a b s t r a c tWind turbine layout optimization in wind farm is one of the most important technologies to increase the wind power utilization. This paper studies the wind turbine layout optimization with multiple hub heights wind turbines using greedy algorithm. The linear wake model and the particle wake model are used for wake flow calculation over flat terrain and complex terrain, respectively. Three-dimensional greedy algorithm is developed to optimize wind turbine layout with multiple hub heights for minimizing cost per unit power output. The numerical cases over flat terrain and complex terrain are used to validate the effectiveness of the proposed greedy algorithm for the optimization problem. The results reveal that it incurs lower computational costs to obtain better optimized results using the proposed greedy algorithm than the one using genetic algorithm. Compared to the layout with identical hub height wind turbines, the one with multiple hub height wind turbines can increase the total power output and decrease the cost per unit power output remarkably, especially for the wind farm over complex terrain. It is suggested that three-dimensional greedy algorithm is an effective method for more benefits of using wind turbines with multiple hub heights in wind farm design.

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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.

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