EVOLUTIONARY TRENDS THAT DISRUPT THE CURRENT DOMINANT ENERGY SECTOR STRUCTURE: THE EXAMPLE OF 100% RENEWABLE ENERGY POWER SUPPLY IN EURASIA

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1 EVOLUTIONARY TRENDS THAT DISRUPT THE CURRENT DOMINANT ENERGY SECTOR STRUCTURE: THE EXAMPLE OF 100% RENEWABLE ENERGY POWER SUPPLY IN EURASIA Christian Breyer Professor for Solar Economy Lappeenranta University of Technology, Finland; Energy Watch Group, Berlin Research Workshop on Global Trends and Uncertainties in the Energy Sector at Higher School of Economics Moscow, December 11, 2015

2 Agenda Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary 2

3 What is the key problem? Climate Change presents a unique challenge for economics: it is the greatest and widest-ranging market failure ever seen. N. Stern, Economics of Climate Change,

4 IPCC mitigation in energy sectors source: IPCC, th AR Synthesis Report 4 Key insights: GHG emissions in the power sector to be zero by 2050 ALL new investments MUST fulfill this requirement

5 We have a dramatic subsidy problem Key insights: global energy subsidies are almost fully allocated for fossil (and nuclear) fuels fossil fuel subsidies are as large as global expenditures for the health sector RE would grow much faster if harmful fossil-nuclear subsidies would be phased-out 5

6 PV capacity expectations and role of IEA 2DS hi-ren NPS GW 1799 GW 1721 GW 1927 GW 728 GW 938 GW GW 3687 GW 3199 GW 3277 GW 1066 GW 1519 GW Key insights: leading reports show at least 2-4 times higher numbers than IEA WEO for 2030 and 2040 IEA WEO is lagging behind due to assuming wrong growth Greenpeace and BNEF had been close to real numbers in the past 10 years forecasts of fossil fuel companies such as Shell, BP and ExxonMobil are as conservative as the IEA WEO 6 source: Greenpeace, BNEF, IEA

7 Installed capacities in the World Key insights Substantial increse of renewables in the world in last ten years Still high share of unsustainable resource use in the power plant portfolio New installed capacities more sustainable 7

8 Current status of the mix in Eurasia Key insights Eurasia is lagging behind the trend towards renewables Power plant portfolio is suited perfectly to host high RE capacities due to hydro dams and gas Rather old power plant structure offers the chance to invest in sustainable technologies 8

9 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 9

10 Agenda Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary 10

11 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 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 11

12 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 CO 2 from air 12 Evolutionary Gas storage trends on the example of Eurasia Energy Demand Electricity Water Desalination Industrial Gas

13 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 Key data ~244 mio population (2030) ~1450 TWh electricity demand (2030) ~255 GW peak load (2030) ~21 mio km 2 area ~18 bil m 3 /a water desalination demand (2030) 13

14 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 Regional-wide open trade Country-wide open trade Area-wide open trade Area-wide open trade Des-Gas PV selfconsumption Water Desalination Industrial Gas X X X X X X 14

15 Scenarios assumptions Financial assumptions (year 2030) Generation costs Technology Capex Opex fix Opex var Lifetime [ /kw] [ /kw] [ /kwh] [a] PV rooftop PV fixed-tilted PV single-axis Wind onshore Hydro Run-of-River Hydro Dam Geothermal energy Water electrolysis Methanation CO 2 scrubbing CCGT OCGT Biomass PP Wood gasifier CHP Biogas CHP MSW incinerator Steam Turbine Capex Opex fix Opex var Lifetime Technology [ /(m 3 a)] [ /(m 3 a)] [ /(m 3 a)] [a] Water Desalination Technology Energy/Power Ratio [h] Battery 6 PHS 8 A-CAES 100 Gas Storage 80*24 Efficiency [%] Battery 90 PHS 92 A-CAES 70 Gas Storage 100 Water Electrolysis 84 CO 2 Scrubbing 78 Methanisation 77 CCGT 58 OCGT 43 Geothermal energy 24 MSW Incinerator 34 Biogas CHP 40 Steam Turbine 42 CSP collector 51 15

