中国电机工程学报2017，Vol.37Issue(16)：4567-4576,10.DOI:10.13334/j.0258-8013.pcsee.170399
基于支持向量机的电力系统紧急控制实时决策方法
Real-time Emergency Control Decision in Power System Based on Support Vector Machines
摘要
Abstract
Emergency control of power system is an important means to keep system stability and prevent accidents expanding after the failure is eliminated.Compared with the off-line decision-making widely used in the current power grid,the real-time emergency control decision can provide more accurate and effective control measures.But the real-time decision is very demanding for computing speed,and the traditional method is not competent.Based on support vector machines (SVM),a real-time decision making method for emergency control of power system has been studied.The key technology was the use of SVM to dig system stability rules from a large amount of simulation data,so as to obtain the stability constraints in the real-time structure,and thus a large number of simulation searches can shift from the real-time phase to the offline stage.This paper firstly established the optimization model of the emergency control strategy,and the stability constraints in the model were linearized by the sensitivity method.By transforming the classification expression of SVM,the stability margin index can be obtained in real-time,and the sensitivity was solved.Finally,the simulation results in IEEE-39 buses system showed that,the stability index proposed can accurately reflect the stability margin of the system;at the same time the decision method of the proposed stability condition can effectively restore the stability of the system according to different disturbances.关键词
电力系统/紧急控制/实时决策/支持向量机Key words
power system/emergency control/real-time decision/support vector machine (SVM)分类
信息技术与安全科学引用本文复制引用
胡伟,张玮灵,闵勇,陈磊,董昱,余锐,刘柏私,王磊..基于支持向量机的电力系统紧急控制实时决策方法[J].中国电机工程学报,2017,37(16):4567-4576,10.基金项目
国家电网公司科技项目 （）
清华大学电力系统国家重点实验自主课题(SKLD16Z08).Science and Technology Project of State Grid Corporation of China and Science （SKLD16Z08）
Technology Project of State Key Lab of Power System of Tsinghua University (SKLD16Z08). （SKLD16Z08）
