The effects of mean wind speed uncertainty on project finance debt sizing for offshore wind farms. (15th October 2019) - Mora, Esteve Borràs; Spelling, James; van der Weijde, Adriaan H.; Pavageau, Ellen-Mary
Highlights: Reducing estimated mean wind speed uncertainty does not always lead to better LCOEs. Additional measurement becomes more valuable as the maximum gearing increases. Consolidation of Floating LIDAR technology as the optimal measurement campaign. Abstract: Financing costs for offshore projects depend, among many other variables, on the quality of mean wind speed predictions. Financial institutions determine the amount of debt that can be reasonably supported by the project, based on probabilistic cash flow metrics derived from estimated mean wind speeds. Within the offshore wind industry, it is widely believed that longer wind resource campaigns or more precise wind measurement devices that decrease mean wind speed uncertainty lead to lower LCOE values. This paper shows that this is not always true, while a decrease in mean wind speed uncertainty may result in better financing conditions, it typically requires higher development expenditure. We build a theoretical cost modelling framework, which includes detailed project financing constraints, and then apply this to an industrial case study to analyse project financing of different types of offshore wind farms. We show that developers need to find the right balance between a decrease in financing costs and an increase in development expenditure. For projects limited by the maximum gearing or with an unfavourable trade-off between the development expenditure and the increased P90 annual energy production, more precise resource estimation can result in higher LCOE values. This paper suggests a new way of understanding the effects of wind resource assessment campaigns by integrating project finance constraints into cost calculations and highlighting the importance of detailed cost modelling for optimal design of offshore wind farms.