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Study of abnormal electricity consumption for
ID：123 View Protection：ATTENDEE Updated Time：2022-05-16 17:15:02 Hits：325 Poster Presentation

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Abstract
     As a new form of heating, "coal to electricity" has begun to bear fruit, but with it, the number of abnormal electricity consumption is also increasing, which is not only bringing huge losses to the power company, but also causing faults in the transmission lines. The traditional manual inspection of abnormal power faults is inefficient and low in accuracy. To address these problems, by using the power information contain- ed in the power company, the author processed the data firstly in this paper, and according to the universal law of abnormal power usage, the author could generate abnormal data. Then select the best mathematical feature indicators suitable for the model. Finally this article proposes a abnormal power usage detection model based genetic-neural network. The results and a comparis-on with conventional tests show that the proposed model is more accurate, efficient and independent of circuit information than traditional abnormal electricity usage detection.
 
Keywords
coal conversion;abnormal electricity usage detection;electricity information; mathematical features;genetic-neural networks
Speaker
ChengYushu
国网山西省电力公司营销部

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Important Date

  • Conference Date

    May 27

    2022

    to

    May 29

    2022

  • Feb 28 2022

    Draft paper submission deadline

  • May 29 2022

    Registration deadline

  • Jun 22 2022

    Contribution Submission Deadline

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IEEE Beijing Section
China Electrotechnical Society
Southeast University
Supported By
IEEE Industry Applications Society
IEEE Nanjing Section
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