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PV Learning Curves: Past and Future Drivers of Cost Reduction

Authors: Friederike Kersten; Görig; P. Wawer; R. Doll; Christian Breyer; A. Kux; D.M. Huljic; +1 Authors

PV Learning Curves: Past and Future Drivers of Cost Reduction

Abstract

Photovoltaic (PV) is one of the fastest growing electricity generation technologies in the world. Average annual growth rates of global PV-installations have reached around 45% for the last 15 years, which triggered a fast and ongoing reduction of production cost in PV industry. The presented work aims at consolidating historical price and cost information, deriving refined learning curves for PV modules and systems, and analysing the main factors of learning. For c-Si modules a valid learning rate of 17% is found based on a meta-analysis of various studies. In early years, even a learning rate of 30% is observed. As an example for thin-film PV, CdTe module cost reduce by 16% as the cumulated production output doubles. Interestingly, efficiency improvements contribute only in second order to the overall cost reduction for both technologies, emphasising the relevance of production excellence and economies of scale. On PV system level, a cost reduction of 14% per doubling of cumulated installed capacity is derived. Finally, a sensitivity analysis reveals that learning rate variations are only of minor influence on the overall global PV market potential.

26th European Photovoltaic Solar Energy Conference and Exhibition; 4697-4702

Keywords

PV Taking Off: Large-Scale Deployment, Markets for Large-scale PV

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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%