supposed to have the highest share in the energy system for both capacities and generation


Scenarios assumptionsGeneration profile (for MENA region)

PV generation profile Wind generation profile

PV generation profile is constant over the year, but has dailyvariations. While the wind generation is more seasonal.


Agenda

MotivationMethodology and DataResults for the Energy SystemAlternatives to 100% RESummary


ResultsInstalled generation capacities worldwide

• Solar PV capacities exceed 50% of total capacities mix in Northeast Asia, Southeast Asia, South America and India/SAARC. Only in the India/SAARC system, PV exceeds 50% of total generation.

source: Breyer Ch., Bogdanov D., et al., 2016. On the Role of Solar Photovoltaics in Global Energy Transition Scenarios, 32nd EU PVSEC, Munich, June 20-24


ResultsInstalled capacities and generation

Region

Installed capacity Generated energy

PV prosumers

total

PV optimally

tilted

PV single-axis

PV total capacity

share

PV prosumers

total

PV optimally

tilted

PV single-axis

PV total generation

share

Wind onshore

% % % % % % % % %World 25.9 1.4 22.4 49.7 18.2 0.9 20.8 39.9 47.0Europe 30.7 4.5 6.2 41.3 18.8 2.7 5.9 27.4 63.8Eurasia 15.7 1.1 2.7 19.5 7.5 0.6 1.8 9.9 62.9MENA 9.7 1.3 29.8 40.8 8.6 1.1 34.5 44.3 58.6NE Asia 28.5 1.1 23.8 53.4 22.4 0.9 22.1 45.3 46.1SE Asia 21.2 0.7 41.6 63.5 14.3 0.5 33.7 48.4 16SAARC 12.8 0.3 51.2 64.4 9 0.2 44.3 53.5 20.2Africa 16 0.4 29.1 45.5 12.1 0.3 29.7 42.1 46.9S America 38.8 0.2 21.2 60.2 23.6 0.1 16.5 40.3 14.4N America 29.4 0.7 16.4 46.6 20.4 0.5 16.3 37.2 59.2


ResultsInstalled storage capacities worldwide

• In India/SAARC, Southeast Asia and Sub-Saharan Africa batteries represent more than 50% of all storage capacities.

• Prosumers batteries storage play a most relevant role in the systems in all the regions except Eurasia, India/SAARC and MENA

source: Breyer Ch., Bogdanov D., et al., 2016. On the Role of Solar Photovoltaics in Global Energy Transition Scenarios, 32nd EU PVSEC, Munich, June 20-24


ResultsPV generation and storage output

Region

Generated PV electricity Energy output Storage

PV prosumers

total

PV optimally

tilted

PV single-axis

PV total generation

share

Battery prosumers

total

Battery system

Battery total PHS Gas

storage

% % % % % % % % %World 18.2 0.9 20.8 39.9 5.1 4.4 9.5 1.3 2.7Europe 18.8 2.7 5.9 27.4 5.2 0.1 5.3 2.9 3.2Eurasia 7.5 0.6 1.8 9.9 0.0 0.2 0.2 0.1 3.1MENA 8.6 1.1 34.5 44.3 1.2 5.8 7.0 0.0 3.5NE Asia 22.4 0.9 22.1 45.3 6.8 3.9 10.6 2.6 2.1SE Asia 14.3 0.5 33.7 48.4 3.3 10.2 13.6 0.1 2.2SAARC 9 0.2 44.3 53.5 0.0 16.2 16.3 0.4 2.1Africa 12.1 0.3 29.7 42.1 2.7 6.3 8.9 0.1 2.6S America 23.6 0.1 16.5 40.3 7.3 2.2 9.5 0.0 3.7N America 20.4 0.5 16.3 37.2 6.9 2.5 9.5 0.1 3.1


Results

Eurasia

MENA Europe Africa N AmericaNE Asia

S AmericaSE Asia SAARC

0

2

4

6

8

10

12

14

16

18

0

10

20

30

40

50

60

70

Shor

t-ter

m s

tora

ge s

hare

[%]

PV sh

are [

%]

PV Total Capacities sharePV Total Generation shareShort-term storage generation share

correlation between system PV capacities share and battery storage share: 0.96


Agenda



LCOE of alternatives are NO alternative

source: Agora Energiewende, 2014. Comparing the Cost of Low-Carbon Technologies: What is the Cheapest option; Grubler A., 2010. The costs of the French nuclear scale-up: A case of negative learning by doing, Energy Policy, 38, 5174

Key insights:PV-Wind-Gas is the least cost optionnuclear and coal-CCS is too expensivenuclear and coal-CCS are high risk technologies100% RE systems are highly cost competitive

Preliminary NCE resultsclearly indicate 100% RE systems cost about55-70 €/MWh for 2030 cost assumptions on comparable basis

source: Breyer Ch., et al., 2016. On the Role of Solar Photovoltaics in Global Energy Transition Scenarios, 32nd EU PVSEC, Munich, June 20-24


Agenda



Summary

• PV generation will be a major energy source in 100% RE based systems for all regions in the world

• The highest share of PV capacities and generation in the optimal mix is expected to be reached in the India/SAARC region

• PV and battery storage utilization are strongly correlated• Correlation between PV capacities share and share of short-term

storage in total generation reaches 0.92 • Correlation between system PV capacities share and battery storage

share reaches 0.96.• The relevance of short-term storage increases in the PV generation

based energy systems and stays rather low in the wind energy based systems.

Thanks for your attention …… and to the team!

The authors gratefully acknowledge the public financing of Tekes, the Finnish Funding Agency for Innovation, for the ‘Neo-Carbon Energy’ project under the number 40101/14.

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PV GENERATION SHARE IN THE ENERGY SYSTEM AND BATTERY ... · 3 PV generation share in the energy system and battery utilisation correlation in a net zero emission world Dmitrii Bogdanov