Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis. (15th August 2021)

• Record Type: Journal Article
• Authors: Hayes, Liam; Stocks, Matthew; Blakers, Andrew
• Is Part Of: Energy. Volume 229(2021)
• Publication Date: 2021-08-15
• Subjects: ERA5 -- Offshore wind farm -- Wind power modelling -- Reanalysis -- Capacity factor -- Hourly timeseries; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.120603
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Accurate long-term wind speed data is important for understanding the role of offshore wind farms in future energy systems. Meteorological reanalyses, such as ERA5, are relied upon by the wind energy industry and researchers. Being unaffected by onshore topography and surface roughness, the historic generation of offshore wind farms can be accurately predicted using such weather reanalysis. In this work we present a new method for using ERA5 weather data to model long term (>40 year) hourly wind generation for individual offshore wind farms. The model is validated against 57 offshore wind farms in Europe, and reduces the root mean squared error in hourly and daily capacity factor predictions by 10% and 18% respectively when compared to the Renewables Ninja. Further, 40 years (from 1980 to 2019) of ERA5 hourly wind speeds within 200 km of the coast is made easily available for energy system research on our accompanying website (windtlas.xyz). Highlights: Wind speeds from ERA5 reanalysis accurately predict offshore wind farm generation 40 years of hourly wind generation for any offshore location publicly available Hourly wind generation predictions improved by 16%