4.6 Article

Global sensitivity analysis for offshore wind cost modelling

期刊

WIND ENERGY
卷 24, 期 9, 页码 974-990

出版社

WILEY
DOI: 10.1002/we.2612

关键词

decision making under uncertainty; global sensitivity analysis; offshore wind; offshore wind cost modelling

资金

  1. EDF Energy R&D UK at the Industrial Doctoral Centre for Offshore Renewable Energy (IDCORE), a consortium of the University of Exeter
  2. EDF Energy R&D UK at the Industrial Doctoral Centre for Offshore Renewable Energy (IDCORE), a consortium of the University of Edinburgh
  3. EDF Energy R&D UK at the Industrial Doctoral Centre for Offshore Renewable Energy (IDCORE), a consortium of the University of Strathclyde
  4. Energy Technologies Institute
  5. Research Councils Energy Programme [EP/J500847/1]
  6. UK Engineering and Physical Sciences Research Council [EP/P001173/1]

向作者/读者索取更多资源

The costs of offshore wind are decreasing rapidly, and there is a need to better understand the key drivers behind these cost reductions. This study uses an industry-leading offshore wind cost modelling tool and applies state-of-art global sensitivity analysis methods.
The costs of offshore wind are decreasing rapidly. However, there is a need to better understand the key drivers behind these cost reductions. New environmental regulations, economic policies, technological advancements and financing structures have resulted in a set of relationships that need to be considered in order to define risks and profitability for the next generation of offshore wind farms. We use an industry-leading offshore wind cost modelling tool which integrates site characteristics, technology specificities and financial modelling expertise and apply state-of-art global sensitivity analysis methods for different classes of offshore wind farms, ranking the contribution of around 150 input parameters that influence the cost of offshore wind development. We show that the top 5 parameters when building an offshore wind investment business case are the wind speed, target equity rate of return, turbine costs, drilling costs and debt service coverage ratio. The contribution of this paper can help guide additional efforts towards reducing the uncertainty of those key parameters to decrease costs and provide a framework to choose global sensitivity analysis techniques for offshore wind techno-economic models.

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