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基于优化LS-SVM的电力系统实用动态安全域稳定裕度拟合
引用本文:周惟婧,刘天琪. 基于优化LS-SVM的电力系统实用动态安全域稳定裕度拟合[J]. 电气应用, 2007, 26(5): 21-25
作者姓名:周惟婧  刘天琪
作者单位:四川大学电气信息学院,610065;四川大学电气信息学院,610065
基金项目:国家重点基础研究发展计划(973计划) , 自然科技基金重大项目
摘    要:采用最小二乘支持向量机回归模型构造电力系统动态安全域的稳定裕度拟合器,并分别采用粒子群优化算法和多层动态自适应搜索技术选择最小二乘支持向量机的参数,对系统既定故障下运行点的临界切除时间进行在线拟合并计算出稳定裕度的平均相对误差.以EPRI36节点模型为算例进行仿真计算,并将两种参数优化方法与贝叶斯框架理论自动优选方法得到的结果进行比较,仿真结果表明这两种方法能提高拟合的精度,具有一定的实用价值.

关 键 词:动态安全域  稳定裕度  最小二乘支持向量机  粒子群优化算法
修稿时间:2006-09-26

On-Line Imitating Tansient Stability Margin Based on Optimized LS-SVM of Practical Dynamic Security Regions in Power System
Zhou Weijing. On-Line Imitating Tansient Stability Margin Based on Optimized LS-SVM of Practical Dynamic Security Regions in Power System[J]. Electrotechnical Application, 2007, 26(5): 21-25
Authors:Zhou Weijing
Affiliation:Sichuan University
Abstract:This paper uses the regression arithmetic of Least Squares Support Vector Machine (LS SVM ) to built the stability margin imitation machine for imitating the critical cutting time on line and computing its transient stability margin, to same fixed fault. At the same time,it uses the particle swarm algorithm (PSO) and the multi layer adaptive best fitting parameters search algorithm to induct best optimized parameters.It is tests on the EPRI36 bus model of PSASP,and compares the result of the two methods and the Bayesian framework.The result indicates the two method can achieve greater accuracy and is practical in use.
Keywords:dynamic security regions stability margin least support vector machine(LS SVM) particle swarm optimization(PSO)
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