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  • 标题:Prediction of Operating Abnormality Rate of Charging Pile Based on Generalized AR(q) Combined Regression
  • 本地全文:下载
  • 作者:Xu Xin ; Fu Jun ; Sun Zhijie
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:176
  • DOI:10.1051/matecconf/201817601042
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要: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.
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