Multi-Objective Bee Swarm Optimization Algorithm with Minimum Manhattan Distance for Passive Power Filter Optimization Problems

Nien-Che Yang and Danish Mehmood
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Nien-Che Yang: Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
Danish Mehmood: Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

Mathematics, 2022, vol. 10, issue 1, 1-20

Abstract: Harmonic distortion in power systems is a significant problem, and it is thus necessary to mitigate critical harmonics. This study proposes an optimal method for designing passive power filters (PPFs) to suppress these harmonics. The design of a PPF involves multi-objective optimization. A multi-objective bee swarm optimization (MOBSO) with Pareto optimality is implemented, and an external archive is used to store the non-dominated solutions obtained. The minimum Manhattan distance strategy was used to select the most balanced solution in the Pareto solution set. A series of case studies are presented to demonstrate the efficiency and superiority of the proposed method. Therefore, the proposed method has a very promising future not only in filter design but also in solving other multi-objective optimization problems.

Keywords: harmonic; passive power filters; optimal design; bee swarm optimization algorithm; Pareto front; minimum Manhattan distance (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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