Predicting the costs of photovoltaic solar modules in 2020 using 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-by-doing 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]  Peter Holmes Kobos,et al.  Technological learning and renewable energy costs: implications for US renewable energy policy , 2004 .

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

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

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

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

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

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

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

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

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

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

[12]  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 .

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

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

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

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

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

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

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

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

[22]  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 .

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

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