Estimating the Power Characteristics of Clusters of Large Offshore Wind Farms

Abstract:

The next phase of offshore wind projects in the UK focuses on the development of very large wind farms clustered within several allocated zones. However, this change in the distribution of wind capacity brings uncertainty for the operational planning of the power system. Firstly, there are concerns that concentrating large amounts of capacity in one area could reduce some of the benefits seen by spatially dispersing the turbines, such as the smoothing of the power generation variability. Secondly, wind farms of the scale planned are likely to influence the boundary layer sufficiently to impact the performance of adjacent farms, therefore the power generation characteristics of the clusters are largely unknown.

The aim of this study is to use the Weather Research and Forecasting (WRF) model to investigate the power output of a cluster of offshore wind farms for a range of extreme events, taking into account the wake effects of the individual turbines and the neighbouring farms. Each wind farm in the cluster is represented as an elevated momentum sink and a source of turbulent kinetic energy using the WRF Wind Farm Parameterization.

The research focuses on the Dogger Bank zone (located in the North Sea approximately 125 km off the East coast of the UK), which could have 7.2 GW of installed capacity across six separate wind farms. For this site, a 33 year reanalysis data set (MERRA, from NASA-GMAO) has been used to identify a series of extreme event case studies. These are characterised by either periods of persistent low (or high) wind speeds, or by rapid changes in power output. The latter could be caused by small changes in the wind speed inducing large changes in power output, very high winds prompting turbine shut down, or a change in the wind direction which shifts the wake effects of the neighbouring farms in the cluster and therefore changes the wind resource available.