A new approach for wind turbine placement problem using modified differential evolution algorithm

Authors: HÜSEYİN HAKLI

Abstract: Energy use is increasing worldwide with industrialization and advancing technology. Following this increase, renewable energy resources are increasingly preferred to reduce the costs of energy production. Wind energy is preferred as a renewable energy resource because it is clean and safe. Wind turbines are used to meet the demand for wind energy. They are placed close to each other to generate higher amounts of energy. However, the wake effect problem arises in these types of layouts, and this hinders the turbines from producing the desired yield. A modified differential evolution (MDE) algorithm was proposed in this study to solve the placement problem for wind turbines, and employed a binary-real-coded method ? obtained by combining binary coding and real coding. The proposed method contains three different modifications: generation of the initial population, regeneration, and mutation. The effective distribution of the wind turbines on land was achieved with a preliminary operation proposed to generate the initial population. In addition, with the MDE method, population regeneration and elitism were carried out to increase the diversity of population and to preserve the success of the method. Finally, a mutation operation was performed on the individuals to alternate the presence or absence of wind turbines. To investigate the performance of the MDE method in solving the wind turbine placement problem, the method was applied to a study area of 2 x 2 km. The results were compared with those obtained with other methods used in the published literature for the wind turbine placement problem. The most successful and productive placement was achieved using the proposed method, and experimental results showed that the MDE is an efficient and successful tool to solve the wind turbine placement problem.

Keywords: Wind turbine placement, binary-real coding, differential evolution algorithm, optimization

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