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Taking the photovoltaic (PV)-hybrid energy storage system (HESS) composed of the distributed PV power generation and the distributed energy storage as the research object, under the scenario of smoothing PV power fluctuation, a dual-regulating feedback optimization control strategy of the PV-HESS based on double Kalman filters (KFs) and model predictive control (MPC) is proposed. The first Kalman filter (KF1) is used to realize the effective decomposition of the PV power, the MPC is used to optimize the output and the state of charge (SOC) of the HESS, and the output of the HESS is optimized by the second Kalman filter (KF2) to realize the energy distribution between the energy storage battery and supercapacitors. The optimized output of the HESS is fed back to the KF1 to realize the closed-loop optimization of the entire PV-HESS. The effectiveness and correctness of the proposed optimization control method are verified by simulating the actual operation data of a certain PV-HESS station in China. The simulation results show that the service life of the HESS can be extended by the dual feedback regulating control, and the overall economics of the PV-HESS can be improved.

Dual-Regulating Feedback Optimization Control of Distributed Energy Storage System in Power Smoothing Scenariox Based on KF-MPC