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Title
Evaluation Model of Electric Energy Measuring Device Operating Status Based on Deep Learning
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作者
韩玉环秦志沁张毅侯健刘雅俊苑林
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Author
HAN Yuhuan;QIN Zhiqin;ZHANG Yi;HOU Jian;LIU Yajun;YUAN Lin
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单位
国网山西省电力公司晋城供电公司
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Organization
State Grid Shanxi Electric Power Company Jincheng Power Supply Company, Jincheng
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摘要
【目的】在电能计量装置日常运行工作中需要进行运行状态评估,人工检查耗费时间长、效率低下、核查不准确,难以满足实际应用需求。【方法】基于用电信息采集数据,建立基于深度学习的计量装置运行状态评估模型,通过深度学习模型抓取电量历史数据的特征。利用迁移学习优化模型训练过程,完成对用户未来电量使用情况的预测,并对电量期望值与计量值的差值设定阈值,判断电能表的运行状态。【结果】模型结果可作为评估智能电表运行状态的关键参考,为台区智能电表运行维护和精准更换等给予重要的支持,可有效减少实地运维管理人员和运维次数,使故障分析和准确定位得到提升。【结论】由仿真数据和实际台区数据分别对方法的准确性进行验证,实验结果表明本文提出的评估模型效果较好。
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Abstract
【Purposes】 Manual inspection’s lengthy time commitment, poor efficiency, and in-accurate verification make it challenging to meet practical application requirements in the daily operation of electric energy metering devices. 【Methods】 According to the collected data of elec-tricity information, an evaluation model of metering device operation status based on deep learn-ing is established, and the characteristics of historical data of electricity through the deep learning model are captured. By using the transfer learning optimization model training process, the pre-diction of the users’ future electricity usage is completed, and the threshold value is set for the difference between the expected value and the measured value of electricity to judge the running state of the energy meter. 【Findings】 The study’s findings will be a solid foundation for assessing the regional electric energy metering system’s state of operation, as well as for accurately repla-cing and maintaining meter. In addition, it will increase the precision of power grid fault diagno-sis and location while significantly lowering the cost of on-site maintenance. 【Conclusions】 By contrasting the simulated value with the actual platform value, the correctness of the method is demonstrated. The experimental results show that the proposed evaluation model is effective.
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关键词
计量装置深度学习运行状态评估迁移学习
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KeyWords
metering device; deep learning; operation state evaluation; transfer learning
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基金项目(Foundation)
国网山西省电力公司科技项目(5205E0220003)
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DOI
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引用格式
韩玉环,秦志沁,张毅,等.基于深度学习的电能计量装置运行状态评估模型研究[J].太原理工大学学报,2024,55(1):111-119.
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Citation
HAN Yuhuan,QIN Zhiqin,ZHANG Yi,et al.Evaluation model of electric energy measuring device operating status based on deep learning[J].Journal of Taiyuan University of Technology,2024,55(1):111-119.
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