eurasian super grid for 100% renewable energy power supply

EURASIAN SUPER GRID FOR 100% RENEWABLE ENERGY POWER SUPPLY: GENERATION AND STORAGE TECHNOLOGIES IN THE COST OPTIMAL MIX Dmitrii Bogdanov and Christian Breyer Lappeenranta University of Technology, Finland

ISES Solar World Congress 2015 Daegu, 12.11.2015

Agenda

     

2

Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary

Eurasian Super Grid for 100% RE power supply Dmitrii Bogdanov ► [email protected]

Eurasia’s RE potential • Huge renewable resources of Eurasia: • Perfect wind conditions in North Russia • Perfect wind and solar irradiation in Central Asia • High hydro capacities and potential in Siberia, Volga region and Pamir • High share of hydro dam power plants providing additional flexibility to the system • Vast biomass resources from residues from agricultural and forestry industries

• Growing electricity demand • Promising possibility to build cost competitive independent 100% RE system using current technologies

3


Current status of the power plant mix

4


Agenda

     

5



Key Objective 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 of Eurasia, • optimal operation modes for every element of the energy system, • least cost energy supply for the given constraints.

LUT Energy model, key features • • • •

6

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

Methodology Full system Renewable energy sources • PV ground-mounted • PV single-axis tracking • PV rooftop • Wind onshore • 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 storages • Adiabatic compressed air storage • Thermal energy storage, Power-to-Heat • Gas storage based on Power-to-Gas • Water electrolysis • Methanation • CO2 from air Eurasian Grid for 100% RE power supply • GasSuper storage 7 Dmitrii Bogdanov ► [email protected]

Energy Demand • Electricity • Water Desalination • Industrial Gas

Scenarios assumptions

13 regions • 7 Federal Districts of Russia • Belarus • Caucasus region including Armenia, Azerbaijan and Georgia • Kazakhstan • Pamir region including Kirgizstan and Tajikistan • Uzbekistan • Turkmenistan 8


Key data • ~244 mio population (2030) • ~1450 TWh electricity demand (2030) • ~255 GW peak load (2030) • ~21 mio km2 area • ~18 bil m3/a water desalination demand (2030)

Scenarios assumptions Grid configurations

• Regional-wide open trade • (no interconnections between regions)

• Country-wide open trade • (no interconnections between countries)

• Area-wide open trade • (country-wide HVDC grids are interconnected)

• Area-wide open trade with water desalination and industrial gas production Scenarios Assumption PV selfconsumption

Regional-wide Country-wide open trade open trade X

X

Area-wide open trade

Area-wide open trade Des-Gas

X

X

Water Desalination

X

Industrial Gas

X

9


Scenarios assumptions Financial assumptions (year 2030) Generation costs

Technology PV rooftop PV fixed-tilted PV single-axis Wind onshore Hydro Run-of-River Hydro Dam Geothermal energy Water electrolysis Methanation CO2 scrubbing CCGT OCGT Biomass PP Wood gasifier CHP Biogas CHP MSW incinerator Steam Turbine Technology Water Desalination

10

Capex [€/kW] 813 550 620 1000 2560 1650 4860 380 234 356 775 475 2500 1500 370 5240 700

Opex fix [€/kW] 12 8 9 20 115.2 66 87 13 5 14 19 14 175 20 14.8 235.8 14

Opex var [€/kWh] 0 0 0 0 0.005 0.003 0 0.001 0 0.0013 0.002 0.011 0.001 0.001 0.001 0.007 0

Lifetime [a] 35 35 35 25 60 60 30 30 30 30 30 30 30 40 20 20 30

Capex [€/(m3∙a)] 2.23

Opex fix [€/(m3∙a)] 0.096

Opex var [€/(m3∙a)] 0

Lifetime [a] 30


Technology Battery PHS A-CAES Gas Storage

Battery PHS A-CAES Gas Storage Water Electrolysis CO2 Scrubbing Methanisation CCGT OCGT Geothermal energy MSW Incinerator Biogas CHP Steam Turbine CSP collector

Energy/Power Ratio [h] 6 8 100 80*24 Efficiency [%] 90 92 70 100 84 78 77 58 43 24 34 40 42 51

Scenarios assumptions Financial assumptions (year 2030) Storage and transmission costs Technology Battery PHS A-CAES Gas Storage Technology Water Storage

Technology Horizontal pumping Vertical pumping Technology Transmission Line Technology Converter Station

11

Capex [€/kWh] 150 70 31 0.05

Opex fix [€/(kWh∙a)] 10 11 0.4 0

Opex var [€/kWh] 0.0002 0.0002 0.0012 0

Lifetime [a] 10 50 40 50

Capex [€/(m3∙h)] 65

Opex fix [€/(m3∙h∙a)] 1

Opex var [€/(m3∙h)] 0

Lifetime [a] 50

Capex [€/(m3∙h∙km)]

Opex fix [€/(m3∙h∙km∙a)]

