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| Secondary Frequency Modulation Control Strategy for Battery Energy Storage Based on Dynamic Participation Factor and Adaptive Model Predictive Control |
| Zhu Zhenshan1,2, Weng Kailiang1, Ouyang Haitao1 |
1. College of Electrical Engineering and Automation Fuzhou University Fuzhou 350108 China;
2. Fujian Province University Engineering Research Center of Smart Distribution Grid Equipment Fuzhou 350108 China |
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Abstract Battery energy storage, as an advanced power device with bidirectional charging and discharging capabilities, fast response speed, and high regulation precision, exhibits strong frequency regulation potential. However, existing studies on the participation of energy storage in secondary frequency regulation lack flexibility in designing the frequency regulation responsibility allocation strategy between energy storage and thermal power units. Consequently, they fail to fully leverage the advantages of energy storage and thermal power units under complex load fluctuation scenarios. Moreover, the conventional methods face conflicts between meeting system frequency regulation demands and ensuring the state of charge (SOC) recovery of energy storage. To address this issue, this paper proposes a secondary frequency regulation strategy that integrates dynamic participation factors and adaptive model predictive control (MPC) while considering SOC recovery.
Firstly, based on the sensitivity principle, the relationship between the energy storage participation factor and system frequency deviation under the area control error (ACE) mode is established. A hierarchical decision-making mechanism is then designed, incorporating sensitivity, frequency deviation, and load fluctuations. A fuzzy control approach is employed to dynamically adjust the energy storage participation factor based on the load condition, optimizing the frequency regulation responsibility allocation between energy storage and thermal power units. This approach effectively exploits the rapid response capability of energy storage and the sustained regulation ability of thermal power units. On this basis, since directly using the dynamic frequency regulation responsibility signal as the energy storage power command is suboptimal, it is instead formulated as the optimization objective of an MPC controller. The MPC framework then iteratively computes the optimal power output of energy storage in real time, thereby improving the system's frequency regulation performance. Furthermore, an adaptive MPC-based energy storage regulation and SOC recovery strategy is proposed, incorporating a SOC recovery term into the MPC objective function. By segmenting the ACE signal and SOC state, the weight of this term is adaptively adjusted across different operating regions, effectively mitigating the conflict between frequency regulation and SOC recovery while enhancing the bidirectional frequency regulation capability of energy storage across all operating conditions.
Simulation results demonstrate that under step load disturbances, the proposed method reduces the maximum frequency deviation to -0.209 7 Hz, achieving a 13.88% and 8.07% improvement compared to two conventional energy storage frequency regulation methods. Additionally, the frequency nadir rate is reduced to 0.252 6 Hz/s, with respective improvements of 23.22% and 32.44% compared to two conventional methods. Under continuous load disturbances, the root mean square value of frequency deviation of the proposed method is reduced by 48.84%, 40.46%, and 22.32% compared to three benchmark methods. In the frequency regulation process, the integral of absolute frequency variation of the proposed method remains minimum compared with the three benchmark methods. Moreover, in extreme scenarios where the initial SOC is 0.12 or 0.88, the proposed MPC adaptive partitioning method with adjustable weights for SOC recovery ensures effective frequency regulation while simultaneously achieving significant improvements in SOC recovery. The root mean square value of SOC deviation is reduced to 2.644×10-1 and 2.686×10-1, representing reductions of 32.03% and 30.16% compared to method that disregard SOC recovery, and reductions of 13.11% and 13.55% compared to method that use fixed-weight strategies.
The simulation analysis leads to the following conclusions: The dynamic participation factor and adaptive model predictive control strategy can distinguish the frequency regulation participation of thermal power units and energy storage at different stages of secondary frequency regulation. This approach enhances system frequency regulation performance while guiding the SOC of energy storage back to the ideal operating range, ensuring its long-term stable operation.
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Received: 28 October 2024
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[1] 李翠萍, 司文博, 李军徽, 等. 基于集合经验模态分解和多目标遗传算法的火-多储系统调频功率双层优化[J]. 电工技术学报, 2024, 39(7): 2017-2032.
Li Cuiping, Si Wengbo, Li Junhui, et al.Two-layer optimization of frequency modulated power of thermal generation and multi-storage system based on ensemble empirical mode decomposition and multi-objective genetic algorithm[J]. Transactions of China Electrotechnical Society, 2024, 39(7): 2017-2032.
[2] 张怡静, 李智, 时艳强, 等. 基于储能惯量支撑的受端电网频率优化控制方法[J]. 电工技术学报, 2024, 39(11): 3556-3568.
Zhang Yijing, Li Zhi, Shi Yanqiang, et al.Optimal frequency control method of receiving power grid based on energy storage inertia support[J]. Transac-tions of China Electrotechnical Society, 2024, 39(11): 3556-3568.