16 Scenarios assumptions Financial assumptions (year 2030) Storage and transmission costs Technology Capex Opex fix Opex var Lifetime [ /kwh] [ /(kwh a)] [ /kwh] [a] Battery PHS A-CAES Gas Storage Capex Opex fix Opex var Lifetime Technology [ /(m 3 h)] [ /(m 3 h a)] [ /(m 3 h)] [a] Water Storage Technology Capex [ /(m 3 h km)] Opex fix [ /(m 3 h km a)] Energy consumption [kwh/(m 3 h km)] Lifetime [a] Horizontal pumping Vertical pumping WACC = 7% Capex Opex fix Opex var Lifetime Technology [ /(kw km)] [ /(kw km a)] [ /kw] [a] Transmission Line Technology Capex [ /kw] Opex fix [ /(kw a)] Opex var [ /kw] Lifetime [a] Converter Station

17 Scenarios assumptions Full load hours Region PV fixedtilted FLH PV 1-axis FLH CSP FLH Wind FLH Russia North- West Russia Central Russia Southern Russia Volga Russia Ural Russia Siberian Russian Far East Belarus Caucasus Kazakhstan Pamir Uzbekistan Turkmenistan 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 %-20% best sub-areas of region %-30% best sub-areas of region %-40% best sub-areas of region %-50% best sub-areas of region Data: based on NASA (Stackhouse P.W., Whitlock C.H., (eds.), SSE release 6.0) reprocessed by DLR (Stetter D., Dissertation, Stuttgart)

18 Scenarios assumptions PV and Wind LCOE (weather year 2005, cost year 2030) 18

19 Scenarios assumptions Generation profile (area aggregated) PV generation profile Aggregated area profile computed using earlier presented weighed average rule. Wind generation profile Aggregated area profile computed using earlier presented weighed average rule. 19

20 Scenarios assumptions Load (area aggregated) Synthesized load curves for each region Total load (2030) Total load (2030) - including the impact of prosumers (less load) 20 Key insights: PV self-consumption does not reduce the peak load but reduces the gradients in the system

21 Agenda Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary 21

22 Results 2030 Scenario Total LCOE LCOE primary LCOC LCOS LCOT Total ann. cost Total CAPEX RE Generated capacities electricity [ /kwh] [ /kwh] [ /kwh] [ /kwh] [ /kwh] [bn ] [bn ] [GW] [TWh] Region-wide Country-wide Area-wide Area-wide Des-Gas*, ** Total LCOE LCOE*** primary prosumer prosumer LCOS prosumer Total ann. Cost prosumer Total CAPEX prosumer RE capacities prosumer Generated electricity prosumer [ /kwh] [ /kwh] [ /kwh] [bn ] [bn ] [GW] [TWh] * 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 /m 3 LCOG: /kwh th,gas 22

23 Total annual cost (bn ) Total Electricity generation RE (TWh) 23 Results Benefits of electricity and industrial gas sectors integration Area-wide desalination gas DesalinationSector Ind Gas Sector Power Sector Independent sectors DesalinationSector Ind Gas Sector Power Sector Independent sectors Integrated sectors Integrated sectors 18.3 % relative integration benefit 594 TWh absolute integration benefit 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) 23.2% relative integration benefit 37.8 bn absolute integration benefit

24 Results Import / Export (year 2030) Area-wide open trade Key insights: Net Importers: Belarus, Central Russia Net Exporters: Northwest Russia, Ural, Pamir 24

