蔡慧, 乔适苏, 袁健, 陈含琪, 李璟, 潘一洲. 基于信息融合的低压智能电能表动态评价模型[J]. 电力系统自动化, 2020, 44(11): 206-214.
引用本文: 蔡慧, 乔适苏, 袁健, 陈含琪, 李璟, 潘一洲. 基于信息融合的低压智能电能表动态评价模型[J]. 电力系统自动化, 2020, 44(11): 206-214.
CAI Hui, QIAO Shisu, YUAN Jian, CHEN Hanqi, LI Jing, PAN Yizhou. Information Fusion Based Dynamic Evaluation Model of Low-voltage Smart Electricity Meter[J]. Automation of Electric Power Systems, 2020, 44(11): 206-214.
Citation: CAI Hui, QIAO Shisu, YUAN Jian, CHEN Hanqi, LI Jing, PAN Yizhou. Information Fusion Based Dynamic Evaluation Model of Low-voltage Smart Electricity Meter[J]. Automation of Electric Power Systems, 2020, 44(11): 206-214.

基于信息融合的低压智能电能表动态评价模型

Information Fusion Based Dynamic Evaluation Model of Low-voltage Smart Electricity Meter

  • 摘要: 针对智能电能表状态评价技术有待完善的问题,基于信息融合理论建立了一种新的低压智能电能表动态评价模型。该模型对低压智能电能表可靠度进行分析的同时,综合考虑计量异常、全事件、电能表过载率、时钟电池异常4种状态因素,采用熵值法实时计算各项指标权值,并且结合地区影响因素,对低压智能电能表进行动态状态评价。基于威布尔分布理论构建电能表可靠度子评价模型,应用贝叶斯公式建立计量异常和全事件子评价模型,引入泰尔指数评价地区影响因素。采用实际运行数据对该评价模型进行验证,结果表明所提模型合理、可行,能够对智能电表进行有效评价。

     

    Abstract: Aiming at the problem that the state evaluation technology of intelligent electricity meter needs to be perfected, this paper establishes a new dynamic evaluation model of low-voltage intelligent electricity meter based on information fusion theory.While analyzing the reliability of the low-voltage intelligent electricity meter, the four state factors, namely abnormal measurement, full event, overload rate of the electricity meter and abnormal clock battery are comprehensively considered, and the entropy method is adopted to calculate the weight of each index in real time. In addition, the dynamic state evaluation of the lowvoltage intelligent electricity meter is made based on the regional influence factors. Based on Weibull distribution theory, a subevaluation model of reliability for electricity meter is developed, a sub-evaluation model of measurement anomaly and full event is established by using Bayesian formula, and the Thiel index is introduced to evaluate area influential factors. The evaluation model is verified by the actual operation data, and the results show that the developed model is reasonable and feasible, and can effectively evaluate the intelligent electricity meter.

     

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