Optimization of wind farm micro-siting for complex terrain using greedy algorithm

Abstract

An optimization approach based on greedy algorithm for optimization of wind farm micro-siting is presented. The key of optimizing wind farm micro-siting is the fast and accurate evaluation of the wake flow interactions of wind turbines. The virtual particle model is employed for wake flow simulation of wind turbines, which makes the present method applicable for non-uniform flow fields on complex terrains. In previous bionic optimization method, within each step of the optimization process, only the power output of the turbine that is being located or relocated is considered. To aim at the overall power output of the wind farm comprehensively, a dependent region technique is introduced to improve the estimation of power output during the optimization procedure. With the technique, the wake flow influences can be reduced more efficiently during the optimization procedure. During the optimization process, the turbine that is being added will avoid being affected other turbines, and avoid affecting other turbine in the meantime. The results from the numerical calculations demonstrate that the present method is effective for wind farm micro-siting on complex terrain, and it produces better solutions in less time than the previous bionic method.