Interim monitoring of cost dynamics for publicly supported energy technologies

The combination of substantial public funding of nascent energy technologies and recent increases in the costs of those that have been most heavily supported has raised questions about whether policy makers should sustain, alter, enhance, or terminate such programs. This paper uses experience curves for photovoltaics (PV) and wind to (1) estimate ranges of costs for these public programs and (2) introduce new ways of evaluating recent cost dynamics. For both technology cases, the estimated costs of the subsidies required to reach targets are sensitive to the choice of time period on which cost projections are based. The variation in the discounted social cost of subsidies exceeds an order of magnitude. Vigilance is required to avoid the very expensive outcomes contained within these distributions of social costs. Two measures of the significance of recent deviations are introduced. Both indicate that wind costs are within the expected range of prior forecasts but that PV costs are not. The magnitude of the public funds involved in these programs heightens the need for better analytical tools with which to monitor and evaluate cost dynamics.

[1]  J. Sweeney,et al.  Learning-by-Doing and the Optimal Solar Policy in California , 2008 .

[2]  Nebojsa Nakicenovic,et al.  Technological change and the environment , 2002 .

[3]  Erin Baker,et al.  Demand Subsidies Versus R&D: Comparing the Uncertain Impacts of Policy on a Pre-commercial Low-carbon Energy Technology , 2008 .

[4]  Suani Teixeira Coelho,et al.  How adequate policies can push renewables , 2004 .

[5]  Jonathan G. Koomey,et al.  The risk of surprise in energy technology costs , 2007 .

[6]  Andrii Gritsevskyi,et al.  Modeling uncertainty of induced technological change , 2000 .

[7]  S. Messner,et al.  Endogenized technological learning in an energy systems model , 1997 .

[8]  Clas-Otto Wene,et al.  ASSESSING NEW ENERGY TECHNOLOGIES USING AN ENERGY SYSTEM MODEL WITH ENDOGENIZED EXPERIENCE CURVES , 1997 .

[9]  Edward S. Rubin,et al.  Use of experience curves to estimate the future cost of power plants with CO2 capture , 2007 .

[10]  Ian Sue Wing,et al.  Representing induced technological change in models for climate policy analysis , 2006 .

[11]  Peter J. Klenow,et al.  Learning-by-Doing Spillovers in the Semiconductor Industry , 1994, Journal of Political Economy.

[12]  J. Dutton,et al.  Treating Progress Functions as a Managerial Opportunity , 1984 .

[13]  G. Hall,et al.  The experience curve from the economist's perspective , 1985 .

[14]  Ari Rabl,et al.  Prospects for PV: a learning curve analysis , 2003 .

[15]  Wim Turkenburg,et al.  Global experience curves for wind farms , 2005 .

[16]  S. Kahouli-Brahmi Technological learning in energy–environment–economy modelling: A survey , 2008 .

[17]  Niels J. Schenk,et al.  Communicating uncertainty in the IPCC’s greenhouse gas emissions scenarios , 2007 .

[18]  F. Geels Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study , 2002 .

[19]  David Popp,et al.  Entice-Br: The Effects of Backstop Technology R&D on Climate Policy Models , 2004 .

[20]  Gregory F. Nemet,et al.  Beyond the learning curve: factors influencing cost reductions in photovoltaics , 2006 .

[21]  Wim Turkenburg,et al.  Implications of technological learning on the prospects for renewable energy technologies in Europe , 2007 .

[22]  K. Arrow The Economic Implications of Learning by Doing , 1962 .

[23]  Nathan Rosenberg,et al.  Exploring the Black Box: Technology, Economics, and History , 1994 .

[24]  Dejan Kostic,et al.  RSS++ , 2019, Proceedings of the 15th International Conference on Emerging Networking Experiments And Technologies.

[25]  Daniel M Kammen,et al.  What history can teach us about the future costs of U.S. nuclear power. , 2007, Environmental science & technology.

[26]  Dennis Anderson,et al.  Induced Technical Change in Energy and Environmental Modeling: Analytic Approaches and Policy Implications , 2002 .

[27]  María Isabel Blanco The economics of wind energy , 2009 .

