Research on Optimization of Control Strategy for Energy Storage Systems Considering Battery State of Charge

doi:10.12096/j.2096-4528.pgt.260216

Abstract

Abstract:

Objectives Distributed energy storage systems exhibit slow state of charge (SOC) equalization and low current distribution accuracy due to inconsistency in the SOC and capacity among battery cells. To address these issues, a control strategy for energy storage systems that considers SOC for energy storage units with different capacities is proposed. Methods The strategy improves droop control by integrating the SOC difference with the droop coefficient using an inverse tangent nested power function. The variable acceleration factor in the droop coefficient is dynamically adjusted according to the SOC difference to achieve better equalization. Additionally, virtual voltage and DC bus voltage compensation are incorporated to achieve accurate output current distribution while ensuring bus voltage stability. Results The optimized variable acceleration factor reduces the SOC equalization time by approximately 50% compared to the fixed acceleration factor. The output current remains consistent with the capacity ratio without compromising SOC equalization performance. Conclusions This control strategy improves SOC equalization speed and output current distribution accuracy among energy storage units with different capacities.

Key words: distributed energy storage system, microgrid, battery, state of charge, droop control, variable acceleration factor, equalization speed, voltage compensation

CLC Number:

TK 02

Mingqi WANG, Xiangyang XIA, Xiaoyue ZHAO, Ru HUANG, Hualong DENG, Daifei LIU, Yukuan CAI. Research on Optimization of Control Strategy for Energy Storage Systems Considering Battery State of Charge[J]. Power Generation Technology, 2026, 47(2): 395-405.

Figures/Tables 10

Fig. 1 Typical structure of DC microgrid (island mode)

Fig. 2 Equivalent circuit model of energy storage unit

Fig. 3 Variation curve of droop coefficient during discharge process

Fig. 4 SOC droop control structure of energy storage unit 1

Fig. 5 Block diagram of overall control of distributed energy storage system

Fig. 6 Simulated waveforms at p=85

Fig. 7 Waveform of optimized variable acceleration factor

Fig. 8 Simulated waveforms with optimized variable acceleration factor

Tab. 1 Comparison of simulation results for acceleration factors before and after optimization

指标	固定加速因子85	优化后变加速因子
响应时间/s	49.56	51.85
SOC均衡时间/s	>100.00	52.66
收敛时间/s	>100.00	52.66

Fig. 9 Simulated waveforms of energy storage units with different capacities

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