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ORIGINAL RESEARCH article

Front. Electron.

Sec. Power Electronics

Volume 6 - 2025 | doi: 10.3389/felec.2025.1633951

This article is part of the Research TopicEnhancing Power Electronic Converters for Modern Power SystemsView all 6 articles

Overshoot-Tolerant Primary Frequency Control of Battery Energy Storage System for Battery Aging Mitigation

Provisionally accepted
Tingyun  GuTingyun Gu1Yu  WangYu Wang1Yiheng  LiuYiheng Liu2Qihui  FengQihui Feng1Qiao  PengQiao Peng2*
  • 1Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang, China
  • 2Sichuan University, Chengdu, China

The final, formatted version of the article will be published soon.

Battery energy storage systems (BESSs) are required to provide frequency support to the grid in some cases, which increases the charge-discharge cycles of battery and accelerates its aging, especially in primary frequency control (PFC). However, the conventional PFC of BESS mainly focuses on the frequency support performance without adequately considering battery health. This paper proposes an adaptive PFC of BESS for battery aging mitigation, which adopts a novel overshoot-tolerant principle to recover the state of energy (SOE) of battery. Once the frequency support demand aligns with the SOE recovery demand, the BESS responds to the frequency deviation in a reverse way. Then, the battery can be charged or discharged more vigorously, and the SOE of battery can be adequately maintained at an ideal level. A multi-objective online optimization model is proposed to update the optimal PFC coefficient, which is solved by the non-dominated sorting genetic algorithm (NSGA-II). The simulation results verify the proposed method, which can effectively recover the SOE of battery with an improved frequency support performance. Moreover, the case study results also validate that the aging of battery can be mitigated by recovering the SOE.

Keywords: Battery energy storage system, Primary frequency control, battery aging mitigation, overshoot-tolerant, multi-objective optimization

Received: 23 May 2025; Accepted: 03 Sep 2025.

Copyright: © 2025 Gu, Wang, Liu, Feng and Peng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Qiao Peng, Sichuan University, Chengdu, China

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