清洁能源技术的成本动态。

Gunther Glenk, Rebecca Meier, Stefan Reichelstein
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引用次数: 15

摘要

人们普遍认为,全球脱碳进程的速度取决于清洁能源技术,特别是可再生能源和能源储存的成本改善速度。本文采用Wright(1936)的经典边做边学框架,该框架预测成本将随着过去部署的累积量而下降。我们首先研究太阳能光伏组件、风力涡轮机和电解槽的学习曲线。然后,这些估计成为估计产生相应清洁能源(即太阳能、风能和氢气发电)的生命周期成本动态的基础。我们的计算指出了显著且持续的学习曲线,在某些情况下,这预示着成本下降的速度比传统的80%学习曲线要快得多。最后,我们认为,观察到的个别清洁能源技术的学习曲线在推进向脱碳能源经济的过渡中是相互加强的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Cost Dynamics of Clean Energy Technologies.

Cost Dynamics of Clean Energy Technologies.

Cost Dynamics of Clean Energy Technologies.

Cost Dynamics of Clean Energy Technologies.

The pace of the global decarbonization process is widely believed to hinge on the rate of cost improvements for clean energy technologies, in particular renewable power and energy storage. This paper adopts the classical learning-by-doing framework of Wright (1936), which predicts that cost will fall as a function of the cumulative volume of past deployments. We first examine the learning curves for solar photovoltaic modules, wind turbines and electrolyzers. These estimates then become the basis for estimating the dynamics of the life-cycle cost of generating the corresponding clean energy, i.e., electricity from solar and wind power as well as hydrogen. Our calculations point to significant and sustained learning curves, which, in some contexts, predict a much more rapid cost decline than suggested by the traditional 80% learning curve. Finally, we argue that the observed learning curves for individual clean energy technologies reinforce each other in advancing the transition to a decarbonized energy economy.

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