[3] 肖家杰, 李培强, 毛志宇, 等. 基于双层协调控制的电池储能参与电网二次调频策略[J]. 电力自动化设备, 2024, 44(8): 9-17.
Xiao Jiajie, Li Peiqiang, Mao Zhiyu, et al.Strategy of battery energy storage participating in power grid secondary frequency regulation based on two-layer coordinated control[J]. Electric Power Automation Equipment, 2024, 44(8): 9-17.
[4] 梁继业, 袁至, 王维庆, 等. 基于电池储能系统的综合自适应一次调频策略[J]. 电工技术学报, 2025, 40(7): 2322-2334.
Liang Jiye, Yuan Zhi, Wang Weiqing.Comprehensive adaptive primary frequency control strategy based on battery energy storage system[J]. Transactions of China Electrotechnical Society, 2025, 40(7): 2322-2334.
[5] 毛志宇, 李培强, 肖家杰, 等. 面向风功率波动平抑的电池储能双层协调控制策略[J]. 中国电机工程学报, 2024, 44(16): 6494-6507.
Mao Zhiyu, Li Peiqiang, Xiao Jiajie, et al.Coordinated two-layer control strategy of battery energy storage for wind power fluctuate mitigation[J]. Proceedings of the CSEE, 2024, 44(16): 6494-6507.
[6] Yang Dejian, Li Jun, Jin Zhaoyang, et al.Sequential frequency regulation strategy for DFIG and battery energy storage system considering artificial deadbands[J]. International Journal of Electrical Power & Energy Systems, 2024, 155: 109503.
[7] 黎静华, 敖国进, 宋诚鑫, 等. 超级电容参与风电调频的动态响应优化策略[J]. 电力系统自动化, 2024, 48(17): 46-55.
Li Jinghua, Ao Guojin, Song Chengxin, et al.Optimal dynamic response strategy for supercapacitor parti-cipating in wind power frequency regulation[J]. Automation of Electric Power Systems, 2024, 48(17): 46-55.
[8] Ma Qianli, Wei Wei, Wu Lei, et al.Life-aware operation of battery energy storage in frequency regulation[J]. IEEE Transactions on Sustainable Energy, 2023, 14(3): 1725-1736.
[9] 杨德健, 王鑫, 严干贵, 等. 计及调频死区的柔性风储联合频率控制策略[J]. 电工技术学报, 2023, 38(17): 4646-4656.
Yang Dejian, Wang Xin, Yan Gangui, et al.Flexible frequency regulation scheme of DFIG embed battery energy storage system considering deadbands[J]. Transactions of China Electrotechnical Society, 2023, 38(17): 4646-4656.
[10] 李志军, 王硕, 张家安, 等. 基于变论域模糊逻辑的互联电力系统负荷频率控制[J]. 电力系统保护与控制, 2021, 49(16): 151-160.
Li Zhijun, Wang Shuo, Zhang Jiaan, et al.Variable universe fuzzy logic-based load frequency control in an interconnected power system[J]. Power System Protection and Control, 2021, 49(16): 151-160.
[11] Yin Linfei, Wu Yunzhi.Mode-decomposition memory reinforcement network strategy for smart generation control in multi-area power systems containing renew-able energy[J]. Applied Energy, 2022, 307: 118266.
[12] 王育飞, 程伟, 薛花, 等. 基于串级PI-(1+PD)算法的含飞轮储能互联电网AGC控制器设计[J]. 电力系统保护与控制, 2023, 51(14): 127-138.
Wang Yufei, Cheng Wei, Xue Hua, et al.Controller design of an AGC based on a cascade PI-(1+PD) algorithm for an interconnected power grid with flywheel energy storage[J]. Power System Protection and Control, 2023, 51(14): 127-138.
[13] Wang Ping, Chen Xi, Zhang Yunning, et al.Fractional-order load frequency control of an interconnected power system with a hydrogen energy-storage unit[J]. Fractal and Fractional, 2024, 8(3): 126.
[14] 林莉, 林雨露, 谭惠丹, 等. 计及SOC自恢复的混合储能平抑风电功率波动控制[J]. 电工技术学报, 2024, 39(3): 658-671.
Lin Li, Lin Yulu, Tan Huidan, et al.Hybrid energy storage control with SOC self-recovery to smooth out wind power fluctuations[J]. Transactions of China Electrotechnical Society, 2024, 39(3): 658-671.
[15] He Junqiang, Shi Changli, Wei Tongzhen, et al.Stochastic model predictive control of hybrid energy storage for improving AGC performance of thermal generators[J]. IEEE Transactions on Smart Grid, 2022, 13(1): 393-405.
[16] Huang Chongxin, Yang Manting, Ge Hui, et al.DMPC-based load frequency control of multi-area power systems with heterogeneous energy storage system considering SOC consensus[J]. Electric Power Systems Research, 2024, 228: 110064.