15 23

2.3 2.4

Energy consumption [kWh/(m3∙h∙km)] 0.0004 0.0036

Capex [€/(kW∙km)] 0.612

Opex fix [€/(kW∙km∙a)] 0.0075

Opex var [€/kW] 0

Capex [€/kW] Opex fix [€/(kW∙a)] Opex var [€/kW] 180 1.8 0


WACC = 7% Lifetime [a] 30 30 Lifetime [a] 50 Lifetime [a] 50

Scenarios assumptions Full load hours Region Russia NorthWest Russia Central Russia Southern Russia Volga Russia Ural Russia Siberian Russian Far East Belarus Caucasus Kazakhstan Pamir Uzbekistan Turkmenistan

PV fixed- PV 1-axis CSP Wind tilted FLH FLH FLH FLH 979

1262

1200 3636

1130 1241 1184 1014 1174 1136 1058 1414 1427 1688 1518 1542

1408 1511 1473 1292 1491 1477 1281 1667 1815 2178 1931 1935

1221 1305 1314 1194 1390 1397 1074 1398 1726 1970 1872 1829

2970 3155 2973 3502 3049 2712 2835 1877 3149 2337 2766 2769

FLH of region computed as weighed average of regional sub-areas (about 50 km x 50 km each): 0%-10% best “sub-areas” of region – 0.3 10%-20% best “sub-areas” of region – 0.3 20%-30% best “sub-areas” of region – 0.2 30%-40% best “sub-areas” of region – 0.1 40%-50% best “sub-areas” of region – 0.1

12


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

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

13


Scenarios assumptions Generation profile (area aggregated)

14

PV generation profile

Wind generation profile

Aggregated area profile computed using earlier presented weighed average rule.

Aggregated area profile computed using earlier presented weighed average rule.


Scenarios assumptions Load (area aggregated) Synthesized load curves for each region Total load (2030)

Total load (2030) - including the impact of prosumers (less load)

Key insights: • PV self-consumption does not reduce the peak load but reduces the gradients in the system 15


Agenda

     

16



Results Total 2030 Scenario LCOE

LCOE primary

LCOC

[€/kWh] [€/kWh] [€/kWh] Region-wide

Country-wide Area-wide Area-wide Des-Gas*,**

Total ann. Total RE Generated cost CAPEX capacities electricity

LCOS

LCOT

[€/kWh]

[€/kWh]

[bn €]

[bn €]

[GW]

[TWh]

0.063 0.057 0.053

0.043 0.042 0.041

0.003 0.002 0.002

0.017 0.011 0.007

0.000 0.002 0.004

91 82 77

837 758 713

739 648 583

1771 1681 1613

0.043

0.039

0.001

0.001

0.002

125

1166

981

2654

Total LCOE LCOS Total ann. Total RE Generated LCOE*** primary prosumer Cost CAPEX capacities electricity prosumer prosumer prosumer prosumer prosumer prosumer [€/kWh] [€/kWh] [€/kWh] [bn €] [bn €] [GW] [TWh]

0.042

17

0.054

0

5


61

91

109

*

additional demand 86% gas and 14% desalination ** LCOS does not include the cost for the industrial gas (LCOG) *** fully included in table above

LCOW: 1.49 €/m3 LCOG: 0.113 €/kWhth,gas

Results Self-Consumption – Eurasia super-region area-wide open trade

18

Electricity price [€/kWh] PV LCOE [€/kWh] Self-consumption PV LCOE [€/kWh] Self-consumption PV and Battery LCOE [€/kWh] Self-consumption LCOE [€/kWh] Benefit [€/kWh]

RES 0.065 0.036 0.045 0.045 0.040 0.025

2030 COM 0.075 0.049 0.054 0.054 0.052 0.023

IND 0.085 0.049 0.057 0.057 0.054 0.031

Installed capacities PV [GW] Battery storage [GWh]

RES 19 0

COM 26 0

IND 46 0

Generation PV [TWh] Battery storage [TWh] Excess [TWh]

RES 22.8 0 4.6

COM 31.3 0 3.2

IND 55.0 0 7.4

Utilization Self-consumption of generated PV electricity [%] Self-coverage market segment [%] Self-coverage operators [%]

RES 79.7 7.5 37.3

COM 89.8 6.1 30.7

IND 86.5 6.4 31.8


Source (electricity prices): Gerlach A., Werner Ch., Breyer Ch., 2014. Impact of Financing Cost on Global Grid-Parity Dynamics till 2030, 29th EU PVSEC, Amsterdam, September 22-26

Results Total Electricity generation RE (TWh)

Benefits of electricity and industrial gas sectors integration – Area-wide desalination gas 3500 3000

18.3 % relative integration benefit 594 TWh absolute integration benefit

DesalinationSector

2500 2000

Key insights: • integration benefits: decrease in total electricity demand and total annual levelized cost • descrease in total electricity curtailment losses of 41.4% (46.6 TWh absolute) and in total capex by 24.5% (379 bn€ absolute)

Ind Gas Sector

1500

1000

Power Sector

500 0 180

Independent sectors

Integrated sectors

Total annual cost (bn€)

