THE BALTIC SEA REGION STORAGE, GRID EXCHANGE AND FLEXIBLE ELECTRICITY GENERATION FOR THE TRANSITION TO A 100% RENEWABLE ENERGY SYSTEM

Transcription

1 THE BALTIC SEA REGION STORAGE, GRID EXCHANGE AND FLEXIBLE ELECTRICITY GENERATION FOR THE TRANSITION TO A 100% RENEWABLE ENERGY SYSTEM Michael Child, Dmitrii Bogdanov and Christian Breyer Lappeenranta University of Technology (LUT), Finland Neo-Carbon Energy Researchers Seminar, Decemeber 11-13, 2017, Lappeenranta, Finland

2 Highlights A 100% renewable energy system with energy storage solutions can provide reliable, sustainable energy services before 2050 A 100% renewable energy system is lower in cost than the current system based on nuclear and fossil fuels Interconnections between Baltic Sea Region countries can result in further cost savings A well-designed 100% renewable energy system with energy storage solutions can provide power system stability in all 8760 hours of the year 2

3 Agenda Motivation Methodology and Data Results Summary 3

4 Motivation In 2015, the European Commission established the European Energy Union, which highlighted the need for cooperation among member states to create climate friendly energy Several natural regional groupings were identified, including the Baltic Sea Region (BSR) Total estimated installed capacities (net) in 2015 (Area scenario) in the BSR The BSR already shows high shares of RE and high further resource potential The BSR could be amongst the first regions in Europe to achieve 100% RE What could the transition pathway to a 100% RE power system by 2050 look like for the BSR? Total projected installed capacities (net) in 2050 (Area scenario) in the BSR based on 100% RE. 4

5 Agenda Motivation Methodology and Data Results Summary 5

6 Methodology Overview Energy transition pathway from 2015 nuclear and fossil based system to 100% RE by 2050 Transition in 5-year time steps No more than 20% growth in absolute RE installed capacity shares compared to total power generation No new nuclear or fossil based thermal power plants installed after 2015 Least cost RE power plant mix replaces phased out nuclear and fossil power plants Energy system modelled to meet increasing electricity demand for each time step Research Objective: Find the least cost energy transition pathway for the BSR. Left: Aggregated load profile for BSR Right: Estimated electricity demand of BSR from 2015 to 2050 Capacity factor Total Electricity Demand (TWh)

7 Methodology Modelling 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, optimal operation modes for every element of the energy system, least cost energy supply for the given constraints. 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 LUT Energy model, key features linear optimization model hourly temporal resolution 0.45 x 0.45 spatial resolution multi-node approach flexibility and expandability 7

8 Methodology Block diagram of the LUT Energy System Model 8

9 Methodology Scenario assumptions Regions scenario no interconnections between regions Area scenario regions are connected by HVDC 9

10 Methodology - Renewable Resource Potentials Resource Units Norway Denmark Sweden Finland Estonia Latvia Lithuania Total Solar PV GW Onshore wind GW Hydro dams GW Hydro RoR GW Waste TWh Biomass waste TWh Biomass residues TWh Biogas TWh Biomass total TWh Comment on biomass potential: in a full energy system consideration the total biomass potential is also used for heating purposes and for biofuels in the transport sector 10

11 Agenda Motivation Methodology and Data Results Summary 11

12 Results Capacities and generation Regions scenario Area scenario Key insights: RE generation already 60% in 2015 Increasing relevance of electricity Phase out of coal by 2025 and nuclear plants by 2030 Increasing levels of solar PV prosumers and onshore wind Fossil natural gas replaced over time by sustainable biogas, biomethane and SNG Bioenergy to be used in all energy sectors 12

13 Results Interconnections Regions scenario Area scenario Key insights: Current interconnections are approximately 12 GW Simulation results do not show significant need for expansion (+1 GW between Finland and Estonia) 15% of total generation of 587 TWh is traded to other Baltic regions and not consumed in the region of origin Strengthening of interconnections between Estonia, Latvia and Lithuania may also be needed 13

14 Results Storage Regions scenario Area scenario Key insights: Storage becomes increasingly relevant over the transition Output from batteries is most significant PHS maintains a minor role Storage in hydro dams will also maintain its highly relevant role Output from TES, A-CAES and PtG is insignificant in Area scenario Cost of storage higher in Regions scenario 14

