Learning Rates and Cost Reduction in the Marine Energy Sector

Mr Henry Jeffrey, University of Edinburgh. Since the early 1990s cost reduction and learning rates have attracted significant interest in technology and policy analysis. Learning rates (or experience curves) provide a method of analyzing technical change and policy measures and thus allow progress to be assessed and have hence found a role assessing future technology for the energy sector.

The objective of this paper is to enhance the understanding of, and add clarity to, the potential cost reductions that could be achieved in marine energy in combination with assessing how existing learning rates models fit with this emerging technology. A secondary but nevertheless important objective is the identification of the underpinning causal factors that facilitate and govern future cost reductions, and hence dictate the overall learning investments for this sector. This will have the following benefits:

•           Inform the energy forecasting community

•           Inform the public and private sector investment community

•           Inform policy makers

This work will provide robust, auditable knowledge and information surrounding future costs of marine energy. It is important that this increased clarity is made available as it will better inform the wider policy and investment sector with regard to the potential for future cost reductions. This in turn will allow decisions to be made with an increased clarity of information.

Due the nascent nature of the marine energy sector, there is a scarcity of actual cost and price data to facilitate the formation of trends or themes. As a result, a “judgemental approach” to cost reduction and learning rates has been used in this paper. This approach relies on expert opinion underpinning the marine sector roadmap whilst also engaging and comparing with the existing cost reduction literature. This follows on the recommendations within 2003 European Commission EXTOOL cost reduction study which highlighted an opportunity to use judgmental methodologies and roadmaps in future cost reduction studies.


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