Assessment method of smart electricity meter running state based on MFT model

Authors

Yuman XIE, Power Supply Service Center （Measurement Center ）， State Grid Hunan Electric Power Co .， Ltd.， Changsha 410010， China;Intelligent Electrical Measurement and Application Technology Key Laboratory of Hunan Province ， Changsha 410082， China
Cong TAN, Power Supply Service Center （Measurement Center ）， State Grid Hunan Electric Power Co .， Ltd.， Changsha 410010， China;Intelligent Electrical Measurement and Application Technology Key Laboratory of Hunan Province ， Changsha 410082， ChinaFollow
Hongq iao HUANG, Power Supply Service Center （Measurement Center ）， State Grid Hunan Electric Power Co .， Ltd.， Changsha 410010， China;Intelligent Electrical Measurement and Application Technology Key Laboratory of Hunan Province ， Changsha 410082， China
Bingxiang LUO, Power Supply Service Center （Measurement Center ）， State Grid Hunan Electric Power Co .， Ltd.， Changsha 410010， China;Intelligent Electrical Measurement and Application Technology Key Laboratory of Hunan Province ， Changsha 410082， China
Zhiwei JIA, School of Electrical & Information Engineering ， Chang sha University of Science and Technology ， Changsha 410114， China
Chenhao SUN, School of Electrical & Information Engineering ， Chang sha University of Science and Technology ， Changsha 410114， China

Keywords

smart electricity meter;running state assessment;association rule;fuzzy probability;tiered fuzzyinference system

Abstract

The smart electricity meter，as the terminal device for smart grid marketing，electricity information，and energy distribution，provides strong data support in various aspects such as distribution network operation and maintenance management and customer experience optimization.However，due to the complex and variable operating environment，it is difficult to accurately assess its running state.Therefore，the modified association rules mining （MARM） method is employed，which improves upon two key importance evaluation criteria in the traditional ARM model.This enhancement not only increases the accuracy of state assessment but also improves the ability to identify potential operational risks.Additionally，to reduce uncertainty when dealing with continuous features，the traditional fuzzy inference system （FIS） is enhanced by introducing fuzzy probability （FP） and the tiered fuzzy inference system （TFIS）.Through model integration，a MARM-FP-TFIS （MFT） model that combines strong association rule identification with probability fuzzy inference is developed to solve the health assessment of the running state of smart electricity meters，realizing the evaluation of the running state of the smart energy meter.Finally，case studies verify the feasibility and functionality of the established model in practical applications，thus achieving an accurate assessment of the running state of smart electricity meters under multidime nsional data conditions.

DOI

10.19781/j.issn.1673-9140.2025.04.009

First Page

92

Last Page

102

Recommended Citation

XIE, Yuman; TAN, Cong; HUANG, Hongq iao; LUO, Bingxiang; JIA, Zhiwei; and SUN, Chenhao (2025) "Assessment method of smart electricity meter running state based on MFT model," Journal of Electric Power Science and Technology: Vol. 40: Iss. 4, Article 9.
DOI: 10.19781/j.issn.1673-9140.2025.04.009
Available at: https://jepst.researchcommons.org/journal/vol40/iss4/9