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.

中文翻译：

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MG应用中电池储能系统充放电调度的粒子群优化模糊控制器

摘要 为了降低电网的功耗和成本，本文研究了基于粒子群优化（PSO）的模糊逻辑控制器（FLC）的开发，用于微电网中电池储能系统（ESS）的充放电和调度（ MG) 应用程序。最初，开发 FLC 是为了控制存储系统的充放电，以避免传统系统的数学计算。然而，为了改善充放电控制，考虑到可用功率、负载需求、电池温度和荷电状态 (SOC)，使用 PSO 技术优化 FLC 的隶属函数。调度控制器是根据负载实现低成本不间断可靠供电的最佳解决方案。为降低电网电力需求和消耗成本，还引入了最佳二进制 PSO，以在一天中的不同时间在各种负载条件下调度 ESS、电网和分布式电源。获得的结果证明，所开发的基于 PSO 的模糊控制的鲁棒性可以有效地管理电池充放电，显着降低 42.26% 的电网功耗和 45.11% 的能源使用成本，这也证明了研究的贡献.