Abnormal behavior analysis of electricity consumption based on improved random forest with grey relation projection

• Published in: Journal of physics. Conference series Vol. 1754; no. 1; pp. 12027 - 12031
• Main Authors: Kun, WANG, Jinggeng, GAO
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.02.2021
• Subjects: Algorithms; Data processing; Diagnosis; Electric power systems; Electricity; Electricity consumption; Internet of Things; Physics; Power consumption
• ISSN: 1742-6588; 1742-6596; 1742-6596
• DOI: 10.1088/1742-6596/1754/1/012027

Abstracts: With the construction of ubiquitous power Internet of things and the deepening application of big data technology, it is possible to mine the abnormal behavior of electricity consumption from the massive power consumption information. In view of the current application of anti stealing power in power system, an improved random forest algorithm based on grey relation projection is proposed to analyze the abnormal behavior of power consumption. The improved stochastic Sen algorithm is used to build the diagnosis model of abnormal electricity consumption of users, and analyze the power data of the power consumption information acquisition system, so as to improve the accuracy of the intelligent diagnosis algorithm of anti stealing electricity. The effectiveness of the proposed algorithm can be obtained by verification test.