Situation awareness theory-based transformer state evaluation method

Abstract

The invention discloses a situation awareness theory-based transformer state evaluation method. The method comprises the following steps of: firstly determining three sub-objects for a comprehensive transformer body state monitoring amount and a power grid operation scene monitoring amount, wherein the three sub-objects are as follows: 1) a major insulation condition of a transformer, 2) whether the transformer emits heat abnormally, and 3) a mechanical deformation condition of the transformer; and respectively carrying out situation awareness demand analysis on each sub-object decision one by one so as to determine each to-be-perceived monitoring amount, namely, a perception amount, and carrying out analysis by adopting an unascertained theory so as to know the degree of influence, caused by each perception amount, on the major insulation of the transformer and realize the prediction for the future development trend of the major insulation. Compared with the conventional method, the method disclosed by the invention not only can be used for detecting the information, in the aspects of electricity, heat and chemistry, of the transformer, but also can be used for specifically integrating the multi-source information on the basis of demands of operation personnel, so that the operation personnel can know the real conditions, in various aspects, of the transformer more simply and visually.

Description

technical field [0001] The invention relates to the technical field of electric power detection, in particular to a transformer state evaluation method based on situation awareness theory. Background technique [0002] The condition assessment and condition-based maintenance of power equipment is one of the important goals of power grid operation and maintenance. At present, the secondary monitoring technology of power equipment has been rapidly improved and applied. However, in the past, it focused on the condition assessment based on unilateral monitoring. Less consideration is given to the physical correlation and constraint relationship of more monitoring quantities, which has become a bottleneck in improving the accuracy of power equipment status assessment. Introducing the concept of secondary system estimation to fuse multi-monitoring information, thereby improving the accuracy of power equipment status assessment, has become a way to break through the bottleneck. As...

AI Technical Summary

Problems solved by technology

However, in the face of these massive data, it is often more difficult for operators to obtain useful information than in the past, and the status assessment they make is often single-sided, which cannot fully and effectively reflect the current status of the transformer

This can easily lead to wrong judgments by operators, resulting in wrong decisions

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