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Battery energy storage station monitoring method and system based on big data and digital twinning

A technology of battery energy storage and big data, applied in information technology support systems, measuring electricity, electrical components, etc., can solve the problems of low efficiency, inability to thermal runaway intelligent data analysis, low reliability of safety control, etc., to achieve effective The effect of financial services

Active Publication Date: 2021-10-19
GUANGZHOU JIANXIN TECHNOLOGY CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a battery energy storage station monitoring method and system based on big data and digital twins, which solves the problem that the monitoring of battery energy storage stations in the prior art is not perfect, and it is impossible to accurately perform intelligent data analysis on thermal runaway , the technical problems of low safety control reliability and low efficiency have been achieved, driven by big data, using digital twins as a means to digitally manage and monitor battery energy storage stations through multiple models, and improve the accuracy of thermal runaway data analysis , and then improve the technical effect of monitoring efficiency and safety control reliability

Method used

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  • Battery energy storage station monitoring method and system based on big data and digital twinning
  • Battery energy storage station monitoring method and system based on big data and digital twinning

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Embodiment 1

[0030] Such as figure 1As shown, the embodiment of the present application provides a battery energy storage station monitoring method based on big data and digital twins, wherein the method is applied to a battery energy storage station intelligent monitoring system, and the system and the first simulation system A communication connection, the method comprising:

[0031] Step S100: Obtain all element information of the battery energy storage power station;

[0032] Specifically, the full-element information is the information obtained by collecting all the elements in the battery energy storage power station, wherein the full-element information is the information of each component of the physical entity of the battery energy storage power station, and the space environment in which it is located. Information such as elements, so as to carry out digital simulation based on the information of all elements, and collect the information of all elements to provide a comparison b...

Embodiment 2

[0088] Based on the same inventive concept as that of a battery energy storage station monitoring method based on big data and digital twins in the foregoing embodiments, the present invention also provides a battery energy storage station monitoring system based on big data and digital twins, such as Figure 8 As shown, the system includes:

[0089] The first obtaining unit 11, the first obtaining unit 12 is used to obtain the full element information of the battery energy storage power station;

[0090] The first construction unit 13, the first construction unit 13 is used to construct a first digital twin model according to the full element information and the first simulation system, wherein the first digital twin model includes a three-dimensional model, data Model and mechanism model, and there is a connection relationship between the models;

[0091] A second obtaining unit 14, configured to obtain a second digital twin model by dynamically updating the first digital t...

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Abstract

The invention discloses a battery energy storage station monitoring method and system based on big data and digital twinning, and the method comprises the steps: building a first digital twinning model according to total element information of a battery energy storage station and a first simulation system, and the first digital twinning model comprises a three-dimensional model, a data model and a mechanism model; dynamically updating the first digital twinborn model to obtain a second digital twinborn model; according to the failure behavior data of the battery energy storage power station, constructing a first power station monitoring model, wherein the first power station monitoring model comprises a monitoring model, an analysis model and an alarm model; and performing intelligent monitoring on the battery energy storage power station according to the second digital twinning model and the first power station monitoring model. The technical problems that in the prior art, monitoring of the battery energy storage station is not perfect, intelligent data analysis cannot be accurately conducted on thermal runaway, the reliability of safety control is low, and the efficiency is not high are solved.

Description

technical field [0001] The invention relates to the related fields of battery energy storage stations, in particular to a method and system for monitoring battery energy storage stations based on big data and digital twins. Background technique [0002] In recent years, electrochemical energy storage technology has been widely used in many fields such as power generation, auxiliary services, power transmission and distribution, renewable energy access, distributed energy storage and end users in the power system, making battery energy storage technology increasingly It has become a hotspot of current research. Since the battery energy storage technology has multiple characteristics of improving power quality, peak shaving and valley filling, peak shaving and frequency modulation, improving power supply capacity and grid stability, in order to respond to the needs of intelligent applications, a higher level of management of battery energy storage stations is put forward. hig...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J13/00H02J3/32G01R31/367
CPCH02J13/00001H02J13/00002H02J3/32G01R31/367H02J2203/20Y04S10/14Y04S10/40Y02E70/30Y02E60/00Y02B90/20Y04S20/12
Inventor 刘勇坚刘勇唐票林李大全谢巨龙
Owner GUANGZHOU JIANXIN TECHNOLOGY CO LTD
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