Coupled On-Site Measurement/CFD Based Approach for Wind Resource Assessment and Wind Farm Micro-Siting over Complex Terrain

Abstract

Wind resource assessment and wind farm micro-siting over complex terrain are essential for wind power management and wind farm operation. A coupled approach is presented for wind resource assessment over a complex topography in Changsha, China, and an improved Genetic Algorithm (GA) is introduced for optimization of wind turbines micro-siting. The Computational Fluid Dynamics (CFD) with Realizable k-ϵ turbulence closure is adopted to simulate the atmospheric boundary layer flow over the complex terrain, and the results are validated by the wind tunnel tests. Long-term on-site measurements from a meteorological station are combined with the CFD results to evaluate the wind energy potential over the complex terrain. A semi-analytical approach is proposed for prediction of yearly wind power generation at the turbine site, and the Jensen-Katic model is utilized in consideration of the wake effects. The improved GA is presented based on the wind resource map. The schemes with different grid discretization are studied. The results showed that the proposed approach is effective for wind resource assessment and wind turbines micro-siting.