Energy storage device constant volume processing method and device and electronic device

By sampling and clustering the operating parameters of energy storage devices, the types of electrical loads are identified, and the charging and discharging capacity and cycle number are calculated. This solves the problem of inaccurate determination of energy storage device capacity, achieves accurate quantification of reasonable capacity, and reduces construction costs and resource waste.

CN116011835BActive Publication Date: 2026-05-15SHANGHAI MAKESENS ENERGY STORAGE TECH CO LTD
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Patent Information

Application Number
CN202310011782.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-01-05
Publication Date
2026-05-15
Estimated Expiration
2043-01-05

AI Technical Summary

Technical Problem

In the construction of energy storage equipment systems, how to determine the appropriate capacity to maximize benefits and avoid problems such as excessive construction costs or insufficient capacity.

Method used

By acquiring the operating and cost parameters of the energy storage device, determining the sampling points within the sampling period, performing cluster analysis, identifying the types of electricity load at different times, calculating the charging and discharging capacity and the number of cycles, determining the feasible capacity range, and finally selecting appropriate resource information as the set capacity of the energy storage device.

Benefits of technology

Accurately determining the appropriate capacity of energy storage equipment avoids project delays and resource waste caused by inaccurate capacity, and reduces construction costs.

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Abstract

This application provides a method for determining the capacity of an energy storage device. The method includes: acquiring the operating parameters and operating cost parameters of the energy storage device, and determining sampling points within a sampling period. Clustering the sampling points within the sampling period to obtain clustering results. Determining the electricity load type and electricity resource information based on the clustering results, performing capacity analysis, and determining the charge / discharge capacity. Determining the number of charge / discharge cycles and the charge / discharge cycle interval matching the number of charge / discharge cycles within the sampling period based on the electricity resource information. Calculating the feasible capacity based on the charge / discharge capacity and the number of charge / discharge cycles. Calculating the corresponding resource information coefficient based on the feasible capacity, and selecting the feasible capacity corresponding to the largest resource information coefficient as the set capacity of the energy storage device. This application selects a suitable energy storage device capacity by calculating multiple feasible capacities and the resource information coefficients corresponding to different feasible capacities, thereby achieving peak shaving and valley filling of electricity demand.
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