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

Jianzhong Xu, Jin’an Wang, Feng Wang, Junxin Wang, Gen Li*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

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.
Original languageEnglish
JournalIEEE Transactions on Power Delivery
Volume38
Issue number4
Pages (from-to)2641-2649
Number of pages10
ISSN0885-8977
DOIs
Publication statusPublished - 2023

Keywords

  • ;odular multilevel converter (MMC)
  • Supercapacitor energy storage system (SESS)
  • State of Charge (SOC)
  • Predictive power model
  • Continuous control set-model predictive control (CCS-MPC)

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