Energy Technology Learning Through Deployment in Competitive Markets

Abstract

Technology learning as observed in experience and learning curves shows that government deployment programs can be efficient tools for technology-led strategies to manage the risk of climate change. But better theoretical understanding is needed to explain observed learning rates and make reliable extrapolations. A top-down theoretical approach is offered based on cybernetic concepts. The theory explains the clustering of measured learning rates around 20%. It also explains learning rates between 0 and 7% found in some compilations. The theory provides insights into the different roles of government deployment and R&D programs and the need to distinguish between effects of public and private industry R&D. Government R&D programs cannot substitute for deployment programs. But they can provide new technological options that the industry learning systems can turn into radical innovations, which manifest themselves as leaps in cost reduction and in improvements in technical performance.