A State-of-Charge-Frequency Control Strategy for Grid-Forming Battery Energy Storage Systems in Black Start

As the penetration of intermittent renewable energy sources continues to increase, ensuring reliable power system and frequency stability is of importance. Battery energy storage systems (BESSs) have emerged as an important solution to mitigate these challenges by providing essential grid support services. In this context, a state-of-charge (SOC)-frequency control strategy for grid-forming BESSs is proposed to enhance their role in stabilizing grid frequency and improving overall system performance. In the system, the DC-link capacitor is regulated to maintain the angular frequency through a matching control scheme, emulating the characteristics of the rotor dynamics of a synchronous generator (SG). Thereby, the active power control is implemented in the control of the DC/DC converter to further regulate the grid frequency. More specifically, the relationship between the active power and the frequency is established through the SOC of the battery. In addition, owing to the inevitable presence of differential operators in the control loop, a high-gain observer (HGO) is employed, and the corresponding parameter design of the proposed method is elaborated. The proposed strategy simultaneously achieves frequency regulation and implicit energy management by autonomously balancing power output with available battery capacity, demonstrating a novel dual benefit for sustainable grid operation. To verify the effectiveness of the proposed control strategy, a 0.5-Hz frequency change and a 10% power change are carried out through simulations and also on a hardware-in-the-loop (HIL) platform.

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Publication Details

Journal
Batteries
Published
2025-08-04
DOI
https://doi.org/10.3390/batteries11080296
Citations
1
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
1.21

Funders

Controls
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article

A State-of-Charge-Frequency Control Strategy for Grid-Forming Battery Energy Storage Systems in Black Start

Yongheng Yang, Yunuo Yuan
1 citations
Batteries
Microgrid Control and Optimization
1.21
article

A State-of-Charge-Frequency Control Strategy for Grid-Forming Battery Energy Storage Systems in Black Start

Yongheng Yang, Yunuo Yuan
article en
1 citations

Abstract

As the penetration of intermittent renewable energy sources continues to increase, ensuring reliable power system and frequency stability is of importance. Battery energy storage systems (BESSs) have emerged as an important solution to mitigate these challenges by providing essential grid support services. In this context, a state-of-charge (SOC)-frequency control strategy for grid-forming BESSs is proposed to enhance their role in stabilizing grid frequency and improving overall system performance. In the system, the DC-link capacitor is regulated to maintain the angular frequency through a matching control scheme, emulating the characteristics of the rotor dynamics of a synchronous generator (SG). Thereby, the active power control is implemented in the control of the DC/DC converter to further regulate the grid frequency. More specifically, the relationship between the active power and the frequency is established through the SOC of the battery. In addition, owing to the inevitable presence of differential operators in the control loop, a high-gain observer (HGO) is employed, and the corresponding parameter design of the proposed method is elaborated. The proposed strategy simultaneously achieves frequency regulation and implicit energy management by autonomously balancing power output with available battery capacity, demonstrating a novel dual benefit for sustainable grid operation. To verify the effectiveness of the proposed control strategy, a 0.5-Hz frequency change and a 10% power change are carried out through simulations and also on a hardware-in-the-loop (HIL) platform.

BatteriesVol. 11(8)
Hangzhou Wanxiang Polytechnic (CN), Zhejiang University (CN)
Zhejiang University
Openalex Percentile: Top 18%
Microgrid Control and Optimization
1.21
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