| 引用本文: | 俞隽亚,王增平,孙洁,杨国生.基于支路交换—粒子群算法的配电网故障恢复[J].电力系统保护与控制,2014,42(13):95-99.[点击复制] |
| YU Jun-ya,WANG Zeng-ping,SUN Jie,YANG Guo-sheng.Service restoration of distribution network based on the branch exchange-particle swarm algorithm[J].Power System Protection and Control,2014,42(13):95-99[点击复制] |
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| 摘要: |
| 针对基本粒子群算法容易“早熟”的问题，将模拟退火的思想融入惯性权重的动态调整中，使得惯性权重随着迭代次数的增加逐渐减小，防止算法陷入局部最优。同时，采用种群适应度方差判断粒子的相似性，判断出算法“早熟”，则对粒子进行自适应变异，即控制变异数目先大后小，并随机选取粒子重新生成位移。为了提高粒子群算法的搜索速度，将粒子群算法与支路交换法相结合，粒子的位移仅为连接非故障失电区和正常区域的联络开关，对于形成环网的方案，采用支路交换法确定要打开的分段开关。既保证了配电网辐射状运行的要求，又可以使形成的网络网损较低，大大提高了算法的效率。算例表明，基于支路交换—粒子群算法的配电网故障恢复可以实现非故障失电区的快速恢复供电。 |
| 关键词: 配电网 故障恢复 粒子群算法 自适应变异 支路交换法 |
| DOI： |
| 投稿时间：2013-06-24修订日期：2014-03-18 |
| 基金项目:国家高技术研究发展计划（2012AA050208） |
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| Service restoration of distribution network based on the branch exchange-particle swarm algorithm |
| YU Jun-ya,WANG Zeng-ping,SUN Jie,YANG Guo-sheng |
| (State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;Yantai Power Supply Company, Yantai 264000, China;Relay Protection Institute, China Electric Power Research Institute, Beijing 100192, China) |
| Abstract: |
| To solve the premature issue of particle swarm optimization (PSO), this paper introduces the idea of simulated annealing into the dynamic inertia weight adjustment to make the inertia weight decrease with the increase in the number of iterations and avoid the algorithm falling into local optimization. And it uses population fitness variance to judge the particles’ similarity in order to mutate the particle adaptively, i.e. control the mutation number “big then small” and select particles randomly and rebuild displacement. In order to improve the search speed of PSO algorithm, the PSO algorithm and branch exchange algorithm are combined, in which the particle displacement is just the contact switch connecting non-fault power-lossing area and normal area, as for the scheme of forming looped network, the branch exchange algorithm is used to determine the section switch to open. The combination of PSO and branch exchange could ensure the radial operation requirements of distribution grid, and make the network formed by a lower net loss. The example shows that the distribution network fault recovery based on branch exchange-PSO can quickly restore power supply of power failure area. |
| Key words: distribution network service restoration particle swarm optimization adaptive mutation branch-exchange algorithm |
