Authors: Stine Grenaa Jensen
Addresses: Systems Analysis Department, Risø National Laboratory, Frederiksborgvej 399, DK-4000 Roskilde, Denmark
Abstract: The technological development of renewable energy technologies is affected by several factors such as policy initiatives, market developments, and learning within the industry. A simplified expression describing this development, i.e. cost reduction as result of accumulated experience, is increasingly being incorporated in models to assess long-term development of renewable energy technologies. Most of these applications use learning rates to predict future costs and thereby the potential of renewable energy technologies. This article examines different models on the basis of data from photovoltaic and wind power, such as experience curves and multiple regression models with respect to applicability in historical descriptions, predictions, and policy recommendations.
Keywords: renewable energy; experience curves; technological change; wind power; photovoltaics; regression models; technological innovation.
International Journal of Energy Technology and Policy, 2004 Vol.2 No.4, pp.335 - 353
Available online: 29 Nov 2004 *Full-text access for editors Access for subscribers Purchase this article Comment on this article