Abnormality detection method and device of energy data, terminal equipment and storage medium

By performing interval division and delay factor calculation on energy data and temperature data, the target energy data is corrected, and the problem of high false alarm rate of abnormal detection of energy data in the prior art is solved, and the detection accuracy and response efficiency are improved.

CN120146626APending Publication Date: 2025-06-13GUANGDONG POWER GRID CO LTD
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Patent Information

Application Number
CN202510302242.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-14
Publication Date
2025-06-13

AI Technical Summary

Technical Problem

Existing energy data anomaly detection algorithms are difficult to accurately identify normal data affected by the delay effect of temperature changes, resulting in high false alarm rates and affecting rapid response and processing efficiency.

Method used

By obtaining energy data and temperature data, an initial sequence is constructed, and the interval is divided according to the temperature change trend, the delay factor at each time point is calculated, the abnormal delay factor is determined, and the target energy data is corrected to reflect the data changes after the sudden change of temperature.

Benefits of technology

It improves the accuracy of abnormal detection of energy data, reduces the false alarm rate, and enhances the rapid response and processing efficiency of real abnormal events.

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Abstract

The invention discloses an energy data anomaly detection method and device, terminal equipment and a storage medium, and the method comprises the steps: enabling energy data and temperature data at a plurality of time points to form an initial sequence, dividing the initial sequence into a plurality of intervals according to a temperature change trend, and calculating a delay factor of each time point in each interval, the delay degree of the energy data on the temperature data at each time point is evaluated, delay factors in the same temperature change type are compared, abnormal delay factors can be accurately distinguished, and the time points corresponding to the abnormal delay factors serve as delay points. The target energy data and the target temperature data of the delay point are corrected by referring to the energy data and the temperature data of the standard interval with the low delay effect, so that the corrected to-be-detected sequence can reflect the gradual accumulation process of the energy data after the temperature is suddenly changed, and the accuracy of energy data anomaly detection is improved.
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