SOC Balancing Control Based on Predictive Power Model Amongst Supercapacitor Packs in MMC With Embedded Energy Storage System

Modular multilevel converter with supercapacitor (SC) packs-based energy storage system (MMC-SESS) can play a role in energy transition and renewable energy consumption. However, SESS's imbalance problem is caused by the inconsistency of its packs, which has a negative effect on the utilization of the MMC-SESS and has become a hot research topic. Confronting this problem, this article proposes a state of charge (SOC) balancing control strategy amongst SC packs based on a discrete time-domain predictive power model in MMC-SESS based medium-voltage direct-current (MVDC). It is a double-loop control to accurately control the charging and discharging power. The outer power control establishes a discrete time-domain predictive power model for the SOC differences. The inner current loop designs a hybrid controller based on the continuous control set-model prediction control (CCS-MPC) and the feedback control strategy to accurately track the dynamic current reference. Simulations in PSCAD/EMTDC have shown that the proposed control can achieve SOC balancing amongst SC packs and improve the dynamic response as well as mitigate the SC pack current ripples.

Automated summary

This article proposes a charge balancing control strategy for a modular multilevel converter with supercapacitor energy storage system based on medium-voltage direct-current. The control strategy accurately controls the charging and discharging power and achieves state of charge balancing among supercapacitor packs. Simulation results show that the proposed control strategy improves dynamic response and reduces current ripples.