[28]  W. Arthur Out-of-equilibrium economics and agent-based modeling , 2006 .

[29]  R. Wiser,et al.  Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007 (Revised) , 2008 .

[30]  Lena Neij,et al.  Outcome indicators for the evaluation of energy policy instruments and technical change , 2006 .

[31]  C. Freeman,et al.  As Time Goes By: From the Industrial Revolutions to the Information Revolution , 2001 .

[32]  A. Alchian Reliability of Progress Curves in Airframe Production , 1963 .

[33]  Bob van der Zwaan,et al.  The learning potential of photovoltaics: implications for energy policy , 2004 .

[34]  W. Nordhaus The "Stern Review" on the Economics of Climate Change , 2006 .

[35]  Chihiro Watanabe,et al.  Photovoltaic deployment strategy in Japan and the USA—an institutional appraisal☆ , 2007 .

[36]  Nathan E. Hultman,et al.  A reactor-level analysis of busbar costs for US nuclear plants, 1970-2005 , 2007 .

[37]  Anny Cazenave,et al.  Recent Climate Observations Compared to Projections , 2007, Science.

[38]  Chihiro Watanabe,et al.  Towards a local learning (innovation) model of solar photovoltaic deployment , 2008 .

[39]  Linda Argote,et al.  Organizational Learning Curves: A Method for Investigating Intra-Plant Transfer of Knowledge Acquired Through Learning by Doing , 1991 .

[40]  Daniel M. Kammen,et al.  The Economics of Energy Market Transformation Programs , 1999 .

[41]  Charles Babbage On the Economy of Machinery and Manufactures: OF THE DIVISION OF LABOUR , 2010 .

[42]  T. P. Wright,et al.  Factors affecting the cost of airplanes , 1936 .

[43]  L. Rapping Learning and World War II Production Functions , 1965 .

[44]  N. Baloff,et al.  The Learning Curve--Some Controversial Issues , 1966 .

[45]  G. Nemet,et al.  *Policy and innovation in low -carbon energy technologies , 2007 .

[46]  Edward S. Rubin,et al.  Learning curves for environmental technology and their importance for climate policy analysis , 2004 .

[47]  C. Wene Experience Curves for Energy Technology Policy , 2000 .

[48]  Erin Baker,et al.  Investment in risky R&D programs in the face of climate uncertainty , 2008 .

[49]  J. Schumpeter,et al.  The Theory of Economic Development , 2017 .

[50]  W.G.J.H.M. van Sark,et al.  Introducing errors in progress ratios determined from experience curves , 2008 .

[51]  Johan Albrecht,et al.  The future role of photovoltaics: A learning curve versus portfolio perspective , 2007 .

[52]  P. Gipe Wind Energy Comes of Age , 1995 .

[53]  Leigh Tesfatsion,et al.  Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics) , 2006 .

[54]  Lena Neij,et al.  Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments , 2008 .

[55]  P. D. Maycock Photovoltaic technology, performance, markets, cost and forecast: 1975-2010 , 1995 .

[56]  William D. Nordhaus,et al.  Modeling Induced Innovation in Climate Change Policy , 2002 .

[57]  Chris Hope,et al.  Climate modelling with endogenous technical change: Stochastic learning and optimal greenhouse gas abatement in the PAGE2002 model , 2007 .

[58]  Michael Grubb,et al.  Induced Technological Change: Exploring its Implications for the Economics of Atmospheric Stabilization: Synthesis Report from the innovation Modeling Comparison Project , 2006 .

[59]  Leigh Tesfatsion,et al.  Agent-Based Computational Economics: Growing Economies From the Bottom Up , 2002, Artificial Life.

[60]  Leo Schrattenholzer,et al.  Learning rates for energy technologies , 2001 .

[61]  Pushpam Kumar Agriculture (Chapter8) in IPCC, 2007: Climate change 2007: Mitigation of Climate Change. Contribution of Working Group III to the Fourth assessment Report of the Intergovernmental Panel on Climate Change , 2007 .

[62]  S. Borenstein The Market Value and Cost of Solar Photovoltaic Electricity Production , 2008 .