BANKS CAPACITOR COMPENSATION FOR CRITICAL NODAL DETECTION BY AUGMENTED RED WOLF OPTIMIZATION ALGORITHM

K Lenin

doi:10.29121/granthaalayah.v6.i10.2018.1175

Abstract

In this paper Banks Capacitor Compensation for Critical Nodal Detections by Augmented Red Wolf Optimization Algorithm has been worked out. Projected ERWO algorithm hybridizes the wolf optimization (WO) algorithm with swarm based algorithm called as particle swarm optimization (PSO) algorithm. In the approach each Red wolf has a flag vector, and length is equivalent to the whole sum of numbers which features in the dataset of the wolf optimization (WO). Exploration capability of the projected Red wolf optimization algorithm has been enriched by hybridization of both WO with PSO. Efficiency of the projected Enriched Red wolf optimization (ERWO) is tested in standard IEEE 57 bus test system. Simulation study indicates Enriched Red wolf optimization (ERWO) algorithm performs well in tumbling the actual power losses.

Highlights

Reactive power problem plays major role in improving secure& economic of power system operation & control
In this work Enriched Red wolf optimization (ERWO) algorithm has been implemented to work out the problem
Particle swarm optimization (PSO) [21] has good feature of exploration ability and it has been hybridized with Wolf optimization algorithm (WO) to produce an enriched version called as Enriched Red wolf optimization (ERWO)

Summary

Introduction

Reactive power problem plays major role in improving secure& economic of power system operation & control. A variety of methodologies [1-6] have been implemented to solve the problem, but difficulty found in handling the constraints. Days various types of Evolutionary algorithms implemented to solve problem [7-19]. In this work Enriched Red wolf optimization (ERWO) algorithm has been implemented to work out the problem. Both Exploration & Exploitation has been improved. Particle swarm optimization (PSO) [21] has good feature of exploration ability and it has been hybridized with Wolf optimization algorithm (WO) to produce an enriched version called as Enriched Red wolf optimization (ERWO). In standard IEEE 57 bus test system efficiency of Enriched Red wolf optimization (ERWO) algorithm has been evaluated. Results indicate that Enriched Red wolf optimization (ERWO) algorithm performs well in tumbling the actual power losses

Problem Formulation

Red Wolf Optimization

Particle Swarm Optimization

Simulated Outcomes

Conclusion