Particle swarm optimised fuzzy controller for charging–discharging and scheduling of battery energy storage system in MG applications. (December 2020)

• Record Type: Journal Article
• Authors: Faisal, M.; Hannan, M.A.; Ker, Pin J.; Rahman, M.S.Abd.; Begum, R.A.; Mahlia, T.M.I.
• Is Part Of: Energy reports. Volume 6(2020)Supplement 7
• Page Start: 215
• Page End: 228
• Publication Date: 2020-12
• Subjects: Battery energy storage -- Optimisation -- charging–discharging -- Fuzzy -- Microgrid -- PSO -- Scheduling; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2020.12.007
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: 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.