基于新型多目标粒子群算法的电力系统动态无功优化  

Dynamic Reactive Power Optimization of Power System Based on New Multi-objective Particle Swarm Algorithm

作　　者：李璇[1] 李玎[2] 

机构地区：[1]广东电网公司广州供电局变电一部,广东广州510245 [2]广东电网公司电力科学研究院,广东广州510600

出　　处：《广东电力》2009年第12期12-15,共4页Guangdong Electric Power

摘　　要：提出了基于新型多目标粒子群算法的无功优化方法。将控制设备动作次数约束转化为目标函数,并对转化后的多目标优化问题设计了适应度函数,较好地解决了变量离散化与控制设备动作次数限制之间的配合问题。经算例验证,优化后有功网损下降了15.1%,且优化前的环流、变压器过载等问题得到了解决。A rcactive power optimization method based on new multi-objective particle swarm algorithm is presented. In this method, action number constraint of control devices is converted into objective function, and the fitness function for the transformed multi-objective optimization problem is designed, which solves the coordination between discretization of variables and action number restriction of control devices. Case study shows that the active network loss after the optimization decreases by 15. 1% ; such problems as circular current and overload of transformer before the optimization are solved.

关 键 词：动态无功优化 多目标 粒子群算法 动作次数约束 

分 类 号：TM714.3[电气工程—电力系统及自动化]