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Economic analysis of tidal stream turbine arrays: a review

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  • Zoe Goss
  • Daniel Coles
  • Matthew Piggott

Abstract

This tidal stream energy industry has to date been comprised of small demonstrator projects made up of one to a four turbines. However, there are currently plans to expand to commercially sized projects with tens of turbines or more. As the industry moves to large-scale arrays for the first time, there has been a push to develop tools to optimise the array design and help bring down the costs. This review investigates different methods of modelling the economic performance of tidal-stream arrays, for use within these optimisation tools. The different cost reduction pathways are discussed from costs falling as the global installed capacity increases, due to greater experience, improved power curves through larger-diameter higher-rated turbines, to economic efficiencies that can be found by moving to large-scale arrays. A literature review is conducted to establish the most appropriate input values for use in economic models. This includes finding a best case, worst case and typical values for costs and other related parameters. The information collated in this review can provide a useful steering for the many optimisation tools that have been developed, especially when cost information is commercially sensitive and a realistic parameter range is difficult to obtain.

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  • Zoe Goss & Daniel Coles & Matthew Piggott, 2021. "Economic analysis of tidal stream turbine arrays: a review," Papers 2105.04718, arXiv.org.
    • Handle: RePEc:arx:papers:2105.04718
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    1. Goss, Z.L. & Coles, D.S. & Kramer, S.C. & Piggott, M.D., 2021. "Efficient economic optimisation of large-scale tidal stream arrays," Applied Energy, Elsevier, vol. 295(C).
    2. Ross O’Connell & Mitra Kamidelivand & Ioannis Polydoros & Christopher Wright & Paul Bonar & Alison J. Williams & Jimmy Murphy, 2023. "The Integration of Tools for the Techno-Economic Evaluation of Fixed and Floating Tidal Energy Deployment in the Irish Sea," Energies, MDPI, vol. 16(22), pages 1-25, November.

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