Resumen
In order to make full use of the potential of wind resources in a specific offshore area, this paper proposes a new method to simultaneously optimize the number, hub height and layout of a wind farm. The wind farm is subdivided by grids, and the intersection points are set as the potential wind turbine positions. The method adopts a genetic algorithm and encodes wind farm parameters into chromosomes in binary form. The length of chromosomes is decided by the number of potential positions and the hub heights to be selected. The optimization process includes selection, crossover, and mutation, while the efficiency of wind farm is set as the optimization objective. The proposed method is validated by three benchmark cases. It has proven to be effective in deciding the number of turbines and improving the efficiency of the wind farm. Another advantage of the proposed method is that it can be widely applied to wind farms of any shape. A case study applying the new method to an irregularly shaped wind farm in Hong Kong is demonstrated. By comparing the results with the original regularly shaped wind farm, the new method can improve power generation by 6.28%. Therefore, the proposed model is a supportive tool for designing the best number, hub heights and positions of wind turbines.