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Research on the performance of fire-storage coordinated frequency modulation based on a bi-level optimization model
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Xu HAN1, Xuanyu ZHONG1, Zhongwen LIU2
Thermal Power Generation | 2026, 55(2) : 75 - 85
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Thermal Power Generation | 2026, 55(2): 75-85
Peak shaving and frequency regulation technology for energy storage system coupled with thermal power unit
Research on the performance of fire-storage coordinated frequency modulation based on a bi-level optimization model
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Xu HAN1, Xuanyu ZHONG1, Zhongwen LIU2
Affiliations
  • 1.Hebei Key Laboratory of Low Carbon and High Efficiency Power Generation Technology, North China Electric Power University, Baoding 071003, China
  • 2.China Power Huachuang Electric Power Technology Research Co., Ltd., Suzhou 215009, China
Published: 2026-02-25 doi: 10.19666/j.rlfd.202511015
Outline
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[Objective]

In order to better cope with the impact of the rapid development of new energy on the existing power grid structure and improve the stability and economy of thermal power unit operation, this paper proposes to construct a dual-layer optimization model of fire storage frequency regulation based on real-time power prediction of thermal power units and fuzzy control allocation of energy storage power.

[Methods]

The upper layer of the model utilizes frequency deviation decomposition and real-time power prediction of thermal power to optimize the power benchmark, effectively overcoming the response delay of the unit. The lower layer introduces a fuzzy logic control strategy to achieve adaptive and precise power allocation between the thermal unit and the energy storage system. On this basis, multi-objective genetic algorithm is used to optimize the energy storage capacity configuration scheme, and the frequency modulation performance under different control strategies is quantitatively evaluated based on indicators such as system frequency fluctuation. Taking a 600 MW thermal power unit as the research object, the optimal energy storage configuration was obtained through algorithm as follows: flywheel energy storage power of 8.5 MW and capacity of 1.3 MW·h, and lithium battery energy storage power of 3.6 MW and capacity of 14.6 MW·h. The total investment cost corresponding to this configuration is 2.027 7×109 yuan, and the actual income during the 400 s frequency modulation cycle is 850.95 yuan.

[Results]

After simulation verification using MATLAB/Simulink, it was found that under step disturbance, the dual layer optimization strategy of fire storage coordination reduces the frequency fluctuation of the system to 4.826×10–2 Hz, which is 38.53% lower than the independent frequency regulation of the fire power unit. The average absolute deviation of power fluctuation is reduced to 4.224 MW, which is 32.57% lower than the independent operation. Under continuous disturbance, the frequency fluctuation of the system decreased by 19.31%, the average absolute deviation of power fluctuation decreased by 78.71%, and the actual contribution of electricity increased by 0.527 MW·h. The results show that the thermal-storage coordinated dual layer optimization control strategy presented in this paper effectively mitigates system frequency and power fluctuations, thereby alleviating the frequency regulation pressure on thermal power units. Concurrently, it enhances the utilization efficiency of the energy storage system and improves the economic viability of frequency regulation services.

[Conclusion]

This research thus provides a novel technical direction for the flexible transformation of thermal power plants, enabling them to play a more supportive and complementary role in future power systems dominated by renewable energy sources.

predictive control  /  multivariate composite energy storage  /  dual-layer optimization control  /  thermal power primary frequency regulation  /  evaluation index
Xu HAN, Xuanyu ZHONG, Zhongwen LIU. Research on the performance of fire-storage coordinated frequency modulation based on a bi-level optimization model[J]. Thermal Power Generation, 2026 , 55 (2) : 75 -85 . DOI: 10.19666/j.rlfd.202511015
  • Hebei Province Higher Education Science Research Project Youth Elite Project(BJ2025053)
  • Hebei Natural Science Foundation(E2023502025)
Year 2026 volume 55 Issue 2
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Article Info
doi: 10.19666/j.rlfd.202511015
  • Receive Date:2025-11-06
  • Online Date:2026-08-14
  • Published:2026-02-25
Article Data
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History
  • Received:2025-11-06
  • Revised:2025-12-03
  • Accepted:2025-12-08
Funding
Hebei Province Higher Education Science Research Project Youth Elite Project(BJ2025053)
Hebei Natural Science Foundation(E2023502025)
Affiliations
    1.Hebei Key Laboratory of Low Carbon and High Efficiency Power Generation Technology, North China Electric Power University, Baoding 071003, China
    2.China Power Huachuang Electric Power Technology Research Co., Ltd., Suzhou 215009, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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