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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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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