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

Nien-Che Yang, Danish Mehmood and Kai-You Lai
Additional contact information
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
Kai-You Lai: Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

Mathematics, 2021, vol. 9, issue 24, 1-19

Abstract: Passive power filters (PPFs) are most effective in mitigating harmonic pollution from power systems; however, the design of PPFs involves several objectives, which makes them a complex multiple-objective optimization problem. This study proposes a method to achieve an optimal design of PPFs. We have developed a new multi-objective optimization method based on an artificial bee colony (ABC) algorithm with a minimum Manhattan distance. Four different types of PPFs, namely, single-tuned, second-order damped, third-order damped, and C-type damped order filters, and their characteristics were considered in this study. A series of case studies have been presented to prove the efficiency and better performance of the proposed method over previous well-known algorithms.

Keywords: artificial bee colony algorithm; harmonic; Pareto front; passive power filters; minimum Manhattan distance (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/24/3187/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/24/3187/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:24:p:3187-:d:699589

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().