Long-Term Electricity Scenarios 2050

Transcription

1 Long-Term Electricity Scenarios 2050 Enerday Enertrain Team: Lucas Bückers, Jonas Egerer, Clemens Gerbaulet, Marlen Goerner, Clemens Haftendorn, Christian von Hirschhausen, Wolf-Peter Schill, Claudia Schmidt, Kilian Seitz, Anja Thanheiser Chair of Energy Economics and Public Sector Management

2 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -2-

3 Introduction Aim of Enertrain 2009: - Determination of consistent electricity scenarios for Europe until Including DC imports of Concentrating Solar Power (CSP) - Identification of required data - Testing scenario implications with ELMOD Added value: - Load flow calculation for DC/AC networks - Quantification of welfare implications This pilot-study provides the scenarios of MENAintegration with electricity networks and welfareeconomic analysis -3-

4 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -4-

5 Drivers for Scenario Development Electricity demand Climate policy Fuel prices Market environment Scenario 2050 Volatility Technology strategies Learning curves for generation technologies Identified key parameters -5-

6 Overview of Scenarios for 2050 Climate Policy -30% -80% Electricity Demand x 2.5 x 1 DIRTY LOBBY GREEN POOR DIRTY MÜSLI Scenarios examined -6-

7 Relevant Scenarios for ELMOD Application Installed capacity for 80% reduction target Electricity Demand x 2.5 x 1 LOBBY 45% Fossil (CCS) 30% RES (EU) 25% Nuclear MÜSLI 25% Fossil (CCS) 65% RES (EU) GREEN 30% Fossil (CCS) 35% RES (EU) 35% CSP 10% CSP Super Grid required for MÜSLI and GREEN -7-

8 Power Plant Portfolio 2050 (14 large EU countries) GW MÜSLI GREEN LOBBY Tidal Geothermal CSP Photovoltaic Wind Biomass Pump Hydro CCGT Coal Nuclear CSP dominant in GREEN LOBBY requires less capacity due to higher availability -8-

9 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -9-

10 ELMOD Model of the Western / Central European UCTE network with 2120 nodes and 3243 lines Objective n,t g n d n p(d n ) c(g n ) node, hour generation in n demand in n demand function in n generation costs in n max W q n, t = p( q ) dq ( c( g g ) n, t 0 * n, t n, t n, t ) n, t n, t -10-

11 ELMOD Base Model Simplified UCTE AC grid - One supply and demand node per country - Only cross border lines Additional HVDC overlay grid Additional points of generation for CSP -11-

12 Fossil Fuel Costs [ /GJ] MÜSLI GREEN LOBBY Coal Gas

13 Marginal Generation Costs (2050) [ /MWh] MÜSLI GREEN LOBBY CSP RES (EU) CCS CCGT Nuclear Marginal costs of CCS lower than CCGT Low marginal costs of RES (wind) -13-

14 Selected Set of Cases Wind & Low Medium High PV: availability: availability: availability: Demand: x0.1 x0.2 x0.6 Average: x1.0 BASE Peak: x1.3 PEAK / LOW WIND PEAK / HIGH WIND Stress test: peak demand with low wind & PV Highest grid impact: peak with high wind & PV -14-

15 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -15-

16 Results l GWh Base GREEN Scenario Peak/ low wind High share of CSP CCGT serves as back-up Peak/ high wind Wave/Tidal Geothermal CSP PV Wind Biomass Pump Hydro CCGT CCS -16-

17 Results II GWh Base MÜSLI Scenario Peak/ low wind Peak/ high wind In high wind case increase in demand and no CCS or CCGT required Wave/Tidal Geothermal CSP PV Wind Biomass Pump Hydro CCGT CCS -17-

18 HVDC Utilization of MÜSLI and GREEN DC Connection [GW] MÜSLI GREEN Germany Scandinavia Morocco Spain Tunes Italy Scandinavia Denmark France Spain Germany Austria Turkey Hungary Germany France Germany Hungary Italy Austria Large capacity required in GREEN scenario for CSP -18-

19 Producer Rent Sufficient for CSP and DC Grid? demand Market price CSP and HVDC installation costs not included RES CSP Biomass CCS CCGT -19-

