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7 December 2023 Method for identifying abnormal power metering data in shared power information collection system
Yefei Li, Guangyao Miao, Shujun Jing, Bo Fan, Meiling Jia
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Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129411M (2023) https://doi.org/10.1117/12.3011771
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
With the massive use of mobile IoT technology and shared thinking innovative electricity consumption mode, shared electricity consumption smart devices have come into being, and the identification of abnormal electrical energy metering data in the process of shared electricity consumption collection has become an urgent research problem. In this paper, by studying the method of identifying abnormal electrical energy metering data in shared electricity information collection system, we select the improved particle swarm algorithm to optimize the parameters of support vector machine kernel function, construct the power quality disturbance model, and implement the classification of abnormal electrical energy metering data collected by electricity information system; use LOF algorithm to calculate the abnormality factor, and use the disturbance model determined by fly away abnormal intelligent analysis method to judge whether the displayed value of electrical energy meter The LOF algorithm is used to calculate the abnormality factor, and the disturbance model determined by the fly-away abnormality analysis method is used to determine whether the displayed value of the energy meter is abnormal or not. The experimental results show that the method of this paper is more accurate in classifying abnormal data and can better prevent the occurrence of error judgment, which can effectively improve the quality and efficiency of abnormal judgment of electric energy metering data and better realize the accurate measurement of shared electricity.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yefei Li, Guangyao Miao, Shujun Jing, Bo Fan, and Meiling Jia "Method for identifying abnormal power metering data in shared power information collection system", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129411M (7 December 2023); https://doi.org/10.1117/12.3011771
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KEYWORDS
Data modeling
Particles
Power consumption
Data acquisition
Particle swarm optimization
Classification systems
Education and training
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