Open Access Paper
15 January 2025 Research on analysis and optimization mathematical model of 356 day charge and discharge data of user side energy storage based on least squares function fitting
Shiling Zhang, Qiang Xiao, Haoyu Wang, Qian Zhou
Author Affiliations +
Proceedings Volume 13513, The International Conference Optoelectronic Information and Optical Engineering (OIOE2024); 135133O (2025) https://doi.org/10.1117/12.3054838
Event: The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), 2024, Wuhan, China
Abstract
User-side energy storage power stations are widely used, and their historical operating data will have a strong correlation with the operating data of energy storage batteries. By obtaining charging and discharging power data points of energy storage power stations every 15 minutes, the centralized/user side energy storage power station charging and discharging curve is formed. The energy storage power station charging and discharging curve can be effectively obtained through the least squares fitting method. Through the quantitative analysis of the 34228 data points, it was found that the typical charging and discharging types of typical six centralized energy storage power stations include "1 charge, 1 discharge", "2 charge, 2 discharge" and other typical charging and discharging curves. And the charging time is mainly concentrated in the time zone from 0:00 to 8:00 in the morning, followed by discharge during the peak period between 12:00 and 2:00, and discharge during the peak period from 8:00 to 10:00 in the evening. Generally speaking, for independent centralized energy storage power plants, the entire charging and discharging process can be completed within 2 to 3 hours. In on-site analysis of the energy storage power stations, there is significant difference in the SOC (State of Charge) between power charging and discharging, as well as power following the depth of battery charging and discharging. The range of SOC variation during power charging and discharging is between 20% and 100%, while during power following, the range of SOC variation is between 70% and 80%. This article takes actual 356 day operation data of centralized energy storage power stations as the research object, quantitatively analyzes the characteristics of charge and discharge data, and the research results have good guiding value for the operation and maintenance of user side energy storage power stations.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Shiling Zhang, Qiang Xiao, Haoyu Wang, and Qian Zhou "Research on analysis and optimization mathematical model of 356 day charge and discharge data of user side energy storage based on least squares function fitting", Proc. SPIE 13513, The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), 135133O (15 January 2025); https://doi.org/10.1117/12.3054838
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KEYWORDS
Data storage

Batteries

Mathematical optimization

Power grids

Solar energy

Analytical research

Computer programming

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