基于猫鼠种群算法的分散式风力发电优化配置

Optimal Configuration for Distributed Wind Generation Based on Cat and Mouse Swarm Algorithm

发展智能电网是能源可持续发展的重要支撑,而以分散式发电的方式利用可再生能源发电是智能电网的一大特点。从经济、技术和环境等因素出发,将人工鱼群算法和猫群算法相结合,提出了一种新型的优化方法——猫鼠种群算法。研究了分散式风力发电的优化配置问题,包括选择分散式风力发电机的位置和确定风力发电机的容量。猫鼠种群算法同鱼群算法一样,具有参数不敏感性,解决了优化算法参数较多带来的困扰。最后本文以IEEE14节点系统为例,验证了算法的有效性和优越性。

Smart grid is an important basis for energy sustainable development. One of important characteristic of smart grid is distribuled renewable power generation. With consideration of economy, technology and environment factors, a new optimal algorithm, cat and mouse swarm algorithm, is presented based on flocking algorithm and cat swarm algorithm. Optimal configuration of distributed wind power generation is studied by using proposed algorithm, including wind turbine location and capacity selection. The proposed algorithm is insensitive to parameters, which is robust during optimization. Simulation resuhs based on IEEE14 node system show the validity and superinrity of the proposed algorithm.