Energy storage energy management system for coordinating power distribution and battery optimization

By using adaptive VMD decomposition and dynamic SOC initial allocation, combined with resistance coefficient optimization, the power allocation and battery optimization of the energy storage system are coordinated, solving the problems of battery pack inconsistency and multi-objective optimization difficulties, and achieving efficient and economical operation of the battery pack.

CN121485230AInactive Publication Date: 2026-02-06SHENZHEN NANKE DIGITAL ENERGY TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202511641436.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-11
Publication Date
2026-02-06
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Traditional energy storage management methods fail to fully consider the differences in dynamic response characteristics between batteries and supercapacitors, leading to worsening battery pack inconsistencies. Furthermore, the lack of a collaborative mechanism in multi-objective optimization makes it difficult to achieve a balance between economic efficiency and lifespan extension.

Method used

Power frequency domain separation is achieved through adaptive VMD decomposition, equalization is improved based on dynamic SOC initial allocation, economic operating cost is optimized by weighted calculation using resistance coefficient, and execution accuracy is ensured through MILP switching control, coordinating power allocation and battery optimization.

Benefits of technology

It effectively reduces the charging and discharging stress and aging rate of the battery, improves the consistency of the battery pack, reduces the total operating cost of the system, and achieves a synergistic improvement in the lifespan, economy and operational reliability of the energy storage system.

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Abstract

The invention relates to an energy storage energy management system for coordinating power distribution and battery optimization, and belongs to the technical field of energy storage energy management. The system comprises a coordinated scheduling layer, a power distribution layer and a unit execution layer. The coordinated scheduling layer receives an original power signal, generates smooth power through smoothing and frequency domain decomposition, and decouples the smooth power; the power distribution layer outputs a final power instruction comprehensively considering economy, loss and SOC balance through sequence optimization; and the unit execution layer converts an instruction into an energy storage unit switching state and a power instruction through mixed integer programming and high-frequency management. According to the method, power frequency domain separation is realized through adaptive VMD decomposition, balance is improved based on dynamic SOC initial distribution, economic operation cost is optimized through resistance coefficient weighting, loss and balance are balanced through multi-objective optimization, and finally execution precision is guaranteed through MILP switching control. The problems of rough power distribution, accelerated battery aging, difficulty in multi-target cooperation and the like in traditional energy storage management are effectively solved.
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