[17] Meng Gaojun, Chang Qingqing, Sun Yukun, et al.Energy storage auxiliary frequency modulation control strategy considering ACE and SOC of energy storage[J]. IEEE Access, 2021, 9: 26271-26277.
[18] 崔红芬, 杨波, 蒋叶, 等. 基于模糊控制和SOC自恢复储能参与二次调频控制策略[J]. 电力系统保护与控制, 2019, 47(22): 89-97.
Cui Hongfen, Yang Bo, Jiang Ye, et al.Strategy based on fuzzy control and self adaptive modification of SOC involved in secondary frequency regulation with battery energy storage[J]. Power System Protection and Control, 2019, 47(22): 89-97.
[19] Guo Menglei, Zheng Jianyong, Mei Fei, et al.Double-layer AGC frequency regulation control method considering operating economic cost and energy storage SOC consistency[J]. International Journal of Electrical Power & Energy Systems, 2023, 145: 108704.
[20] 严干贵, 王铭岐, 段双明, 等. 考虑荷电状态恢复的储能一次调频控制策略[J]. 电力系统自动化, 2022, 46(21): 52-61.
Yan Gangui, Wang Mingqi, Duan Shuangming, et al.Primary frequency regulation control strategy of energy storage considering state of charge recovery[J]. Automation of Electric Power Systems, 2022, 46(21): 52-61.
[21] He Li, Tan Zhuangxi, Li Yong, et al.A coordinated consensus control strategy for distributed battery energy storages considering different frequency control demands[J]. IEEE Transactions on Sustainable Energy, 2024, 15(1): 304-315.
[22] 李欣然, 黄际元, 陈远扬, 等. 基于灵敏度分析的储能电池参与二次调频控制策略[J]. 电工技术学报, 2017, 32(12): 224-233.
Li Xinran, Huang Jiyuan, Chen Yuanyang, et al.Battery energy storage control strategy in secondary frequency regulation considering its action moment and depth[J]. Transactions of China Electrotechnical Society, 2017, 32(12): 224-233.
[23] 李若, 李欣然, 谭庄熙, 等. 考虑储能电池参与二次调频的综合控制策略[J]. 电力系统自动化, 2018, 42(8): 74-82.
Li Ruo, Li Xinran, Tan Zhuangxi, et al.Integrated control strategy considering energy storage battery participating in secondary frequency regulation[J]. Automation of Electric Power Systems, 2018, 42(8): 74-82.
[24] Cheng Yunzhi, Tabrizi M, Sahni M, et al.Dynamic available AGC based approach for enhancing utility scale energy storage performance[J]. IEEE Transactions on Smart Grid, 2014, 5(2): 1070-1078.
[25] 张仕鹏, 李培强, 张亦君, 等.基于变滤波时间常数和模糊控制的复合储能二次调频策略[J/OL]. 上海交通大学学报, 2024: 1-26[2024-06-27]. https://doi. org/10.16183/j.cnki.jsjtu.2023.516.
Zhang Shipeng, Li Peiqiang, Zhang Yijun, et al.Secondary frequency modulation strategy of composite energy storage based on variable filter time constant and fuzzy control[J/OL]. Journal of Shanghai Jiaotong University, 2024: 1-26[2024-06-27]. https://doi.org/ 10.16183/j.cnki.jsjtu.2023.516.
[26] Huang Hao, Li Fangxing.Sensitivity analysis of load-damping characteristic in power system frequency regulation[J]. IEEE Transactions on Power Systems, 2013, 28(2): 1324-1335.
[27] 肖家杰, 李培强, 毛志宇. 基于模糊分配因子的电池储能参与二次调频策略[J]. 电网技术, 2023, 47(9): 3568-3577.
Xiao Jiajie, Li Peiqiang, Mao Zhiyu, et al.Battery energy storage participating in secondary frequency regulation based on fuzzy allocation factor[J]. Power System Technology, 2023, 47(9): 3568-3577.
[28] 李军徽, 侯涛, 严干贵, 等. 计及调频成本和荷电状态恢复的多储能系统调频功率双层优化[J]. 中国电机工程学报, 2021, 41(23): 8020-8033.
Li Junhui, Hou Tao, Yan Gangui, et al.Two-layer optimization of frequency modulation power in multi-battery energy storage system considering frequency modulation cost and recovery of state of charge[J]. Proceedings of the CSEE, 2021, 41(23): 8020-8033.
[29] 贺悝, 郭罗权, 谭庄熙, 等. 高比例新能源电网中储能调频死区优化设定控制策略[J]. 电力系统保护与控制, 2024, 52(18): 65-75.
He Li, Guo Luoquan, Tan Zhuangxi, et al.Improved dead zone setting of a frequency regulation strategy for energy storage with high penetration of RESs[J]. Power System Protection and Control, 2024, 52(18): 65-75. |
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2026, Vol. 41 
