Under Voltage Load Shedding Scheme Using Meta-heuristic Optimization Methods

Abstract

Load shedding has been extensively studied because of multiple power system failure occurrences worldwide. Reliable techniques are required to provide rapid and precise load shedding to avert voltage collapse in power networks. Meta-heuristic optimization approaches are currently the widely developed methods because of their robustness and flexibility in dealing with complex and non-linear systems. These methods include genetic algorithm, fuzzy logic control, particle swarm optimization, artificial neural network, ant colony optimization, big-bang big-crunch optimization, and many others. This study provides an overview of all the meta-heuristic methods implemented for under voltage load shedding in power systems.