Abstract
When technological innovations are implemented in the wind energy sector, one should observe reductions in the production cost of electricity. However, the accuracy of inferring the rate of innovation from production cost reductions is open to challenge when those costs change due to factors not attributable to technological innovation. To control for such factors, this study applies engineering models and derives production cost reduction trends through changes in the technical parameters of wind turbines. The obtained innovation measure is unlikely to be affected by the noninnovative determinants of the production cost as long as the underlying engineering models are accurate. The usefulness of the generated innovation measure is illustrated in the context of learning curve literature.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request (e.g., the spreadsheet for engineering models and derived data series).
Acknowledgments
The research was funded by the SMART City, SMART Region, SMART Community (Grant No. CZ.02.1.01/0.0/0.0/17_048/0007435), supported by the H2020-MSCA-RISE project GEMCLIME-2020 GA. No. 681228, and received institutional support RVO 67985998 from the Czech Academy of Sciences. The author is thankful to Byeongju Jeong for his invaluable comments.
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Information
Published In
Journal of Energy Engineering
Volume 148 • Issue 3 • June 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Mar 17, 2021
Accepted: Jan 13, 2022
Published online: Mar 17, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 17, 2022
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