Collaborative control methods, systems and equipment for high-voltage direct-connected battery energy storage systems

By collecting and optimizing grid and battery information in real time, calculating power commands and allocation coefficients, and using predictive models to optimize control signals, the problem of battery cluster balancing and coordinated control in high-voltage direct-connected battery energy storage systems has been solved, improving system efficiency and reliability, extending battery life, and enabling rapid grid response and stable operation.

CN121813498BActive Publication Date: 2026-06-30JIANGSU ELECTRIC POWER RES INST +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
JIANGSU ELECTRIC POWER RES INST
Filing Date
2026-03-09
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

High-voltage direct-connected battery energy storage systems suffer from issues such as internal battery cluster balancing and insufficient coordination between grid voltage and internal battery cluster sub-modules, which affect battery life and the overall performance of the energy storage system.

Method used

By collecting grid-side information and battery status information in real time, calculating power commands and power allocation coefficients, and using predictive models to optimize switching signals and DC/DC converter control signals, the battery energy storage submodule achieves self-balancing and rapid response.

Benefits of technology

It improves the efficiency and reliability of battery energy storage systems, extends battery life, achieves self-balancing of battery state, and can quickly and accurately respond to changes in grid voltage, ensuring stable system operation.

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Abstract

This application provides a collaborative control method, system, and device for a high-voltage direct-connected battery energy storage system, relating to the field of battery energy storage technology. The method includes: calculating the power command of the high-voltage direct-connected battery energy storage system based on real-time collected voltage and current information from the grid side and the system's operating requirements; calculating the power allocation coefficient of each battery energy storage sub-module based on the acquired battery state information; predicting the future output of each battery energy storage sub-module based on a prediction model, according to the power command of the high-voltage direct-connected battery energy storage system and the power allocation coefficients of each battery energy storage sub-module; optimizing the switching signals of each battery energy storage sub-module and the control signals of the DC / DC converter based on the prediction results, and outputting the optimization results. This method effectively improves the efficiency and reliability of the battery energy storage system, extends battery life, and achieves self-balancing of battery state.
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