Analysis of large scale distribution network using whale optimization algorithm

Shaik Hussain Vali; Vempalle Rafi; R. Kiranmayi; P. Yamuna; M. Siva Leela; G. V. Nagesh Kumar

Author(s)

Shaik Hussain Vali JNTUA College of Engineering (Autonomous) Pulivendula, YSR Kadapa, India

Vempalle Rafi JNTUA College of Engineering (Autonomous) Pulivendula, YSR Kadapa, India

R. Kiranmayi JNTUA College of Engineering (Autonomous) Ananthapuramu, Ananthapuramu, India

P. Yamuna JNTUA College of Engineering (Autonomous) Ananthapuramu,Ananthapuramu,India

M. Siva Leela JNTUA College of Engineering (Autonomous) Pulivendula, YSR Kadapa, India

G. V. Nagesh Kumar JNTUA College of Engineering (Autonomous) Pulivendula, YSR Kadapa, India

Abstract

In this study, we use a loop matrix to describe the reorganisation of the RDN's formulation. Calculation time is increased when an optimum reorganisation is determined analytically. More network buses means more time to calculate. Therefore, a technique of optimisation is required to determine the best reorganisation of the radial distribution system. The optimum reorganisation aims to reduce network losses to a minimum and the voltage profile is enhanced. Loop matrices are used to describe the re-formulation of the radial distribution system. The analytical technique of identifying optimum reconfiguration involves additional calculation time. The computational complexity grows as the system's bus count rises. Therefore, a search for the best possible radial distribution system reconfiguration necessitates an optimization technique. The ideal reconfiguration focuses mostly on reducing the system's overall loss. The genetic algorithm (GA), particle swarm optimization (PSO), and whale optimization algorithm (WOA) are the optimization methods used in this paper. Two test systems consisting of 119 buses, and 135 buses are used to evaluate the effectiveness of various optimization strategies. The outcomes are then compared with one another.

Publication Details

Page(s) 48-55

DOI DOI not available

Published Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 19, Issue: 1, Year: 2024

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Keywords

Load flow, Losses, whale optimization algorithm (WOA), radial distribution network (RDN), particle swarm technique

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