Keywords
smart electricity meter, fault analysis, clustering algorithm, cloud theory, data mining
Abstract
The smart electricity meter is an important and sophisticated metrical equipment in smart grid. Its fault types have complicated characteristics of randomness and fuzziness, which have significant impacts on electrical safety of consumer as well as fairness and justness of measurement directly. Therefore, a classification diagnosis cloud model of fault information of smart electricity meter is proposed in order to analyze the randomness and fuzziness of fault data in smart electricity meter and their correlation. In this model, the clustering algorithm is applied, and the cloud theory is employed to conduct data mining. In addition, the weakness and key parts affecting reliable operation of smart electricity meter is also specified. Finally, the abnormal event record of smart electricity meter in a certain area in 2015 is chosen as the data source for analysis. The effectiveness and practicability of the proposed method is verified.
DOI
10.19781/j.issn.16739140.2020.02.022
First Page
163
Last Page
169
Recommended Citation
JIANG, Jianfeng; ZHANG, Yin; TIAN, Shuxin; and YANG, Xijun
(2020)
"Fault data analysis of smart electricity meter based cloud theory,"
Journal of Electric Power Science and Technology: Vol. 35:
Iss.
2, Article 22.
DOI: 10.19781/j.issn.16739140.2020.02.022
Available at:
https://jepst.researchcommons.org/journal/vol35/iss2/22