A fault diagnosis method for power grid based on space optimal code set and dhnn error correction

Abstract

The present invention relates to the technical field of power grid fault diagnosis, in particular to a power grid fault diagnosis method based on space optimal code set and DHNN error correction, which maps remote signaling data into the fault diagnosis space, and performs the fault diagnosis with the fault space optimal code set. Compare and classify, so as to realize the fault diagnosis of the power grid. Through the remote signal displacement data of different failure modes, the discrete Hopfield neural network is trained, and the associative ability of DHNN is used to correct the misplaced or missing data of the remote signal, so as to realize the cleaning of the remote signal front-end data. Finally, an intelligent grid fault diagnosis method with error correction capability is formed to realize the diagnosis of fault components in the fault diagnosis space. The validity of the Hopfield neural network information correction model and the fault diagnosis model for the diagnosis of fault components in the power grid is verified by testing the fault remote signaling data of the actual power grid.

Description

technical field [0001] The invention relates to the technical field of power grid fault diagnosis, in particular to a power grid fault diagnosis method based on a spatial optimal code set and DHNN error correction. Background technique [0002] When the power grid fails, a large amount of fault and alarm information will be uploaded to the dispatch center, making it difficult for dispatchers to make accurate judgments on the faulty equipment and fault types in a short period of time, especially in complex faults or faulty relay protection or It is more difficult to deal with situations such as refusal to move. In addition, due to the serious interference of the communication system or the failure of the monitoring equipment, the misplacement or loss of the remote signaling data occurs, which interferes with the judgment of the dispatcher. Therefore, a set of intelligent and fast fault diagnosis system is needed to assist dispatchers to make accurate judgments on faulty comp...

AI Technical Summary

Problems solved by technology

However, the existing grid fault diagnosis methods using remote signaling data are not ideal for the following two aspects: 1. It is difficult to diagnose grid faults simply and quickly when applied to large-scale and complex grids; 2. Difficulty in properly diagnosing grid faults when missing or misplaced bits

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