This paper proposes a hybrid control method based on model predictive control (MPC) and iterative learning control (ILC) for the hybrid energy storage system (HESS) in the application of islanded microgrid with photovoltaic (PV) generation. The hybrid method helps to deal with the sudden change in generation and load power demands. MPC aims to regulate the current of the battery and the supercapacitor (SC) to track the dynamic current references. An improved quadratic programming algorithm is proposed to reduce the iterations in online optimization. To compensate for the steady-state error caused by the power loss in the power electronic devices, a controller based on ILC is designed to correct the dynamic current references of HESS. Simulation results are used to verify the proposed algorithm. Validations using hardware experimental results substantiate the improved performance of the proposed control method in terms of reduced voltage regulations.

中文翻译：

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基于模型预测和迭代学习控制的混合储能系统混合控制方法


本文提出了一种基于模型预测控制（MPC）和迭代学习控制（ILC）的混合储能系统（HESS）在光伏发电孤岛微电网应用中的混合控制方法。混合方法有助于应对发电和负载电力需求的突然变化。 MPC 旨在调节电池和超级电容器 (SC) 的电流以跟踪动态电流参考。提出一种改进的二次规划算法来减少在线优化的迭代次数。为了补偿电力电子装置中功率损耗引起的稳态误差，设计了一种基于ILC的控制器来校正HESS的动态电流基准。仿真结果用于验证所提出的算法。使用硬件实验结果的验证证实了所提出的控制方法在减少电压调节方面的性能改进。