25 Results Total LCOE (year 2030) area-wide open trade 25

26 Results Total LCOE (year 2030) area-wide open trade 26

27 Results Total LCOE (year 2030) area-wide open trade 27

28 Results Total LCOE (year 2030) area-wide open trade 28

29 Results Components of LCOE area-wide open trade and area-wide desalination gas Area-wide open trade Area-wide open trade desalination gas 29

30 Results Installed Capacities 2030 Scenario Wind PV Hydro RoR Hydro dams Biogas Biomass Waste Geothermal Battery PHS CAES PtG GT [GW] [GW] [GW] [GW] [GW] [GW] [GW] [GW] [GWh] [GWh] [GWh] [GW el ] [GW] Region-wide Country-wide Area-wide Integrated Scenario PV fixed-tilted PV single-axis PV prosumers PV total Battery system Battery prosumers Battery total [GW] [GW] [GW] [GW] [GWh] [GWh] [GWh] Region-wide Country-wide Area-wide Integrated

31 Results Regions Electricity Capacities area-wide open trade Area-wide open trade Area-wide open trade desalination gas 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 31

32 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 Area-wide open trade desalination gas 32

33 Agenda Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary 33

34 Results Net importer region Central Russia 34

35 Results Balancing region Kazakhstan 35

36 Results Net exporter region North-West Russia 36

37 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 37

38 Comparison to other regions Regions LCOE total regionwide LCOE total areawide Integrati on benefit ** storage s* grids interreg ional trade* Curtailm ent PV prosum ers* PV system * Wind * Biomass * hydro* [ /MWh] [ /MWh] [%] [%] [%] [%] [%] [%] [%] [%] [%] Northeast Asia % 10% 26% 6% 14.3% 27.5% 48.2% 7.8% 7.2% Southeast Asia % 8% 3% 3% 7.2% 36.8% 22.0% 22.9% 7.6% Eurasia % <1% 13% 3% 3.8% 9.9% 58.1% 13.0% 15.4% South America % 5% 12% 5% 12.1% 28.0% 10.8% 28.0% 21.1% Europe % 6% 17% 2% 12.3% 14.9% 55.0% 6.6% 9.3% India/ SAARC % 22% 23% 3% 6.2% 43.5% 32.1% 10.9% 5.4% * Integrated scenario, supply share ** annualised costs Key insights: 100% RE is highly competitive least cost for high match of seasonal supply and demand PV share typically around 40% (range 14-50%) hydro and biomass limited the more sectors are integrated flexibility options limit storage to 10% and it will further decrease with heat and mobility sector integration most generation locally within sub-regions (grids 2-26%) 38 sources: see

39 Agenda Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary 39

40 LCOE of alternatives are NO alternative Key insights PV-Wind-Gas is the least cost option nuclear and coal-ccs is too expensive nuclear and coal-ccs are high risk technologies high value added for PV-Wind due to higher capacities needed 40 source: Agora Energiewende, Comparing the Cost of Low-Carbon Technologies: What is the Cheapest option, Berlin

41 Agenda Motivation Methodology and Data Results for the Energy System Results for Hourly Operation Alternatives Summary 41

42 Summary 100% Renewable Energy system is reachable in Eurasia! super grid interconnection decrease average cost of electricity to 53.5 /MWh of the total area from 55.8 /MWh (country-only) and 62.6 /MWh (region-only) integration benefit of gas and desalination is about 18-23% (generation and cost ) due to more efficient usage of storage and flexibility options and it is much higher than for North-East Asia and South America due to continental climate of Eurasia share of PV is rather small and does not exceed 14% low price of electricity from grid restricts the development of prosumers markets hydro dams can be used as a virtual battery for solar and wind electricity balancing, in the same time hydro RoR is not cost competitive to PV and Wind despite an upper limit 50% higher than the current capacity for hydro dams and RoR, in all the considered scenarios PV and wind are more profitable technologies according to the availability of the regions resources 100% RE system is more cost competitive than a nuclear-fossil option! 42

