Wind turbine positioning optimization of wind farm using greedy algorithm

In this paper, the greedy algorithm is used to solve the wind turbine positioning optimization problem. Various models are employed to describe the problem, including the linear wake model, the power-law power curve model with power control mechanisms, Weibull distribution, and the profit function. The incremental calculation method is developed to consider the influence of the adding turbine on other turbines in the wind farm and accelerate the wind power assessment process. The repeated adjustment strategy is used to improve the optimized result. Three cases with simple models and a case with realistic models are used to test the present method. The results show that the greedy algorithm with repeated adjustment can obtain a better result than bionic algorithm and genetic algorithm in less computational time. The proposed greedy algorithm is an effective solution strategy for wind turbine positioning optimization.