Open AccessResearch on the Method of Improving the Quality of Electric Energy Measurement Data
Author(s) -
Bing Sui,
Xiao Chen,
Zeng Shou,
Wang Hongzhe,
Zhitong Guo
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012092
Subject(s) - reliability engineering , index (typography) , power quality , computer science , data mining , data quality , series (stratigraphy) , time series , power grid , quality (philosophy) , energy (signal processing) , power (physics) , statistics , engineering , mathematics , paleontology , metric (unit) , operations management , physics , quantum mechanics , machine learning , world wide web , biology , philosophy , epistemology
In the process of collecting data in the power grid harmonic monitoring and analysis system, changes in load, operating modes, and equipment failures will cause data changes. For the strong correlation index, this paper establishes a mathematical model of the monitoring value for the measurement index, while for the weak correlation index, considering that the monitoring data is a type of time series data, a time series model of the monitoring value for the measurement index can be established, and then the abnormal value monitoring is performed by statistical methods. Moreover, experiments prove that the research method used in the paper to detect whether abnormal data exists in the data can effectively improve the efficiency and provide a guarantee for the quality of data monitoring.