Optimal setting of TCSCs in power systems using teaching–learning-based optimisation algorithm

被引：0
|
作者：
A. Rezaee Jordehi
机构：
[1] University Putra Malaysia (UPM),Department of Electrical Engineering
来源：
Neural Computing and Applications | 2015年 / 26卷
关键词：
Teaching–learning-based optimisation; FACTS allocation problem; Contingency;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Teaching–learning-based optimisation (TLBO) is an emerging gradient-free optimisation algorithm inspired by interactions between students and teacher in classrooms. TLBO has no control parameter to be tuned by user. This property makes it popular in research community. It has been successfully applied to challenging optimisation problems in different areas. In this study, TLBO is assisted to find optimal setting of thyristor-controlled series compensators in electric power systems. The experiments have been done for both N-1 and N-2 line outage contingencies. The results show that TLBO performs well in solving this problem.
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收藏
页码：1249 / 1256
页数：7
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