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


OSEGI EMMANUEL NDIDI 1*, WOKOMA BIOBELE ALEXANDER 2, OJUKA OTONYE 2, BRUCE-ALLISON SA 2, CHUJOR CORNELIUS CHICHI 2
1. Department of Information Technology, National Open University of Nigeria (NOUN), Lagos, Nigeria
2. Department of Electrical Engineering, Rivers State University Rivers State, Nigeria
* Corresponding author, email: emmaosegi@gmail.com

Issue:

JESR, Number 2, Volume XXVIII

Section:

Issue Nr. 2 - Volume 28(2022)

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.

Keywords:

artificial intelligence, optimization, power systems network, shunt compensation, voltage collapse.

Code [ID]:

JESR202202V28S01A0004 [0005463]

Note:

Full paper:

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