Cost Dynamics of Clean Energy Technologies

43 Pages Posted: 3 Jun 2021

Date Written: April 1, 2021


The rapid transition to a decarbonized energy economy is widely believed to hinge on the rate of cost improvements for certain clean energy technologies, in particular renewable power and energy storage. This paper adopts the classical learning-by-doing framework of Wright (1936), which predicts cost (price) to fall as a function of the cumulative volume of past deployments. We examine the learning rates for key clean energy system components (e.g., solar photovoltaic modules) and the life-cycle cost of generating clean energy (e.g., wind energy and hydrogen obtained through electrolysis). Our calculations point to signi´Čücant and sustained learning rates, which, in some contexts, are much faster than the traditional 20%learning rate observed in other industries. Finally, we argue that the observed learning rates for individual technologies reinforce each other in advancing the transition to a decarbonized energy economy.

Keywords: learning-by-doing, renewable energy, energy storage, electrolysis, levelized cost of energy

Suggested Citation

Submitter, TRR 266 Accounting for Transparency and Glenk, Gunther and Meier, Rebecca and Reichelstein, Stefan, Cost Dynamics of Clean Energy Technologies (April 1, 2021). TRR 266 Accounting for Transparency Working Paper Series No. 51, Available at SSRN:

TRR 266 Accounting for Transparency Submitter (Contact Author)

University of Paderborn ( email )

Warburger Str. 100
Paderborn, D-33098

Gunther Glenk

University of Mannheim ( email )

Mannheim Institute for Sustainable Energy Studies
Mannheim, 68131

Rebecca Meier

University of Mannheim ( email )

L 7, 3-5
Mannheim, 68161

Stefan Reichelstein

Stanford University ( email )

Stanford, CA 94305
United States

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