Power grid anomaly detection method and device, computer equipment and storage medium

Abstract

The invention relates to a power grid anomaly detection method and device, computer equipment and a storage medium. The method comprises the steps of obtaining the sample set of the state informationof a power grid in each time period, and training the power grid anomaly detection model according to the sample set to obtain an anomaly score corresponding to each sample, calculating the actual deviation between the reference score and the anomaly score, optimizing the power grid anomaly detection model according to the actual deviation until the actual deviation reaches the expectation, and completing training to obtain a trained power grid anomaly detection model. By adopting the method, the diagnosis speed of the power grid fault can be improved, and the fault source can be accurately recognized.

Description

technical field [0001] The present application relates to the technical field of data mining, in particular to a method, device, computer equipment and storage medium for abnormality detection of a power grid. Background technique [0002] At present, my country's economic construction has entered a stage of rapid development, and various industries are increasingly dependent on the power system. The stable operation of the power system has become a major task related to the national economy and people's livelihood. However, due to operational errors, man-made sabotage, and natural force majeure, large-scale power outages occur from time to time. Therefore, the self-healing of the power system, that is, the ability to quickly diagnose, isolate the fault and recover itself after the grid fails, has become a major research direction of the smart grid. As a prerequisite for the realization of the "self-healing" of the smart grid, power system fault diagnosis methods have alway...

AI Technical Summary

Problems solved by technology

[0004] After a fault occurs, the dispatch center can obtain a large amount of data related to fault diagnosis. While so much information allows dispatch operators to understand the status of the power grid in a timely manner, it also has a great negative impact: when a fault occurs, especially a large-scale fault And when there is protection or circuit breaker malfunction or refusal to operate, a large amount of information will be flooded into the dispatch center at the same time, which will bring extremely complicated situations to manual judgment.

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