In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.
结合智能电网的需求和大型工业企业的能量管理现状提出企业级电气化监控和能量管理系统(Enter-prise Electric Energy Control System,E3CS)的设计方案.利用基于嵌入式技术的一体化智能测控和保护装置对广域分布在生产区域的各个用电能耗设备进行信息采集和智能控制;基于电力企业CIM扩展企业级公共信息模型ECIM,采用可伸缩矢量图形SVG格式显示企业电网接线图,实现图模一体化管理的企业数据平台;在掌握了工业企业完整的能量消耗信息后,在企业层面或者区域能量监测中心层面实现系统级的能量分析和优化节能.
