WRF Prediction of Operational Wind Farm Data and Influence of Upwind Farms on Power Production

Abstract

Accuracy of the Weather Research and Forecasting (WRF) model is determined for prediction of wind resource and power supply of an operational wind farm located in complex terrain in Baja California and the influence of upwind-farm wakes on energy production is assessed. The WRF model initialized with the North American Regional Reanalysis (NARR) provides time-variation and annual occurrence of wind speed within 12% and 1.4%, using either the Rapid Update Cycle (RUC) or Pleim-Xu (PX) land-surface models. Energy supply is within 5.25% (RUC) and 2% (PX) of SCADA data from a 10 MW wind farm. The wind resource at several sites in the region offers the potential for wind farms with capacity factors in the range 32-34%. This reduces to 29% when wind turbine momentum extraction is modelled and the wakes of these farms extend over 12 km downwind, with greater extent for larger-diameter 5 MW turbines than 2 MW turbines. The farm wakes reduce power output from an operational farm by over 20% for wind speeds below rated speed resulting in 1.3-1.7% reduction in annual energy. This analysis establishes confidence in use of numerical weather prediction tools for wind farm operational data and informs use for wind farm planning.