Comprehensive Evaluation Method for Thermal Power Unit Flexibility Based on Data-driven and Its Application

WANG Zhijie; CHEN Wen; ZHU Xiaoxing; WANG Xihui

doi:10.19725/j.cnki.1007-2322.2022.0281

Modern Electric Power > 2024 > 41(4): 667-672. > DOI: 10.19725/j.cnki.1007-2322.2022.0281

WANG Zhijie, CHEN Wen, ZHU Xiaoxing, et al. Comprehensive Evaluation Method for Thermal Power Unit Flexibility Based on Data-driven and Its Application[J]. Modern Electric Power, 2024, 41(4): 667-672. DOI: 10.19725/j.cnki.1007-2322.2022.0281

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Comprehensive Evaluation Method for Thermal Power Unit Flexibility Based on Data-driven and Its Application

WANG Zhijie^{1, 2, ,},
CHEN Wen^{2, 3,},
ZHU Xiaoxing^{1, 2,},
WANG Xihui^{1, 2,}

1.
State Grid Hunan Electric Power Company Limited Research Institute, Changsha 410031, Hunan Province, China
2.
Hunan Key Laboratory of High Efficiency Clean Power Generation Technology, Changsha 410031, Hunan Province, China
3.
Hunan Xiangdian Test Research Institute Co., Ltd., Changsha 410031, Hunan Province, China

Funds: Project Supported by the Science and Technology Project of State Grid Hunan Electric Power Co., Ltd (5216A521N00H )

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Received Date: July 28, 2022
Accepted Date: June 05, 2023
Available Online: June 25, 2023

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Abstract

Abstract

Sensing the flexible supply capacity of thermal power units actively is of great significance in promoting new energy consumption and enabling flexible dispatching of power grid. In this paper, a comprehensive evaluation method for thermal power unit flexibility based on data-drive was proposed. Firstly, flexibility, responsiveness, economy and environmental protection were selected as evaluation indexes , and the evaluation factors of each index were defined. Secondly, a significant volume of operating data were utilized to obtain the characterization values of each evaluation factor within the daily operation interval of the unit through fuzzy c -means clustering algorithm and polynomial fitting. Meanwhile, the quantization of each evaluation factor was achieved by a weighted integral mean method. Finally, the entropy weight method and subjective assignment method were combined to determine the weight of each evaluation index, thereby realizing comprehensive evaluation of thermal power unit flexibility. An instance was taken to verify the effectiveness of the proposed method.
- data-driven,
- thermal power unit,
- flexibility,
- weight coefficient,
- comprehensive evaluation

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References (25)

References

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