Assessing the Impact of Spatial Variability and Wake Effects on Power Prediction for NJ Offshore Wind Energy Area

Offshore wind energy is a promising new technology with the potential to overhaul the energy production market in the US. New Jersey is currently planning to develop an 1100 MW offshore wind farm and triple its renewable energy in the next decade. Existing simulation models for predicting the power output of turbines with changing meteorological environments focus on the performance of single turbines and ignore the spatial variability and turbine interaction within the designated wind energy area (WEA). For this reason, it is desired to determine the spatial variability within WEA and simulate this variability in wind models to ensure accurate power predictions. Here, we present a study using Weather Research and Forecasting (WRF) to characterize the spatial wind variability and employ a turbine wake interaction model to quantify the power production reduction due to wake interference in the wind farm. This analysis is achieved by comparing hourly wind speeds at turbine hub-height over the period of one year. Data was obtained from the Rutgers University WRF model at several hundred points within the offshore WEA, to perform a statistical analysis of deviation through empirical orthogonal functions. Further testing utilized NREL's software for wake modeling, FLORIS, to simulate turbine interactions using the wind data. Sample wind farm configurations of 25 turbines were tested, with turbines spaced at 5x and 10x the turbine rotor diameter, to observe the interactions between turbines and their effects on overall power output. Results from the spatial analysis suggest a correlation between the distance from the shore and wind speed, indicating that there is significant variability in the power output based on the physical location of turbines. Three representative locations from the WEA were then selected to simulate the different wind farms using model data in FLORIS. It was found that wake effects in this simulation could lead to a 5 percent drop in the power generation capacity of the entire farm, compared to a farm ignoring wake interactions. Both the wake effects and physical location of turbines will have a significant effect on power output. Overall, accurate modeling is imperative to the feasibility of the planned wind farm, and continuing research needs to be done to support this and future offshore wind projects.