Evolved intelligent clustered bee colony for voltage stability prediction on power transmission system

被引:0
作者
Z. J. Lim
M. W. Mustafa
机构
[1] Universiti Teknologi Malaysia,Faculty of Electrical Engineering
来源
Soft Computing | 2016年 / 20卷
关键词
Voltage stability; Artificial neural network; Artificial bee colony; Particle swarm optimization; Steepest descend; Fast Voltage Stability Index; Prediction; Classification;
D O I
暂无
中图分类号
学科分类号
摘要
Very often, voltage instability causes millions of money to cater with the negative effects it gave to the people; therefore, it is very important that prior to this worst situation, some manual or automatic recovery system had to be turn on to minimize or totally avoid the entire situation. But these recovery systems will not be turn on if there is no good indication or alarm that controls or informs. In this paper, evolved intelligent clustered artificial bee colony (EICBC) is introduced to predict the voltage stability condition of the IEEE 30-bus test system. Fast Voltage Stability Index is utilized as an indicator to measure the distance of the power system network to the voltage collapse point when the reactive load is varied slowly as reactive load gives the most impact on the stability of the system. EICBC is able to converge faster to its best solution while maintaining the stability of the prediction system by avoiding local minima convergence. The results also show that the proposed algorithm is superior in the prediction accuracy and can be used to categorize the conditions of the network for the ease of identification.
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页码:3215 / 3230
页数:15
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