Configuration Scheme and Economic Analysis Method of Battery Energy Storage Participating in Power System Peak Shaving

Rational allocation of energy storage can reduce the burden of peak shaving on thermal power units and improve the wind power consumption rate. This paper presents a configuration scheme for energy storage participating in peak shaving and its corresponding economic analysis method. During the energ...

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Bibliographic Details
Published in2023 5th Asia Energy and Electrical Engineering Symposium (AEEES) pp. 929 - 934
Main Authors Niu, Jiayi, Zeng, Fanpeng, Li, Weixing
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.03.2023
Subjects
Analytical models
economic analysis
Economics
Energy consumption
energy storage
life cycle benefits
Optimal scheduling
optimize configuration
Power measurement
Time series analysis
Wind power generation
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Summary:Rational allocation of energy storage can reduce the burden of peak shaving on thermal power units and improve the wind power consumption rate. This paper presents a configuration scheme for energy storage participating in peak shaving and its corresponding economic analysis method. During the energy storage configuration calculation stage, a time-series simulation method is used to calculate a series of configuration combinations of energy storage power and capacity that meet the requirements for new energy consumption, taking into account the substitution of energy storage for conventional thermal power units. In the economic analysis stage of energy storage, an optimal scheduling model and life-cycle revenue model for energy storage participating in peak shaving are established, with the configuration combination obtained from the preliminary calculation serving as the constraint condition. The optimal allocation result is the power and capacity combination that maximizes revenue. Finally, the effectiveness of the energy storage configuration calculation and economic analysis methods presented in this paper are verified through the analysis and calculation of energy storage configuration based on measured data from a provincial power system.
DOI:10.1109/AEEES56888.2023.10114092