Due to load shedding, circumvent equipment damage, and possible power outages in the electric power system. The continuity of power supply under the Islanded mode of operation in microgrid creates shrink in the power of the tie-line, and frequency oscillation in the event of small load perturbations. Hence, there needs a sufficient capacity of distributed energy resources, proper power management, and a grid dynamic behavior to satisfy the load demand. Therefore, in this paper, an intelligent predictive feedback fuzzy controller (PFF) together with a conventional proportional–integral–derivative (PID) controller (PFFPID) using hybrid elephant herd virtual inertia (EVI) control optimization algorithm is proposed. The proposed controller is designed to optimize the operation based on considering the uncertainties of the grid situation in terms of weather conditions, energy backup capacity, and load profile. The three inputs provided to PFF are renewable power, battery power, and load power, as a membership function in different forms to find the power variation in terms of voltage, frequency, and current. Then to estimate the gain of each output power, the PID controller is used. The purpose of the EVI algorithm is used as a controller optimization algorithm to tune the PFFPID controller to compensate the load based on generated power to meet the load demand. Finally, the simulation is performed with several existing controllers and the result indicates that the proposed controller is robust with respect to random load perturbations and change in the parameter.

中文翻译：

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孤岛微电网中使用象群虚拟惯性优化控制算法的鲁棒预测反馈FPID控制器

由于减载，避免设备损坏，以及电力系统可能出现的停电。微电网孤岛运行模式下供电的连续性造成联络线功率的收缩，以及在小负载扰动情况下的频率振荡。因此，需要有足够容量的分布式能源、适当的电源管理和电网动态行为来满足负载需求。因此，在本文中，提出了一种智能预测反馈模糊控制器（PFF）以及使用混合象群虚拟惯性（EVI）控制优化算法的传统比例-积分-微分（PID）控制器（PFFPID）。所提出的控制器旨在根据天气条件、能源备用容量和负载分布等电网情况的不确定性来优化运行。提供给 PFF 的三个输入是可再生电源、电池电源和负载电源，作为不同形式的隶属函数，可以找到电压、频率和电流方面的功率变化。然后为了估计每个输出功率的增益，使用 PID 控制器。EVI 算法的目的是用作控制器优化算法来调整 PFFPID 控制器，以根据产生的功率补偿负载以满足负载需求。最后，