160 140

DesalinationSector

120 100

Ind Gas Sector

80 60 40

Power Sector

20 0 Independent sectors

19


Integrated sectors

23.2% relative integration benefit 37.8 bn€ absolute integration benefit

Results Import / Export (year 2030) Area-wide open trade

Key insights: • Net Importers: Belarus, Central Russia • Net Exporters: Northwest Russia, Ural, Pamir

20


Results Total LCOE (year 2030) – region-wide open trade

21



22



23



24


Results Total LCOE (year 2030) – area-wide open trade

25



26



27



28


Results Components of LCOE – area-wide open trade and area-wide desalination gas Area-wide open trade

Area-wide open trade desalination gas

29


Results Installed Capacities

2030 Scenario

Hydro Hydro Wind PV RoR dams Biogas Biomass Waste Geothermal Battery PHS CAES

[GW] [GW] [GW] [GW] [GW]

[GW]

[GW]

[GW]

PtG

GT

[GWh] [GWh] [GWh] [GWel] [GW]

Region-wide 327 207

0.2

88

15.2

17.3

1.3

2.7

15.2

9.0

1783

32.5

89

Country-wide 318 146

0.2

88

15.1

16.7

1.3

2.7

15.2

9.0

497.4 21.7

71

Area-wide

300

113

0.1

91

13.8

16.4

1.3

2.7

8.7

9.0

0.3

15.8

Integrated

560 263

6.4

91

10.4

14.5

1.3

2.4

0.5

9.0

0.0

105.2 34

2030 Scenario

PV PV PV fixed-tilted single-axis prosumers

PV total

Battery Battery Battery system prosumers total

[GW]

[GW]

[GW]

[GW]

[GWh]

[GWh]

[GWh]

Region-wide

6.0

109.4

91.5

206.9

15.2

0

15.2

Country-wide

6.0

49.0

91.5

146.5

15.2

0

15.2

Area-wide

6.5

15.5

91.5

113.4

8.7

0

8.7

Integrated

0.2

170.9

91.5

262.6

0.5

0

0.5

30


56

Results Resource utilization – area-wide open trade and area-wide desalination gas Area-wide open trade


PV total capacity 113 GW

PV total capacity 263 GW, +133%

Wind total capacity 300 GW

Wind total capacity 560 GW, +87%

Key insights: • PV and wind capacities are increased substantially in area-wide desalinationgas scenario

31


Results Regions Electricity Capacities – area-wide open trade Area-wide open trade


Key insights: • Area-wide scenario shows negligible system PV capacities in most of the regions, prosumers share is restricted by low electricity prices • Specific climate conditions in Caucasus lead to significant share of fixed-tilted PV Key insights: • PV plays a major role in Area-wide desalination gas scenario for Central Asia and Caucasus • PV single-axis and wind are the main sources of electricity for water desalination and industrial gas production, especially for importing regions

32


Results Storages

Storage capacities

Throughput of storages

Full cycles per year

Battery PHS A-CAES Gas Battery PHS A-CAES Gas Battery PHS A-CAES Gas 2030 Scenario [-] [TWhel] [TWhel] [TWhel] [TWhth] [TWhel] [TWhel] [TWhel] [TWhth] [-] [-] [-] Region-wide

15.2

9.0

1783.5

87.2

4.7

1.6

41.2

147.6

307.0

181.0

23.1

1.7

Country-wide

15.2

9.0

497.4

69.9

4.7

1.5

11.6

107.9

307.0

163.3

23.3

1.5

Area-wide

8.7

9.0

0.3

62.9

3.1

1.5

0.0

89.7

354.5

161.5

-

1.4

Integration

0.5

9.0

0.0

70.3

0.1

0.9

0.0

11.4

260.0

100.1

-

0.2

Thermal energy storage share is negligible because of climate conditions being unfavourable for CSP power plants and lack of competitiveness of TES with other storage technologies.

33


Results Storages Capacities – area-wide and area-wide open trade desalination gas Area-wide open trade

Key insights: • Excess energy for area-wide open trade desalination gas: higher in absolute numbers, but lower in relative ones (from 3.7% to 2.6% of total generation). • Hydro dams as virtual battery very important, batteries do not play a significant role for balancing periods of wind and solar shortages

34



Agenda

     

35



Results Net importer region – Central Russia

36


Results Balancing region – Kazakhstan

37


Results Net exporter region – North-West Russia

38


Results Energy flow of the System of area-wide open trade desalination gas (2030)

Key insights: • PV generation share does not exceed 14%, Wind is the major energy source • A-CAES and gas storages are substituted by flexible demand of gas synthesis

39


Comparison to other regions Regions

LCOE total regionwide

LCOE total areawide

Integrat storag grids Curtail PV PV Wind Biomass hydro* ion es* interre ment prosu system * * benefit gional mers* * ** trade*

[€/MWh]

[€/MWh]

[%]

[%]

[%]

[%]

[%]

North-East Asia

77

68

6.0%

10%

26%

6%

14.3%

South-East Asia

67

64

9.5%

8%

3%

3%

Eurasia

63

53

23.2%