Abstract
Technological innovation, production scale, production experience and market demand all affect photovoltaic (PV) cost and module price. Market variables and time lag relationships are introduced into the renewable energy technology learning curve models, with stepwise regression used to identify critical factors in Japan, USA and China. The empirical results for Japan, USA and China show that the affecting PV cost reductions in descending order are technological innovation, production scaling and production experience, so China should encourage technological innovation and facilitate for technological innovation, technology transfer and large-scale production for cost reductions. Since the module price is also sensitive to market demand, sharp increases in demand with supply shortages should be avoided.
Translated title of the contribution | Photovoltaic module price dynamics: Empirical evidences from case studies |
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Original language | Chinese |
Pages (from-to) | 796-801 |
Number of pages | 6 |
Journal | Qinghua Daxue Xuebao/Journal of Tsinghua University |
Volume | 51 |
Issue number | 6 |
Publication status | Published - Jun 2011 |
Externally published | Yes |
Keywords
- Learning by doing
- Photovoltaic (PV)
- Scale economies
- Technological innovation