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

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, F...

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Main Authors: M. Faisal, M.A. Hannan, Pin J. Ker, M.S.Abd. Rahman, R.A. Begum, T.M.I. Mahlia
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:Energy Reports
Subjects:
PSO
Online Access:http://www.sciencedirect.com/science/article/pii/S235248472031708X
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spelling doaj-fdcca22046ec47d5903b4de7e36babb02020-12-23T05:02:52ZengElsevierEnergy Reports2352-48472020-12-016215228Particle swarm optimised fuzzy controller for charging–discharging and scheduling of battery energy storage system in MG applicationsM. Faisal0M.A. Hannan1Pin J. Ker2M.S.Abd. Rahman3R.A. Begum4T.M.I. Mahlia5Department of Electrical Power Engineering, Universiti Tenaga Nasional, 43000 Kajang, MalaysiaDepartment of Electrical Power Engineering, Universiti Tenaga Nasional, 43000 Kajang, Malaysia; Corresponding author.Department of Electrical Power Engineering, Universiti Tenaga Nasional, 43000 Kajang, MalaysiaDepartment of Electrical Power Engineering, Universiti Tenaga Nasional, 43000 Kajang, MalaysiaInstitute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, MalaysiaSchool of Information, Systems and Modelling, University of Technology Sydney, Ultimo, NSW 2007, AustraliaAiming 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.http://www.sciencedirect.com/science/article/pii/S235248472031708XBattery energy storageOptimisationcharging–dischargingFuzzyMicrogridPSO
collection DOAJ
language English
format Article
sources DOAJ
author M. Faisal
M.A. Hannan
Pin J. Ker
M.S.Abd. Rahman
R.A. Begum
T.M.I. Mahlia
spellingShingle M. Faisal
M.A. Hannan
Pin J. Ker
M.S.Abd. Rahman
R.A. Begum
T.M.I. Mahlia
Particle swarm optimised fuzzy controller for charging–discharging and scheduling of battery energy storage system in MG applications
Energy Reports
Battery energy storage
Optimisation
charging–discharging
Fuzzy
Microgrid
PSO
author_facet M. Faisal
M.A. Hannan
Pin J. Ker
M.S.Abd. Rahman
R.A. Begum
T.M.I. Mahlia
author_sort M. Faisal
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
series Energy Reports
issn 2352-4847
publishDate 2020-12-01
description 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.
topic Battery energy storage
Optimisation
charging–discharging
Fuzzy
Microgrid
PSO
url http://www.sciencedirect.com/science/article/pii/S235248472031708X
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