Adaptive binary search algorithm for malicious user positioning in smart grid neighboring network

Abstract

The invention relates to a smart grid technology, and in particular relates to an adaptive binary search algorithm for malicious user positioning in a smart grid neighboring network. The method comprises the steps that first the maximum value of malicious users in the neighboring network is estimated; in a searching process, a detector adaptively adjusts a search strategy according to the relationship between the number of detected malicious users and the total number of users still needing to be detected; when a one-by-one search strategy is used, the detector detects only one user at a time;when a binary search strategy is adopted, the detector detects multiple users at the same time; and the number of detected users is determined by the number of detected malicious users and the numberof users still needing to be detected together. According to the invention, the adaptive binary search method for malicious user positioning in the smart grid neighboring network is proposed under the premise of reducing the deployment cost of detectors; and the algorithm can adaptively adjust the search strategy during a detection process and shorten the detection time of malicious users.

Description

Technical field [0001] The invention relates to smart grid technology, in particular to a self-adaptive binary search algorithm for locating malicious users in a neighborhood network of a smart grid. Background technique [0002] For a long time, the problem of electricity theft has plagued the development of power companies, and has also seriously affected the country's economic development and social stability. In recent years, with the significant increase in electricity demand, the problem of electricity theft has become particularly prominent. According to incomplete statistics, the current annual economic loss due to electricity theft is as high as 89.3 billion US dollars worldwide. There are many reasons for the phenomenon of electricity theft. It is related to users' legal concepts, moral concepts, socio-economic development level, electricity prices and user affordability, the anti-theft reliability of electric energy metering equipment, the level of electricity marketi...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems of high deployment cost and long detection time of the existing malicious user detection method based on power measurement, the present invention proposes an adaptive binary search method for locating malicious users in the smart grid neighborhood area network

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