TY - GEN
T1 - Data-driven prediction of fine-grained EV charging behaviors in public charging stations
T2 - 12th ACM International Conference on Future Energy Systems, e-Energy 2021
AU - Qiao, Fuli
AU - Lin, Shan
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/6/22
Y1 - 2021/6/22
N2 - With the rapid growth of electrical vehicle public charging stations, accurate predictions of local charging demand enable many prospective applications. In this paper, we explore a data-driven approach to predict future charging demand, and build predictive models to characterize behaviors of both registered long-term users and unregistered short-term users. With a real-world dataset of 28053 records over 798 days at multiple locations, evaluation results demonstrate that our model with XGBoost outperforms existing solutions, reducing the prediction error up to 40.8% at the finest time granularity (15-minute interval).
AB - With the rapid growth of electrical vehicle public charging stations, accurate predictions of local charging demand enable many prospective applications. In this paper, we explore a data-driven approach to predict future charging demand, and build predictive models to characterize behaviors of both registered long-term users and unregistered short-term users. With a real-world dataset of 28053 records over 798 days at multiple locations, evaluation results demonstrate that our model with XGBoost outperforms existing solutions, reducing the prediction error up to 40.8% at the finest time granularity (15-minute interval).
KW - EV charging prediction
KW - machine learning
KW - user behaviors
UR - https://www.scopus.com/pages/publications/85109331151
U2 - 10.1145/3447555.3466567
DO - 10.1145/3447555.3466567
M3 - Conference contribution
AN - SCOPUS:85109331151
T3 - e-Energy 2021 - Proceedings of the 2021 12th ACM International Conference on Future Energy Systems
SP - 276
EP - 277
BT - e-Energy 2021 - Proceedings of the 2021 12th ACM International Conference on Future Energy Systems
PB - Association for Computing Machinery, Inc
Y2 - 28 June 2021 through 2 July 2021
ER -