20 Welfare Analysis CSP & HVDC in MÜSLI and GREEN Assumptions: r = 6%, T = 20 years, CSP installation 4000 /kw MÜSLI: Producer rent: CSP installation cost: DC installation cost: Profit for producer: GREEN: Producer rent: CSP installation cost: DC installation cost: 21.0 billion /year 13.8 billion /year 2.2 billion /year 5.0 billion /year billion /year billion /year 11.0 billion /year Profit for producer: billion /year In both scenarios CSP & HVDC is profitable for the producer

21 Welfare Comparison LOBBY vs. GREEN Welfare in GREEN ca. 10% higher Welfare gain 117 billion Euro per year Will it happen? -21-

22 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -22-

23 Institutional Aspects Characteristics of network investments: - Capital intensity - Long amortization periods - Sunk costs Uncertainties - Development of climate, renewable and regulatory policies - Technological uncertainties: e.g. learning curves for HVDC, CSP Coordination problems - Investments into CSP generation and grid expansion - Cooperation of system operators and regulators Local resistance (NIMBY), lengthy authorization procedures Fear of increasing import dependency, MENA country risks -23-

24 The Way Forward Climate and renewable energy policy: - Clear and stable long-term policy 2050 targets - Binding targets and responsibilities - Strategic infrastructure planning Network regulation: allow cost recovery of network expansion Vertical unbundling might reduce incentive problems Promote public acceptance Public funding: - Research & Development - First key projects -24-

25 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -25-

26 Conclusions The electricity system in 2050 will be fundamentally different than today Large infrastructure investments are required CSP & HVDC are economically feasible strategies for a carbon constraint future Removal of barriers and uncertainties required Long investment cycles timely policy measures necessary How about 2150? -26-

27 Agenda 1. Introduction 2. Scenarios for Model 4. Results 5. Institutional Aspects 6. Conclusions 7. Literature -27-

28 References (Selected) Alfen, H.-W. (2000): Privatwirtschaftliche Modelle für eine bedarfsgerechte Straßenverkehrsinfrastruktur; in: Internationales Bückers, L. et al. 2009: Sustainable Energy Networks Economic impacts of an overlaid grid Verkehrswesen, Heft 4/2000, S in Project Work TU Dresden Arrow, K. J. / Lind, R. C. (1970): Uncertainty and the Evaluation of Public Investment Decisions; in: American Economic European Review, S Commission 2005: World Energy Technology Outlook 2050 WETO-H2. Beckers, T. / Hirschhausen, Chr. von (2003): Privatisierung der Bundesautobahnen über Konzessionsmodelle Alternative German Aerospace Center (DLR) 2005: Concentrating Solar Power for the Mediterranean Region. Konzepte, offene Fragen und wirtschaftspolitische Schlussfolgerungen; Arbeitspapier zu einem Vortrag auf den 19. German Verkehrswissenschaftlichen Aerospace Center Tagen (DLR) am : Trans-Mediterranean der TU Dresden; das Interconnection Arbeitspapier kann unter for Concentrating URL: Power. herunter geladen Solar werde German Aerospace Center (DLR) 2007: Numerical Data for Trans-CSP Greenpeace 2008: Energy (r)evolution International Energy Agency 2008: World Energy Outlook. Leimbach, M. et al. 2008: Mitigation costs in a globalized world: climate policy analysis with REMIND-R. LEPII 2006: POLES 5 - Prospective Outlook on long-term energy systems. January Leuthold, F. et al. 2008: ELMOD A Model of the European Electricity Market. Electricity Markets Working Papers WP-EM-00, July Meehl, G.A. et al. 2007: Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Shell 2008: Shell energy scenarios to

29 Thank you very much for your attention! Any questions or comments? Chair of Energy Economics and Public Sector Management

30 Chair of Energy Economics and Public Sector Management

31 Back-up Chair of Energy Economics and Public Sector Management

32 Results III GWh LOBBY Scenario Base Peak Low Peak High Wave/Tidal Geothermal PV Wind Biomass Pump Hydro CCGT CCS Nuclear Little impact of fluctuating renewables -32-

33 Institutional Aspects How to Make it Happen? Specific characteristics of network investments + Uncertainties + Other barriers = Lack of business cases -33-