Prediction of Operating Abnormality Rate of Charging Pile Based on Generalized AR(q) Combined Regression

The stable operation of charging pile is related to the entire operation efficiency of the charging network of electric vehicles so the prediction of charging pile operation abnormality rate can help the operational department to make operational decisions in advance. This paper uses the electric ve...

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Bibliographic Details
Published inMATEC Web of Conferences Vol. 176; p. 1042
Main Authors Xin, Xu, Jun, Fu, Zhijie, Sun, Xuemei, Li, Guopeng, Zhou
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 01.01.2018
Subjects
Electric vehicle charging
Electric vehicles
Predictions
Regression models
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Summary:The stable operation of charging pile is related to the entire operation efficiency of the charging network of electric vehicles so the prediction of charging pile operation abnormality rate can help the operational department to make operational decisions in advance. This paper uses the electric vehicle charging network operating date in the north of Hebei province, based on the feature of the anomalies records of charging pile, to combine the generalized AR(q) model and the regression model and to predict the abnormality rate of electric vehicle charging network in the north of Hebei province. It is predicted that the average absolute error is 0.0044 and the acceptable prediction effect can be obtained.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/201817601042