Open AccessResearch on driving current prediction method based on ARIMA
Author(s) -
Yuan Zhou,
Guofu Wei,
Yingnan Liu,
Guoxin Zhang
Publication year - 2021
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 - 10.1088/1742-6596/1865/2/022044
Subject(s) - autoregressive integrated moving average , current (fluid) , computer science , alarm , signal (programming language) , time series , engineering , electrical engineering , machine learning , programming language
The abnormal driving current of DC measuring device is sometimes covered by the fluctuation of normal monitoring signal, which is difficult to identify by traditional operation and maintenance monitoring panel and abnormal alarm means. In order to solve the above problems, a prediction and trend analysis algorithm model of ARIMA is proposed to predict the change trend of driving current, realize the prediction of driving current in the next 8 hours, and analyze whether there is a growth trend of driving current by using the change rate. The practicability of the proposed method is verified by the analysis of the actual operation monitoring data of converter station, which can be applied to the trend analysis of driving current in DC measurement system.