The lazy greedy algorithm for power optimization of wind turbine positioning on complex terrain

Wind farm micro-siting is to determine the optimal positions of wind turbines within the wind farm, with the target of maximizing total power output or profit. This paper studies the performance of the lazy greedy algorithm on optimization of wind turbine positions above complex terrain. Instead of the traditional linear models, computational fluid dynamics and virtual particle wake flow model are employed in the present study for a more accurate evaluation of wind energy distribution and wind power output of wind farm on complex terrain. The validity of the submodular property used by the lazy greedy algorithm is discussed for the wind farm micro-siting optimization problem. By conducting the numerical tests, results demonstrate that the combination of the lazy greedy algorithm and the virtual particle wake model is effective in optimizing wind turbine positioning on complex terrain, for it produces better solution in less time comparing to the previous bionic method.