A Multi-Objective Approach for Optimal Sizing and Placement of Distributed Generators and Distribution Static Compensators in a Distribution Network Using the Black Widow Optimization Algorithm

Rameez Shaikh (), Alex Stojcevski, Mehdi Seyedmahmoudian and Jaideep Chandran
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Rameez Shaikh: School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Alex Stojcevski: School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Mehdi Seyedmahmoudian: School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Jaideep Chandran: School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne 3122, Australia

Sustainability, 2024, vol. 16, issue 11, 1-27

Abstract: This paper presents a new optimization technique for the locations and sizes of Distributed Generators (DGs) and distribution static compensators (DSTATCOMs) in a radial system of a distribution network based on a multi-objective approach. It uses black widow optimization to improve voltage profile and power loss reduction. The black widow optimization simulates the mating behaviour of black widow spiders. The optimum size and placement of DGs and DSTATCOMs are deemed to be decision variables that are defined by using black widow optimization. The proposed technique is implemented in selected IEEE bus systems to evaluate its performance. The simulation results indicate reduced power losses and voltage profile enhancement as sizes and locations of integrated DGs and DSTATCOMs are adjusted based on optimization. The number of DGs and DSTATCOMs required to achieve the objectives is reduced. Furthermore, the results of the black widow algorithm are compared to existing techniques in the literature.

Keywords: radial distribution network; distribution STATCOM; DGs; power losses; voltage profile; optimal sizing and placement; black widow optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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