43 Links Bogdanov D. and Breyer Ch., Eurasian Super Grid for 100% Renewable Energy power supply: Generation and storage technologies in the cost optimal mix, ISES Solar World Congress 2015, Daegu, Korea, November 8-12 Д.А. Богданов, К. Брейер, Энергосистема Евразийского региона на базе возобновляемых источников энергии: оптимальная структура генерирующих и аккумулирующих мощностей, Физико-химические проблемы возобновляемой энергетики, 2015 pres, paper Bogdanov D. and Breyer Ch., North-East Asian Super Grid for 100% Renewable Energy power supply: Distributed small-scale and centralized large-scale solar PV as a major energy source, 31 st EU PVSEC, Hamburg, September 14-18; JJAP article Breyer Ch., Gulagi A., Bogdanov D., South-East Asia and the Pacific Rim Super Grid for 100% RE power supply, IEA-PVPS Task 1 Meeting GÜNDER Workshop, Istanbul, October 27 Barbosa L.S.N.S. Bogdanov D., Vainikka P., Breyer Ch., Complementarity of hydro, wind and solar power as a base for a 100% RE energy supply: South America as an example, Rio 15 World Climate & Energy Event, Rio de Janeiro, September 4 43

44 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.

45 Back-up Slides

46 Results Self-Consumption Eurasia super-region area-wide open trade 2030 RES COM IND Electricity price [ /kwh] PV LCOE [ /kwh] Self-consumption PV LCOE [ /kwh] Self-consumption PV and Battery LCOE [ /kwh] Self-consumption LCOE [ /kwh] Benefit [ /kwh] Installed capacities RES COM IND PV [GW] Battery storage [GWh] Generation RES COM IND PV [TWh] Battery storage [TWh] Excess [TWh] Utilization RES COM IND Self-consumption of generated PV electricity [%] Self-coverage market segment [%] Self-coverage operators [%] Source (electricity prices): Gerlach A., Werner Ch., Breyer Ch., Impact of Financing Cost on Global Grid-Parity Dynamics till 2030, 29 th EU PVSEC, Amsterdam, September 22-26

47 Results Total LCOE (year 2030) region-wide open trade 47

48 Results Total LCOE (year 2030) region-wide open trade 48

49 Results Total LCOE (year 2030) region-wide open trade 49

50 Results Total LCOE (year 2030) region-wide open trade 50

51 Results Resource utilization area-wide open trade and area-wide desalination gas Area-wide open trade Area-wide open trade desalination gas 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 51

52 Results Resource utilization area-wide open trade and area-wide desalination gas Area-wide open trade Area-wide open trade desalination gas Hydro dam total capacity 91 GW Hydro dam total capacity 91 GW Hydro RoR total capacity 0.1 GW Hydro RoR total capacity 6.4 GW Key insights: Hydro dam capacities are more valuable for RE system due to flexibility of the generation Hydro Run-of-River is not competitive compared to PV and wind No increase in hydro RoR capacities for the area-wide open trade desalination-gas despite large unused capacities 52

53 Results Storages Storage capacities Throughput of storages Full cycles per year 2030 Scenario Battery PHS A-CAES Gas Battery PHS A-CAES Gas Battery PHS A-CAES Gas [-] [TWh el ] [TWh el ] [TWh el ] [TWh th ] [TWh el ] [TWh el ] [TWh el ] [TWh th ] [-] [-] [-] Region-wide Country-wide Area-wide Integration 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. 53

54 Results Energy flow of the System of region-wide open trade scenario (2030) Key insights: PV generation share does not exceed 14.1%, Wind is the major energy source Throughput of A-CAES storage is 7 times higher than Battery and PHS throughput Throughput of Gas storage is twice higher than A-CAES throughput 54

55 Results Energy flow of the System of area-wide open trade (2030) Key insights: PV generation share does not exceed 8%, Wind is the major energy source A-CAES storages does not play a significant role Gas storage is still feasible 55