Predicting the costs of photovoltaic solar modules in 2020 using experience curve models

被引:94
作者
de la Tour, Arnaud [1 ]
Glachant, Matthieu [1 ]
Meniere, Yann [1 ]
机构
[1] MINES ParisTech, CERNA, F-75006 Paris, France
关键词
Learning curve; Solar photovoltaic energy; Cost prediction;
D O I
10.1016/j.energy.2013.09.037
中图分类号
O414.1 [热力学];
学科分类号
摘要
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. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:341 / 348
页数:8
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