›› 2015, Vol. 28 ›› Issue (6): 5-.

• 论文 • 上一篇    下一篇

基于细菌觅食算法的含风电场电网无功优化

徐飞飞,简献忠   

  1. (上海理工大学 光电信息与计算机工程学院,上海 200093)
  • 出版日期:2015-06-15 发布日期:2015-06-20
  • 作者简介:徐飞飞(1988—),女,硕士研究生。研究方向:风电无功优化。E-mail:xubella66@163.com。简献忠(1969—),男,博士,教授。研究方向:新能源,嵌入式技术应用。
  • 基金资助:

    国家自然科学基金资助项目(41075019)

Wind Farm Reactive Power Optimization by Bacteria Foraging Algorithm

XU Feifei,JIAN Xianzhong   

  1. (School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
  • Online:2015-06-15 Published:2015-06-20

摘要:

针对风电场并网运行后网络损耗大和收敛性差的问题,提出一种细菌觅食优化算法。在建立含风力发电机组的无功优化数学模型基础上,将细菌觅食优化算法应用到含风电场的无功优化问题中。以IEEE-30节点进行测试算例,分别采用传统算法、粒子群算法和细菌觅食算法优化,得到网损下降率为30.29%、28.70%和36.98%。实验及分析表明,该算法效率高、全局搜索能力强、易跳出局部极值,为含风电场的无功优化提供了一种新方法。

关键词: 风电场, 无功优化, 风力发电机, 细菌觅食算法

Abstract:

For the problems of changing flow distribution and increasing network losses as the wind farm incorporates into the power network,a new algorithm for bacteria foraging optimization is proposed and applied to the reactive power optimization of wind farms by establishing the mathematical model of the reactive power optimization of asynchronous wind generators.Taking IEEE-30 node for example,we use the traditional algorithms,particle swarm optimization algorithm and bacteria foraging optimization algorithm to achieve rates of network loss decline of 30.29%,28.70% and 36.98%,respectively.Experiments and analysis show that the method is efficient,strong in global search capability and easy to be out of local extremes.

Key words: wind farm;reactive power optimization;wind generator;bacteria foraging optimization algorithm

中图分类号: 

  • TP306.1