Cover Image

Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications

Battery management systems; Battery storage; Charging (batteries); Controllers; Cost reduction; Electric power transmission networks; Electric power utilization; Fuzzy control; Fuzzy logic; Membership functions; Microgrids; Particle swarm optimization (PSO); Scheduling; Secondary batteries; Temperat...

Full description

Saved in:
Bibliographic Details
Main Authors: Faisal M., Hannan M.A., Ker P.J., Rahman M.S.A., Begum R.A., Mahlia T.M.I.
Other Authors: 57215018777
Format: Article
Published: Elsevier Ltd 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-25116
record_format dspace
spelling my.uniten.dspace-251162023-05-29T16:06:51Z Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications Faisal M. Hannan M.A. Ker P.J. Rahman M.S.A. Begum R.A. Mahlia T.M.I. 57215018777 7103014445 37461740800 36609854400 14007780000 56997615100 Battery management systems; Battery storage; Charging (batteries); Controllers; Cost reduction; Electric power transmission networks; Electric power utilization; Fuzzy control; Fuzzy logic; Membership functions; Microgrids; Particle swarm optimization (PSO); Scheduling; Secondary batteries; Temperature control; Battery energy storage systems; Battery temperature; Conventional systems; Distributed sources; Fuzzy logic controllers; Mathematical calculations; Particle swarm optimisation; Scheduling controllers; Electric power system control Aiming at reducing the power consumption and costs of grids, this paper deals with the development of particle swarm optimisation (PSO) based fuzzy logic controller (FLC) for charging�discharging and scheduling of the battery energy storage systems (ESSs) in microgrid (MG) applications. Initially, FLC was developed to control the charging�discharging of the storage system to avoid mathematical calculation of the conventional system. However, to improve the charging�discharging control, the membership function of the FLC is optimised using PSO technique considering the available power, load demand, battery temperature and state of charge (SOC). The scheduling controller is the optimal solution to achieve low-cost uninterrupted reliable power according to the loads. To reduce the grid power demand and consumption costs, an optimal binary PSO is also introduced to schedule the ESS, grid and distributed sources under various load conditions at different times of the day. The obtained results proved that the robustness of the developed PSO based fuzzy control can effectively manage the battery charging�discharging with reducing the significant grid power consumption of 42.26% and the costs of the energy usage by 45.11% which also demonstrates the contribution of the research. � 2020 The Authors Final 2023-05-29T08:06:51Z 2023-05-29T08:06:51Z 2020 Article 10.1016/j.egyr.2020.12.007 2-s2.0-85097742059 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097742059&doi=10.1016%2fj.egyr.2020.12.007&partnerID=40&md5=b173bcf3cdefbf8c6a4d6dba98db9950 https://irepository.uniten.edu.my/handle/123456789/25116 6 215 228 All Open Access, Gold, Green Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Battery management systems; Battery storage; Charging (batteries); Controllers; Cost reduction; Electric power transmission networks; Electric power utilization; Fuzzy control; Fuzzy logic; Membership functions; Microgrids; Particle swarm optimization (PSO); Scheduling; Secondary batteries; Temperature control; Battery energy storage systems; Battery temperature; Conventional systems; Distributed sources; Fuzzy logic controllers; Mathematical calculations; Particle swarm optimisation; Scheduling controllers; Electric power system control
author2 57215018777
author_facet 57215018777
Faisal M.
Hannan M.A.
Ker P.J.
Rahman M.S.A.
Begum R.A.
Mahlia T.M.I.
format Article
author Faisal M.
Hannan M.A.
Ker P.J.
Rahman M.S.A.
Begum R.A.
Mahlia T.M.I.
spellingShingle Faisal M.
Hannan M.A.
Ker P.J.
Rahman M.S.A.
Begum R.A.
Mahlia T.M.I.
Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications
author_sort Faisal M.
title Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications
title_short Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications
title_full Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications
title_fullStr Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications
title_full_unstemmed Particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in MG applications
title_sort particle swarm optimised fuzzy controller for charging�discharging and scheduling of battery energy storage system in mg applications
publisher Elsevier Ltd
publishDate 2023
_version_ 1806425593884966912
score 13.222552

Similar Items