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Research Article Open access CC BY 4.0

Optimal Placement and Sizing of Capacitors in Radial Distribution Systems: A Two-Stage Method

Sunday Adeleke Salimon, Abiodun Aderemi Baruwa, Saheed Oluwasina Amuda, Hafiz Adesupo Adeleke

Journal of Engineering Research and Reports · pp. 31–43 · Published 2 Dec 2020

10.9734/jerr/2020/v19i217229

Abstract

Optimal allocation of shunt capacitors in the radial distribution networks results in both technical and economic benefits. This paper presents a two-stage method of Loss Sensitivity Factor (LSF) and Cuckoo Search Algorithm (CSA) to find the optimal size and location of shunt capacitors with the objective of minimizing cost due to power loss and reactive power compensation of the distribution networks. The first stage utilizes the LSF to predict the potential candidate buses for shunt capacitor placement thereby reducing the search space of the second stage and avoiding unnecessary repetitive load flow while the second stage uses the CSA to find the size and actual placement of the shunt capacitors satisfying the operating constraints. The applicability of the proposed two stage method is tested on the standard IEEE 33-bus and Ayepe 34-bus Nigerian radial distribution networks of the Ibadan Electricity Distribution Company. After running the algorithm, the simulation results gave percentage real and reactive power loss reduction of 34.28% and 28.94% as compared to the base case for the IEEE 33-bus system while the percentage real and reactive power loss reduction of 22.89% and 21.40% was recorded for the Ayepe 34-bus system. Comparison of the obtained results with other techniques in literatures for the standardized IEEE 33-bus reveals the efficiency of the proposed method as it achieved technical benefits of reduced total power loss, improved voltage profile and bus voltage stability, and the economic benefit of reduced total cost due to electrical power loss and compensation.

Radial distribution system power loss reduction voltage profile voltage stability index loss sensitivity factors cuckoo search algorithm.

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Introduction

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