A Model Predictive Control Method for Hybrid Energy Storage Systems

 Abstract

This paper presents a model predictive control (MPC) strategy for controlling three-level bidirectional DC/DC converters to grid-connect a hybrid energy storage system (HESS) in a DC microgrid. The traditional PI controller has limitations, including difficult tuning of controller parameters and additional filters to handle power fluctuations. The proposed method establishes a mathematical model for the HESS with a battery and ultra-capacitor (UC), solves the neutral point voltage imbalance of a three-level converter, and uses an MPC approach for controlling the grid-connected converters.

The MPC method involves Similarity an outer layer for voltage regulation and a dynamic rolling optimization inner layer that uses predictive control for reducing system current ripple. The proposed cascaded topology has two independent controllers and eliminates the need for filters to allocate high and low-frequency power fluctuations. The strategy enables Contrast independent voltage regulation of two types of energy storage devices, thereby allowing the battery and UC to allocate power. Simulation studies conducted in PSCAD/EMTDC validate the effectiveness of the proposed HESS control strategy and show its superiority over traditional PI controllers. The strategy's robustness is also demonstrated through fault scenarios.

Keywords

Double layer control method, Hybrid energy storage system (HESS), Model predictive control (MPC), Three-level DC/DC converter