What cost for photovoltaic modules in 2020? Lessons from experience curve models

Except in few locations, photovoltaic generated electricity remains considerably more expensive than conventional sources. It is however expected that innovation and learning-bydoing will lead to drastic cuts in production cost in the near future. The goal of this paper is to predict the cost of PV modules out to 2020 using experience curve models, and to draw implications about the cost of PV electricity. Using annual data on photovoltaic module prices, cumulative production, R&D knowledge stock and input prices for silicon and silver over the period 1990 - 2011, we identify a experience curve model which minimizes the difference between predicted and actual module prices. This model predicts a 67% decrease of module price from 2011 to 2020. This rate implies that the cost of PV generated electricity will reach that of conventional electricity by 2020 in the sunniest countries with annual solar irradiation of 2000 kWh/year or more, such as California, Italy, and Spain.

[1]  W.G.J.H.M. van Sark,et al.  Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects , 2011 .

[2]  Haruki Tsuchiya.  PHOTOVOLTAICS COST ANALYSIS BASED ON THE LEARNING CURVE , 1990 .

[3]  F. Ferioli,et al.  Use and limitations of learning curves for energy technology policy: A component-learning hypothesis , 2009 .

[4]  Michael Grubb,et al.  The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project , 2006 .

[5]  Antonio Soria,et al.  Technical change dynamics: evidence from the emerging renewable energy technologies , 2001 .

[6]  Martin Weiss,et al.  Climate change - Scientific assessment and policy analysis. Technological learning in the energy sector , 2008 .

[7]  Jonathan Köhler,et al.  Technological change in energy systems: Learning curves, logistic curves and input–output coefficients , 2007 .

[8]  Maya Papineau,et al.  An economic perspective on experience curves and dynamic economies in renewable energy technologies , 2006 .

[9]  T. Kram,et al.  Endogenous learning and technology clustering: analysis with MARKAL model of the Western European energy system , 2000 .

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

[11]  M. Lieberman.  The learning curve, diffusion, and competitive strategy , 1987 .

[12]  Valentina Bosetti,et al.  The Future Prospect of PV and CSP Solar Technologies: An Expert Elicitation Survey , 2012 .

[13]  Daniele Poponi.  Analysis of diffusion paths for photovoltaic technology based on experience curves , 2003 .

[14]  George D. Cody,et al.  Learning curve approach to projecting cost and performance for photovoltaic technologies , 1997, Optics & Photonics.

[15]  M. Glachant,et al.  Invention and Transfer of Climate Change Mitigation Technologies : A Global Analysis Prepared for the Review of Environmental Economics and Policy , 2010 .

[16]  Wilfried van Sark,et al.  Analysis of the use of experience curves for energy policy purposes: The case of photovoltaic power. Final report of the Photex project , 2004 .

[17]  Robert Fildes,et al.  The practice of econometrics: Classical and contemporary: Ernst R. Berndt, (Addison-Wesley Publishing company, Reading, Mass., 1991), pp. 702, $18.95 , 1992 .

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

[19]  Nick Johnstone,et al.  Invention and Transfer of Climate Change Mitigation Technologies on a Global Scale: A Study Drawing on Patent Data , 2009 .

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

[21]  W.G.J.H.M. van Sark,et al.  Accuracy of progress ratios determined from experience curves: the case of crystalline silicon photovoltaic module technology development , 2008 .

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

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

[24]  Christian Breyer,et al.  Research and Development Investments in PV – a Limiting Factor for a Fast PV Diffusion? , 2010 .

[25]  David A. Belsley,et al.  Regression Analysis and its Application: A Data-Oriented Approach.@@@Applied Linear Regression.@@@Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1981 .

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

[27]  Ruud Smits,et al.  Notions on learning applied to wind turbine development in the Netherlands and Denmark , 2004 .

[28]  C. Granger.  Investigating Causal Relations by Econometric Models and Cross-Spectral Methods , 1969 .

[29]  Gregory F. Nemet,et al.  Interim monitoring of cost dynamics for publicly supported energy technologies , 2009 .

[30]  P. Joskow.  Comparing the Costs of Intermittent and Dispatchable Electricity Generating Technologies , 2011 .

[31]  Socrates Kypreos,et al.  Endogenizing R&D and Market Experience in the "Bottom-Up" Energy-Systems ERIS Model , 2004 .

[32]  S. Kahouli-Brahmi,et al.  Testing for the presence of some features of increasing returns to adoption factors in energy system dynamics: An analysis via the learning curve approach , 2009 .

[33]  Peter Holmes Kobos,et al.  Technological learning and renewable energy costs: implications for US renewable energy policy , 2004 .

[34]  George D. Cody,et al.  A learning curve approach to projecting cost and performance for photovoltaic technologies , 2008 .

[35]  M. Lieberman.  The Learning Curve and Pricing in the Chemical Processing Industries , 1984 .

[36]  C. Granger.  Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[37]  Fatih Birol,et al.  Technical Change Theory and Learning Curves : Patterns of Progress in Electricity Generation Technologies , 2007 .

[38]  Yann Ménière,et al.  Innovation and international technology transfer: The case of the Chinese photovoltaic industry , 2011 .

[39]  Yan Yang,et al.  Theoretical efficiency and asymptotic cost of grid-connected photovoltaic systems , 2009, 2009 IEEE International Symposium on Sustainable Systems and Technology.

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

[41]  Arnulf Grubler,et al.  A Model of Endogenous Technological Change Through Uncertain Returns on Learning (R&D and Investments) , 1997 .

[42]  Andrew Flint.  Learning Spillovers in the PV Cell Industry , 2009 .

[43]  Roberto Zilles,et al.  Comments on experience curves for PV modules , 2002 .

[44]  Harald Gruber.  Learning by Doing and Spillovers: Further Evidence for the Semiconductor Industry , 1998 .

[45]  Tooraj Jamasb,et al.  Technical Change Theory and Learning Curves: Patterns of Progress in Electricity Generation Technologies , 2007 .

[46]  Patrik Söderholm,et al.  Wind Power in Europe: A Simultaneous Innovation–Diffusion Model , 2007 .

[47]  Martin Junginger,et al.  Technological Learning in the Energy Sector , 2008 .

[48]  Joshua M. Pearce,et al.  A Review of Solar Photovoltaic Levelized Cost of Electricity , 2011 .

[49]  Ernst R. Berndt,et al.  The Practice of Econometrics: Classic and Contemporary. , 1992 .

[50]  J. Hausman.  Specification tests in econometrics , 1978 .

[51]  J. Durbin,et al.  Techniques for Testing the Constancy of Regression Relationships Over Time , 1975 .

[52]  Antonio Soria,et al.  Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching , 2000 .

[53]  Patrik Söderholm,et al.  Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies , 2007 .

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

[55]  David Popp,et al.  Entice: Endogenous Technological Change in the Dice Model of Global Warming , 2003 .

[56]  T. Mustelin,et al.  The next wave: protein tyrosine phosphatases enter T cell antigen receptor signalling. , 1999, Cellular signalling.

[57]  Richard M. Swanson,et al.  A vision for crystalline silicon photovoltaics , 2006 .

[58]  Stephan Alberth,et al.  Forecasting technology costs via the experience curve — Myth or magic? , 2008 .