Parameter optimization method and device of coupling type transformer

Through the parameter optimization method of coupled transformers, nonlinear dynamic analysis and global state perception modeling are used to use multi-dimensional real-time monitoring parameters and environmental state parameters to perform nonlinear dynamic analysis and global state perception modeling, which solves the problem of insufficient performance optimization and fault prediction of traditional methods under complex operating conditions, and realizes efficient operation and fault prediction of transformers.

CN119644765AActive Publication Date: 2025-03-18SHENZHEN RUIQIZHENG TECH CO LTD
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Patent Information

Application Number
CN202510178195.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-18
Publication Date
2025-03-18
Estimated Expiration
2045-02-18

AI Technical Summary

Technical Problem

Traditional transformer operation management methods have problems such as diagnostic lag, inefficient, and poor fault prediction accuracy when dealing with performance optimization and fault prediction under complex operating conditions.

Method used

A parameter optimization method for coupled transformers is proposed. By obtaining multi-dimensional real-time working monitoring parameters and environmental state parameters, nonlinear dynamic analysis and global state perception modeling, dynamic operation simulation, multi-objective dynamic balance analysis, local and global parameter optimization, and building a global parameter optimization engine.

Benefits of technology

It realizes multi-dimensional real-time monitoring and analysis of transformers, warning of potential faults in advance, optimizes working parameters, improves the operating efficiency and stability of the transformer, and reduces the risk of failure.

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Abstract

The invention relates to the field of transformer parameter regulation and control, in particular to a parameter optimization method and device for a coupling type transformer. The method comprises the following steps: acquiring multi-dimensional real-time working monitoring parameters and real-time working environment state parameters of the coupling type transformer; performing nonlinear dynamic analysis and global state sensing modeling on the multi-dimensional real-time working monitoring parameters so as to construct a transformer global state sensing model; performing multi-parameter combination definition on the multi-dimensional real-time working monitoring parameters, performing dynamic operation simulation based on a transformer global state sensing model, and collecting operation simulation response data of a plurality of schemes; performing multi-target dynamic balance analysis on the operation simulation response data of the plurality of schemes to obtain an optimal transformer working parameter combination; and carrying out environment dynamic parameter change analysis on the real-time working environment state parameters, and constructing a real-time environment condition distribution field. According to the invention, efficient and self-adaptive adjustment transformer parameter optimization is realized.
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