摘要
针对智能配电网的电能质量监测系统构建成本较高的问题,对通过已知监测数据获得未安装电能质量监测装置(PQM)的系统节点信息的状态估计进行了研究,构建了一种基于状态估计和PQM的电能质量监测系统,提出了一种基于状态估计和多种群改进遗传算法的电能质量监测点优化配置方法,以较少的监测装置实现了对配电网的全面监测,达成了系统性能和经济成本的优化,优化后的电能质量监测系统能对各监测点的全局信息进行再加工,从而帮助电力管理部门尽快查明事件原因、明确责任、排除故障。在两种不同拓扑结构的IEEE配电网络中进行了仿真应用。研究结果表明,该算法能有效地实现配电网的电能质量监测点的优化配置,降低监测系统的构建成本。
Aiming at the high cost problem of power quality monitoring system in distribution network, a state estimation method was re- searched which is used to estimate the monitoring data of uninstalled nodes by known information of power quality monitoring （ PQM ）. The power quality monitoring system was constructed based on state estimation and PQM. An optimal allocation method based on the state estima- tion and the improved genetic algorithm of multiple populations was proposed, with fewer monitoring device for the comprehensive monitoring of the distribution network. The optimization of system performance and finance was achieved. Global information of the monitoring stations was processed by the optimal monitoring system, to help the administrative departments to find out the reason as soon as possible, clear the responsibility and solve faults. The proposed algorithm was applied in two different topologies of IEEE distribution network. The results indi- cate that the proposed algorithm can effectively achieve the optimal allocation of power quality monitoring in the distribution network, and it can reduce the costs of the power quality monitoring system.
出处
《机电工程》
CAS
2016年第3期331-335,共5页
Journal of Mechanical & Electrical Engineering
基金
国家自然科学基金资助项目(51207139)
浙江省教育厅科研项目(Y201431752)
浙江工业大学校级自然科学基金资助项目(1401103025408)
关键词
电能质量
监测点
优化配置
状态估计
遗传算法
power quality
monitoring station
optimal allocation
state estimation
genetic algorithm
