JCMPS

A Hybrid Learning Algorithm for Optimal Reactive Power Dispatch under Unbalanced Conditions

Abstract

: In the power system, optimal reactive power dispatch problem is very challenging optimization problem. Various researches have solved the issues related to optimal reactive power dispatch by minimizing the transmission loss or by optimizing the bus voltage. These researches were immune to voltage fluctuations. The main intention of this paper is to develop a novel approach to lessen the voltage deviation and power loss in optimal reactive power dispatch under unbalanced conditions. This minimization of voltage deviation and power loss were accomplished using a hybrid optimization algorithm referred to as WOA+FF that hybridizes the concept of Whale Optimization Algorithm (WOA) and Firefly algorithm (FF). The proposed WOA+FF operated on the control variables like the voltage and transformer tap settings as well as load reactance with the intention of achieving optimum results. The IEEE 14 and the IEEE 39 benchmark bus systems are the two IEEE benchmark test bus systems that are used to evaluate the entire experiment. Finally, the proposed WOA+FF model is compared with the existing models like Genetic Algorithm (GA), FF, WOA, and Particle Swarm Optimization (PSO) to exhibit the enhancement in the performance of ORPD operation

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