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 paper 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.