| Issue |
E3S Web Conf.
Volume 309, 2021
3rd International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2021)
|
|
|---|---|---|
| Article Number | 01097 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202130901097 | |
| Published online | 07 October 2021 | |
Crowd sourced smart EV charging station network using ML
1 G. Narayanamma Institute of Technology and Science, Dept. of Information Technology, Hyderabad, Telangana, India
2 Gokaraju Rangaraju Institute of Engineering & Technology, Department of Electronics and Communications Engineering, Bachupally, Hyderabad, India
3 Gokaraju Rangaraju Institute of Engineering & Technology, Department of Humanities and Sciences, Bachupally, Hyderabad, India
Electric vehicle owners face the problem of having limited charging station options. Individual charging stations near households can act as a viable solution to solve this problem. A forecasting model which can effectively predict the power consumption of a charging station will help charging station owners get a clear view of how much energy to produce.With this intent, this paper proposes an Internet of Things (IoT) based charging station network that acts as a platform to provide charging to electric vehicles and a model based on ARIMA whose learners are fitted to the charging station subsets with optimum parameters to increase the overall performance of sales prediction. The proposed model predicted power consumption for 7 charging stations, with average MAPE, RMSE and R2 values of 12.88%, 5.67, and 0.79 respectively.
© The Authors, published by EDP Sciences, 2021
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