Energy storage power station system based on cloud side cooperation

Abstract

The invention relates to the technical field of electric power, in particular to an energy storage power station system based on cloud side cooperation. The power station system comprises a battery management system used for managing an energy storage battery of an energy storage power station; an edge computing system used for collecting data; a cloud server used for acquiring historical data ofthe energy storage system from the edge computing system and generating a diagnosis result; an energy management system used for obtaining a latest edge algorithm and a diagnosis result of the cloud server from the edge computing system and generating a control instruction; an automatic control system used for acquiring a control instruction and sending the control instruction to the battery management system to control the energy storage battery; and an intelligent detection system which performs fault detection according to the cloud diagnosis result and sends the detection result to the cloud server. According to the invention, the energy storage battery is diagnosed and a diagnosis result is generated in a manner of combining edge side calculation and cloud calculation, and rapid faultdetection is carried out on the energy storage battery.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to an energy storage power station system based on cloud-edge collaboration. Background technique [0002] Accidents in energy storage power stations occur frequently, and safety has become a bottleneck in the development of the energy storage industry. Therefore, there is an urgent need for rapid diagnosis to realize safety warning, and battery life cycle management to realize battery status prediction and prevention. [0003] Some existing energy storage monitoring mainly relies on on-site systems and local data storage, which cannot provide big data support for fault diagnosis, mechanism analysis, and early warning algorithms. Some existing energy storage monitoring relies on cloud servers for fault diagnosis. However, due to the large amount of data in energy storage power stations, it takes a long time for data to be transmitted to cloud servers, so fault diagnosis is o...

AI Technical Summary

Problems solved by technology

[0003] Some existing energy storage monitoring mainly relies on on-site systems and local data storage, which cannot provide big data support for fault diagnosis, mechanism analysis, and early warning algorithms

Some existing energy storage monitoring relies on cloud servers for fault diagnosis, but due to the large amount of data in energy storage power stations, it takes a long time for data to be transmitted to cloud servers, so fault diagnosis is often not timely enough

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