基于改进粒子群算法电力系统多目标无功优化  

Multi-objective Reactive Power Optimization of Power System Based on Improved Particle Swarm Optimization

作　　者：武因培[1] 张绍德[1] 陈刚[1] 王赟[1] 

机构地区：[1]安徽工业大学电气信息学院,安徽马鞍山243002

出　　处：《能源与节能》2013年第1期17-19,31,共4页Energy and Energy Conservation

摘　　要：在传统的电力系统无功优化问题的基础上,建立了同时兼顾电力系统有功网损最小和电压偏移最小的多目标无功优化模型,并且针对多目标优化问题,提出了一种改进的多目标粒子群算法,该算法利用计算非支配排序和拥挤距离方式更新粒子的个体最优值和全局最优值并保留每一次迭代后的一部分精英解集,最终结果在精英集合中找寻所需的Pareto前端;引入变异算子和动态权重算子,增强了寻优能力,降低了结果早熟和陷入局部最小值的可能,最后将该算法应用于IEEE 14节点系统进行测试,结果表明该算法不仅实现了系统经济运行同时也提高了电网的电压稳定,并且为用户提供了多样化的解集,方便用户根据实际情况灵活选择。On the basis of the problem of reactive power optimization, the paper builds a model of multi-objective optimization algorithm that gives consideration to both voltage quality guarantee and power loss minimization .And face to multi-objective optimization algorithm, the paper present a improved optimization algorithm based on Particle Swarm Optimization. The algorithm use the method of calculating non-dominated array and crowding distance to renew individual optimal solution and whole optimal solution and reserve a part of archived external solution after every iteration. The final outcome is Pareto front which is found in the archived external solution. And the paper put in a mutation operator and a weight operator to strengthen the optimization ability and reduce the possibility that results early and caught in local minimum. At last, the paper use the multi-objective optimization algorithm to apply to IEEE 14 Nodal Systems and the result support that not only the optimization algorithm realize power system in economy and improve voltage stability, but also it offers diversity of solution to users and make users more convenient to be flexible to select solution on the basis of practical condition.

关 键 词：电力系统 无功优化 多目标优化 粒子群算法 有功网损 电压偏移 

分 类 号：U665.12[交通运输工程—船舶及航道工程]