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Wind power learning rates: a conceptual review and meta-analysis
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.ORCID iD: 0000-0001-6226-8190
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.ORCID iD: 0000-0003-2264-7043
2012 (English)In: Energy Economics, ISSN 0140-9883, E-ISSN 1873-6181, Vol. 34, no 3, p. 754-761Article in journal (Refereed) Published
Abstract [en]

In energy system models endogenous technological change can be introduced by implement-ting so-called technology learning rates specifying the quantitative relationship between the cumulative experience of a technology and its cost. The objectives of this paper are to: (a) provide a conceptual review of learning curve model specifications; and (b) conduct a meta-analysis of wind power learning rates. This permits an assessment of a number of important specification and data issues that influence these learning rates. The econometric analysis builds on 113 estimates of the learning-by-doing rate presented in 35 studies. The meta-analy-sis indicates that the choice of the geographical domain of learning, and thus the assumed presence of learning spillovers, is an important determinant of wind power learning rates. We also find that the use of extended learning curve concepts, e.g., integrating public R&D effects, appears to result in lower learning rates than those generated by so-called single-factor learning curve studies. Overall the empirical findings suggest that future studies should pay increased attention to the issue of learning and knowledge spillovers in the renewable energy field, as well as to the interaction between technology learning and R&D efforts.

Place, publisher, year, edition, pages
2012. Vol. 34, no 3, p. 754-761
National Category
Economics
Research subject
Economics
Identifiers
URN: urn:nbn:se:ltu:diva-10912DOI: 10.1016/j.eneco.2011.05.007ISI: 000304513500013Scopus ID: 2-s2.0-84859711327Local ID: 9cde72d2-81e5-45a4-ad3e-fc6af8ff079bOAI: oai:DiVA.org:ltu-10912DiVA, id: diva2:983860
Note
Validerad; 2012; 20110525 (ysko)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2022-10-27Bibliographically approved

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Lindman, ÅsaSöderholm, Patrik

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