The dynamics of solar PV costs and prices as a challenge for technology forecasting
The dynamics of solar PV costs and prices as a challenge for technology forecasting
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DOI：
10.1016/j.rser.2013.05.012
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发表时间：
2013-10
影响因子：
15.9
通讯作者：
C. Candelise;M. Winskel;R. Gross
中科院分区：
文献类型：
--
作者：
C. Candelise;M. Winskel;R. Gross
一个有效的能源技术战略必须在建立一个稳定的长期创新框架与应对技术成本和性能的更直接变化之间取得平衡。在过去的十年中，光伏成本和价格并没有沿着既定的学习曲线稳步前进，而是波动不定，先是上升或平稳，然后迅速下降。本文介绍了，并认为，在模块和系统层面的光伏成本和价格的最近变化的原因，国际趋势和更多的地方具体情况。它发现，模块和系统的成本和价格趋势都反映了多种相互重叠的力量。现有的预测方法--经验曲线和工程评估--在捕捉近期光伏成本和价格趋势背后的关键学习效应方面能力有限：生产规模效应、产业重组和淘汰、国际贸易惯例和国家市场动态。在可预见的未来，这些力量可能仍然是技术学习效果的突出方面，因此需要在能源技术预测中得到改进，更明确的表示。
An effective energy technology strategy has to balance between setting a stable long term framework for innovation, while also responding to more immediate changes in technology cost and performance. Over the last decade, rather than a steady progression along an established learning curve, PV costs and prices have been volatile, with increases or plateaus followed by rapid reductions. The paper describes, and considers the causes of, recent changes in PV costs and prices at module and system level, both international trends and more place-specific contexts. It finds that both module and system costs and price trends have reflected multiple overlapping forces. Established forecasting methods – experience curves and engineering assessments – have limited ability to capture key learning effects behind recent PV cost and price trends: production scale effects, industrial re-organization and shakeouts, international trade practices and national market dynamics. These forces are likely to remain prominent aspect of technology learning effects in the foreseeable future – and so are in need of improved, more explicit representation in energy technology forecasting.