15 Results Storage Area scenario Key insights: Batteries and PHS used for short term and diurnal storage Hydro dams and gas storage are used for longer term and seasonal storage PtG, A-CAES and TES play very minor roles in the Area scenario, but are more important in the Regions scenario 15 Michael Child

16 Results Investments and cost Regions scenario Area scenario Key insights: Decreasing LCOE over time from 60 /MWh in 2015 to 45 /MWh in Area scenario and 48 /MWh for Regions scenario in 2050 Decreasing fuel and CO costs over time Lower LCOE in the Area scenario due to lower generation, storage and curtailment costs which compensate for higher transmission cost Other low carbon technologies (nuclear and fossil CCS) are substantially more expensive and risky 16

17 Results CO Regions scenario Area scenario Key insights: Decarbonisation can be rapid in the BSR Faster decarbonisation in Area scenario (by 2030) than Regions scenario (by 2045) Lower CO costs in the Area scenario over the transition 17

18 Agenda Motivation Methodology and Data Results Summary 18

19 Summary The BSR can achieve 100% RE by 2050, with average LCOE of 49 /MWh over the transition By 2050 LCOE is 45 /MWh, and continuously declining from today onwards The BSR can become the first region in the EU to achieve 100% RE almost complete decarbonisation of power sector by 2035 this can serve as a showcase for other member states Battery storage (possibly in the form of vehicle-to-grid connections of electric vehicles) becomes an important source of system flexibility, especially for prosumers Gas infrastructure maintains a strong position in the energy system Imported NG is gradually replaced by domestic biogas, biomethane and SNG Diverse RE generation and interconnections also contribute to system flexibility and lower overall costs Nuclear and fossil fuel plants can be allowed to live out their expected lifetimes No risk of stranded investments unless societal goals change The results present a least cost transition path for the BSR to meet future power demands through a 100% RE system 19

20 @NeoCarbonEnergy Thank you for your attention! NEO-CARBON Energy project is one of the Tekes strategy research openings and the project is carried out in cooperation with Technical Research Centre of Finland VTT Ltd, Lappeenranta University of Technology (LUT) and University of Turku, Finland Futures Research Centre.

21 FURTHER INFORMATION

22 Results 100% RES is possible 2015 Main insights High losses of the current system dimish for 100% RES Fossil-nuclear substituted mainly by wind, solar PV, bioenergy 2050 Regions scenario 22

23 Barriers and Solutions to 100% RES Barriers Technological barriers: Lack of energy storage solutions Inefficiency Possible solutions Lessons to be learned from solutions available in Germany, R&D allocated to storage solutions, electrification of transport and use of EV batteries may offer significant potential for storage Reduce transmission and distribution losses, improve access for small-scale producers, reduce inefficiencies in production as RE generation replaces older nuclear and fossil plants Economical barriers: Competitiveness A need for new kinds of electricity markets and rules Inefficient markets for storage systems Support and high subsidies for conventional energy system Current dominance by large monopolies and oligopolies Solar PV has already reached grid parity in some market segments and will become more competitive on in the future Storage solutions are available at least in Germany a need to import solutions Ideally there should be no support systems in the long run distorting markets Subsidies for harmful emissions of conventional energy production need to be eliminated Feed-in tariff, net metering and privileged grid access in the begining for renewables Creating a fair, low risk investment landscape is essential to ensure future growth 23

24 Barriers and Solutions to 100% RES Barriers Institutional and political barriers: Fossil fuels lobbying Vested interests Path dependency and technological lock-in Incumbent electricity companies Lack of support policy Lack of powerful advocacy coalitions Failure to overcome existing subsidies Misleading energy scenarios (e.g. Nordic Energy Technology Perspectives 2016) Behavioral barriers: General attitudes Psychological resistance Political will Possible solutions No new investments in nuclear or fossil plants Maintain and expand gas infrastructure Only need to switch fuel from NG to biogas A possibility to build a more distributed energy regime New business models arising, but more needed Incentives for wide range of efficiency improvements Some support policy for renewables and storage seems to be needed in the beginning (to balance subsidies for fossil-nuclear) Feed-in tariff law should be based on German model and nontendering models (more players and lower cost of capital) Promote more solar, wind and bioenergy energy advocacy Develop more sustainable and resilient energy scenarios Promote greater public awareness of renewable energy and energy efficiency Provide more information and practical examples of successful installations Maintain strong political will for change, fairness, sustainability and energy independence Further develop education and training programs at universities and vocational schools 24

