共 49 条
Particle swarm optimised fuzzy controller for charging-discharging and scheduling of battery energy storage system in MG applications
被引:32
作者:
Faisal, M.
[1
]
Hannan, M. A.
[1
]
Ker, Pin J.
[1
]
Abd Rahman, M. S.
[1
]
Begum, R. A.
[2
]
Mahlia, T. M., I
[3
]
机构:
[1] Univ Tenaga Nas, Dept Elect Power Engn, Kajang 43000, Malaysia
[2] Univ Kebangsaan Malaysia, Inst Climate Change, Bangi 43600, Malaysia
[3] Univ Technol Sydney, Sch Informat Syst & Modelling, Ultimo, NSW 2007, Australia
来源:
关键词:
Battery energy storage;
Optimisation;
charging-discharging;
Fuzzy;
Microgrid;
PSO;
Scheduling;
MODEL-PREDICTIVE CONTROL;
LITHIUM-ION BATTERY;
POWER MANAGEMENT;
RENEWABLE ENERGY;
ALGORITHM;
MICROGRIDS;
OPERATION;
STATE;
UNIT;
D O I:
10.1016/j.egyr.2020.12.007
中图分类号:
TE [石油、天然气工业];
TK [能源与动力工程];
学科分类号:
0807 ;
0820 ;
摘要:
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. (C) 2020 The Authors. Published by Elsevier Ltd.
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页码:215 / 228
页数:14
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