Offshore Wind Climatology and Energy Conversion

Abstract

The suitability of the numerical weather prediction model, weather research and forecasting (WRF), is assessed for evaluation of large-scale offshore wind farm sites with a particular focus on conditions in North West India. Prediction accuracy of the wind resource is established for typical operating conditions, intervals of peak wind speed, and over short time-scales during the occurrence of sea breeze. The analysed conditions are employed to evaluate alternative large-scale offshore wind deployment scenarios. Energy yield and economic viability of wind farm sites of up to 2 GW installed capacity are considered with fixed or floating infrastructure. Wind turbine energy yield is dependent on the accurate prediction of wind speed distribution occurrence and this is obtained with a root mean square error (RMSE) within 1.3% for representative time periods within a year. For typical operating intervals, the wind speed occurrence distribution is also shown to be accurate with RMSE of 0.3 to 1% for multiple sites located on flat terrain, at up to 300 km spacing. The mean wind speeds are predicted within 1.3 to 5.1% of error with improvement in prediction accuracy for wind speeds greater than wind turbine rated speed of 11ms-1. The wind speed is predicted within 5.1%, including during days on which sea-breeze events cause rapid change in wind speed and direction over short time intervals. Wind turbine design selection also requires information on the wind profile and turbulence intensity. The wind profile RMSE is within 0.7 to 7.8% over different wind conditions; turbulence intensity is generally underpredicted for a nearshore mast, however across all wind speeds and sites this is within -2 to +1.6%, relative to average measured values in the range 11.4 to 13.4%. The high prediction accuracy of wind speed distribution over multiple locations and of the prediction of wind speed time series, including during short-duration sea-breeze events, provides confidence in the use of WRF for evaluation of offshore wind farm power supply, potentially reducing reliance on extensive field measurements. Deployments of up to 2 GW of wind turbine capacity located along the Gujarat coastline could provide energy supply of between 7.6 to 8.7TWh for sites located at distances between 7 km and 70 km from shore. The site further from shore is in water depths of up to 80 m, greater than the depths suited to typical bed-fixed structures such as monopiles. A techno-economic study of alternative sites and infrastructure indicates that floating systems are expected to have a net project benefit of 409£m. However, sea breeze is found to have a stronger influence on the energy yield of offshore wind farms at the nearshore sites, with a gain in annual energy yield by 5.8% compared to 2% at far offshore locations. Whilst this improves the viability of nearshore locations, the floating offshore wind farm sites remain more profitable and on this basis are recommended over nearshore locations with bottom fixed platforms.

Date of Award	1 Aug 2019
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Peter Stansby (Supervisor) & Tim Stallard (Supervisor)