Relating R&D and Investment Policies to CCS Market Diffusion Through Two-Factor Learning
AbstractCarbon capture and storage (CCS) technologies have the potential to play a major role in the stabilization of anthropogenic greenhouse gases. To develop the capture technology from its current early pilot phase towards commercial maturity, significant public and private funding is directed towards R&D projects and pilot power plants. However, we know little about how this funding relates to the economics of CCS power plants and their market diffusion. This paper addresses that question. We initially review past learning effects from both capacity installations and R&D efforts for a similar technology, flue-gas desulfurization, using the concept of two-factor learning, and estimate the learning curve. We apply the obtained learning-by-doing rate of 7.1% and the learning-by-researching rate of 6.6% to CCS in the electricity market model HECTOR, which simulates 19 European countries hourly until 2040, to understand the impact of learning and associated policies on the market diffusion of CCS. Simulation results show that the individual impact of learning is similar for both learning rates, regardless of the CO2 price. We then evaluate the effectiveness of policies subsidizing CCS investment costs (addressing learning-by-doing) and of policies providing R&D grants (addressing learning-by-researching) by relating the policy budget to the realized CCS capacity. We find that policies promoting diffusion through subsidies are, at lower policy cost, about equally effective as policies providing R&D funding. At higher spending levels, diffusion-promoting policies are more effective. Overall, policy effectiveness increases in low CO2 price scenarios, but the CO2 price still remains the key prerequisite for the economic competitiveness of CCS, even with major policy support.
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Bibliographic InfoPaper provided by E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN) in its series FCN Working Papers with number 6/2010.
Length: 33 pages
Date of creation: Jun 2010
Date of revision:
Policy effectiveness; CCS; two-factor learning; electricity market;
Other versions of this item:
- Lohwasser, Richard & Madlener, Reinhard, 2013. "Relating R&D and investment policies to CCS market diffusion through two-factor learning," Energy Policy, Elsevier, vol. 52(C), pages 439-452.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- O30 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - General
- Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-10-30 (All new papers)
- NEP-ENE-2010-10-30 (Energy Economics)
- NEP-INO-2010-10-30 (Innovation)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Harmsen - van Hout, Marjolein J.W. & Herings, P. Jean-Jacques & Dellaert, Benedict G.C., 2010.
"The Structure of Online Consumer Communication Networks,"
FCN Working Papers
3/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
- Harmsen - van Hout, Marjolein J.W. & Herings, P. Jean-Jacques & Dellaert ,Benedict G.C., 2006. "The Structure of Online Consumer Communication Networks," Research Memorandum 028, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- Jonathan Kohler, Michael Grubb, David Popp and Ottmar Edenhofer , 2006. "The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 17-56.
- Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
- Lang, Joachim & Madlener, Reinhard, 2010. "Relevance of Risk Capital and Margining for the Valuation of Power Plants: Cash Requirements for Credit Risk Mitigation," FCN Working Papers 1/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
- Harmsen-van Hout, Marjolein J.W. & Dellaert, Benedict G.C. & Herings, P. Jean-Jacques, 2008.
"Behavorial Effects in Individual Decisions of Network Formation,"
019, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- Harmsen - van Hout, Marjolein J.W. & Dellaert, Benedict G.C. & Herings, P. Jean-Jacques, 2010. "Behavioral Effects in Individual Decisions of Network Formation: Complexity Reduces Payoff Orientation and Social Preferences," FCN Working Papers 5/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
- Stephan Spiecker & Volker Eickholt, 2013. "The Impact Of Carbon Capture And Storage On A Decarbonized German Power Market," EWL Working Papers 1304, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2013.
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