Multi-objective genetic algorithm based innovative wind farm layout optimization method

• DOI: 10.1016/j.enconman.2015.09.011
• Publication Date: 2015-09-16T07:02:49Z
• Authors: Ying Chen; Hua Li; Bang He; Pengcheng Wang; Kai Jin
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 7. Clean energy

Abstract Layout optimization has become one of the critical approaches to increase power output and decrease total cost of a wind farm. Previous researches have applied intelligent algorithms to optimizing the wind farm layout. However, those wind conditions used in most of previous research are simplified and not accurate enough to match the real world wind conditions. In this paper, the authors propose an innovative optimization method based on multi-objective genetic algorithm, and test it with real wind condition and commercial wind turbine parameters. Four case studies are conducted to investigate the number of wind turbines needed in the given wind farm. Different cost models are also considered in the case studies. The results clearly demonstrate that the new method is able to optimize the layout of a given wind farm with real commercial data and wind conditions in both regular and irregular shapes, and achieve a better result by selecting different type and hub height wind turbines.