SWAMI: A SWARM-INTELLIGENT OPTIMIZATION TECHNIQUE FOR VOLTAGE COLLAPSE MITIGATION

Osegi Emmanuel Ndidi, Wokoma Biobele Alexander, Ojuka Otonye, BRUCE-ALLISON Sa, Chujor Cornelius Chichi
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Abstract

In this paper, a voltage collapse optimization system based on comparative studies of swarm-intelligent techniques is proposed for voltage collapse mitigation in power system network. The approach draws inspiration from the idea of utilizing the intelligent behavior of swarm-based artificial machine intelligence technique coined SWAMI for voltage collapse minimization or prevention through dynamic shunt compensation of overloaded power network buses. Several simulation studies have been conducted considering three very popular and successful SWAMI agents – the PSOM, BCOM and ACOM on an IEEE benchmark power network with promising results. Simulation studies showed that the PSOM SWAMI exhibited the most stable response in terms of voltage profile collapse and recovery from voltage collapse state after voltage sensitivity studies. Safe margins of loading and optimal shunt compensations are determined based on the SWAMI techniques.
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Swami:一种用于电压崩溃缓解的群体智能优化技术
本文提出了一种基于群智能技术对比研究的电网电压崩溃优化系统。该方法的灵感来自于利用基于群体的人工机器智能技术(SWAMI)的智能行为,通过对过载的电网母线进行动态分流补偿来最小化或预防电压崩溃。针对三种非常流行和成功的SWAMI代理——PSOM、BCOM和ACOM,在IEEE基准电网上进行了多次仿真研究,并取得了良好的结果。仿真研究表明,在电压敏感性研究后,PSOM SWAMI在电压分布崩溃和从电压崩溃状态恢复方面表现出最稳定的响应。基于SWAMI技术确定了负载的安全裕度和最优分流补偿。
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