25 Data Power Plant Capacities Technical and Financial Assumptions Capex variation based on learning curves Least cost power plant capacities based on Cost Efficiency of generation and storage Power to energy ratio of storage Available resource Wind onshore has up to 3691 full load hours (FLH) PV single-axis has up to 1288 FLH WACC is set to 7% for all years Variation in capex from for all power plant components utilised by model. Detailed capex, fixed opex, efficiency and power to energy ratio numbers are presented at end of slide set 25

26 Data Area information Technology Area (km²) Population (Millions) Electricity demand (TWh) Residential electricity price ( /kwh) Norway Denmark Sweden Finland Baltics Commercial electricity price ( /kwh) Norway Denmark Sweden Finland Baltics Industrial electricity price ( /kwh) Norway Denmark Sweden Finland Baltics

27 Data Lower and Upper Capacity Limits Upper and Lower Capacity Limits - Renewables (inflexible) PV optimal tilt PV 1-axis tracking Wind Onshore Wind Offshore Run-of- River Hydro Hydro Dam CSP Region / Unit MW MW MW MW MW MW MW Norway Denmark Sweden Finland Baltic Upper and Lower Capacity Limits - Renewables (flexible) Biogas Biomass Waste Geothermal Ocean Region / Unit MW MW MW MW MW Norway 15-NL 151-NL 67-NL 0-NL 0-NL* Denmark 83-NL 1395-NL 249-NL 0-NL 0-NL* Sweden 46-NL 3788-NL 1440-NL 0-NL 0-NL* Finland 84-NL 2578-NL 1104-NL 0-NL 0-NL* Baltic 7-NL 157-NL 37-NL 0-NL 0-NL* NL No upper limit specified for technologies, but resource availability will limit capacity development * Not utilized for BSR 27

28 Data Lower and Upper Capacity Limits Upper and Lower Capacity Limits Non-renewables Coal Oil Natural gas Nuclear Region MW MW MW MW Norway 0-NL 0-NL 1235-NL 0-NL Denmark 3615-NL 818-NL 2626-NL 0-NL Sweden 492-NL 3229-NL 1183-NL 9470-NL Finland 3497-NL 1652-NL 1789-NL 2752-NL Baltic 0-NL 2899-NL 4361-NL 0-NL Upper and Lower Capacity Limits Storage Pumped hydro storage Adiabatic Compressed Air Energy Storage Batteries Region MWh MWh MWh Norway NL Denmark NL Sweden NL Finland NL Baltic NL NL No upper limit specified 28

29 Cost assumptions Technology Cost category Unit Steam turbine (CSP) 95 % Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 42 % 42 % 42 % 43 % 44 % 44 % 45 % 45 % Water electrolysis Capex /kw_h Opex fixed /kw_h Opex variable /kwh_h Lifetime Years Efficiency % 84% 84% 84% 84% 84% 84% 84% 84% Hot Heat Burner Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 95 % 95 % 95 % 95 % 95 % 95 % 95 % 95 % 29

30 Cost assumptions Technology Cost category Unit CAES Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 70 % 70 % 70 % 70 % 70 % 70 % 70 % 70 % CCGT PP Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 58 % 58 % 58 % 58 % 59 % 60 % 60 % 60 % OCGT PP Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 43 % 43 % 43 % 43 % 43 % 43 % 43 % 43 % 30

31 Cost assumptions Technology Cost category Unit Oil PP Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 38 % 38 % 38 % 38 % 38 % 38 % 38 % 38 % Coal PP Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 39 % 39 % 39 % 39 % 39 % 39 % 39 % 39 % Nuclear PP Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 37 % 37 % 37 % 38 % 38 % 38 % 38 % 38 % MSW PP Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 34 % 34 % 34 % 34 % 34 % 34 % 34 % 34 % 31

32 Cost assumptions Technology Cost category Unit Biomass PP Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 36 % 37 % 40 % 43 % 45 % 47 % 48 % 48 % Methanation Capex /kw_sng Opex fixed /kw_sng Opex variable /kwh_sng Lifetime Years Efficiency % 77 % 77 % 77 % 77 % 77 % 77 % 77 % 77 % 32

