Micro-siting of wind turbines is a key technology for wind farm configuration. In this paper, Weibull function is used to describe the probability of wind speed distribution and turbine speed-power curve is employed to estimate turbine power generation. The improved wind and turbine models are formulated into an optimal control framework in terms of minimizing the cost per unit energy of the wind farm, which is solved by a binary-encoded genetic algorithm. Simulation results indicate that the proposed method could provide better performance and represents a more realistic and effective strategy for optimal micro-siting of the wind farm.
['Chunqiu Wan', 'Jun Wang', 'Geng Yang', 'Xiaolan Li', 'Xing Zhang']
Optimal micro-siting of wind turbines by genetic algorithms based on improved wind and turbine models