Prescribed-Time Control for DC Microgrids With Battery Energy Storage Systems
Han Wu, Li Chai, Zhen‐Hua Zhu, Yu‐Chu Tian
Abstract
DC microgrids with battery energy storage systems are being widely implemented for integrating renewable energy. The convergence performance of the battery controller is an important index in the evaluation of the microgrids performance. However, the convergence time of existing finite-time control, fixed-time control, and predefined-time control cannot be preset explicitly. Moreover, existing state-of-charge (SoC)-equalization-based accelerating control algorithms will make the batteries suffer excessive voltage and current. To deal with these problems, this article presents a distributed prescribed-time control scheme embedded with a prescribed-time dynamic average consensus (DAC) algorithm for both discharging mode and charging mode. In discharging mode, the droop coefficient is designed such that all batteries keep the same relative SoC variation rate. With the proposed secondary control input, theoretical analysis shows that the voltage regulation and accurate current sharing can be obtained within any physically allowable user-preassigned time, which is independent of any other control parameters and initial states. SoC balancing is also achieved within the preassigned time. All batteries can keep the same relative SoC variation rate, which is more reasonable than simple SoC equalization. In charging mode, an SoC-based virtual resistance and a prescribed-time virtual voltage compensation control are proposed, with which the current sharing and the same relative SoC variation rate of each battery is achieved within the preassigned time. Simulation studies are conducted to demonstrate the effectiveness of the proposed control scheme