33 Cost assumptions Technology Cost category Unit BHKW Biogas Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 33 % 34 % 37 % 40 % 42 % 44 % 44 % 45 % CO direct air capture Concentrated Solar Receiver Capex /t_co*a Opex fixed /t_co*a Opex variable /t_co Lifetime Years Capex /kwth Opex fixed /kwth Lifetime Years

34 Cost assumptions Technology Cost category Unit Biogas Digester Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % Biogas Upgrade Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 98 % 98 % 98 % 98 % 98 % 98 % 98 % 98 % Geothermal PP Capex /kwe Opex fixed /kwe Lifetime Years Efficiency % 24 % 24 % 24 % 24 % 24 % 24 % 24 % 24 % 34

35 Cost assumptions Technology Cost category Unit Solar PV 0-axis Capex /kwe Opex fixed /kwe Lifetime Years Solar PV 1-axis tracking Solar PV Rooftop - Residential Solar PV Rooftop - Commercial Solar PV Rooftop - Industrial Capex /kwe Opex fixed /kwe Lifetime Years Capex /kwe Opex fixed /kwe 20 17,6 15,7 14,2 12,8 11,7 10,7 9,8 Lifetime Years Capex /kwe Opex fixed /kwe 20 17,6 15,7 14,2 12,8 11,7 10,7 9,8 Lifetime Years Capex /kwe Opex fixed /kwe 20 17,6 15,7 14,2 12,8 11,7 10,7 9,8 Lifetime Years

36 Cost assumptions Technology Cost category Unit Wind Onshore Capex /kwe Opex fixed /kwe Lifetime Years Wind Offshore Capex /kwe Opex fixed /kwe Lifetime Years Hydropower Dam water influx Hydropower run-of-the-river Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years Efficiency % 90 % 90 % 90 % 90 % 90 % 90 % 90 % 90 % Capex /kwe Opex fixed /kwe Opex variable /kwhe Lifetime Years

37 Cost assumptions - Storage Technology Cost category Unit Li-ion stationary Capex /kwhe batteries Opex fixed /kwhe Opex variable /kwhe Lifetime Years Efficiency in % 96 % 96 % 96 % 96 % 96 % 96 % 96 % 96 % Efficiency out % 96 % 96 % 96 % 96 % 96 % 96 % 96 % 96 % Pumped Hydro storage Adiabatic Compressed Air Energy Storage Energy/Power h Capex /kwhe Opex fixed /kwhe Opex variable /kwhe Lifetime Years Efficiency in % 92 % 92 % 92 % 92 % 92 % 92 % 92 % 92 % Efficiency out % 92 % 92 % 92 % 92 % 92 % 92 % 92 % 92 % Energy/Power h Capex /kwhe Opex fixed /kwhe Opex variable /kwhe Lifetime Years Efficiency in % 84 % 84 % 84 % 84 % 84 % 84 % 84 % 84 % Efficiency out % 84 % 84 % 84 % 84 % 84 % 84 % 84 % 84 % Self-discharge % 0.1 % 0.1 % 0.1 % 0.1 % 0.1 % 0.1 % 0.1 % 0.1 % Energy/Power h

38 Cost assumptions - Storage Technology Cost category Unit Compressed Air Storage Capex /kwhe Opex fixed /kwhe Lifetime Years Energy/Power h Gas storage Capex /kwhgas Opex fixed /kwhgas Lifetime Years Technology Cost category Unit Methane Storage Capex /kwhgas Opex fixed /kwhgas Lifetime Years Liquid Fuel Storage Capex /kwhth Opex fixed /kwhth Lifetime Years Solid Fuel Storage Capex /kwhth Opex fixed /kwhth Lifetime Years

39 Cost assumptions - Fuels Fuel Unit Crude oil USD/bbl Crude oil /MWh Natural Gas /MWh Biomethane /MWh Coal - Hard /MWh Coal - Lignite /MWh Uranium /MWh Solid waste - Biomass /MWh CO2 /ton Fuel Unit Solid waste - Norway /MWh MSW Denmark /MWh Sweden /MWh Finland /MWh Baltics /MWh Solid residues Norway /MWh Denmark /MWh Sweden /MWh Finland /MWh Baltics /MWh