Highway Electric Vehicle Charging Load Prediction and its Impact on the Grid

DOI

10.2991/ifeea-15.2016.23How to use a DOI?

Keywords

highway, electric vehicles, load prediction, Floyd algorithm, Monte Carlo method, the impact on grid.

Abstract

In this passage, a new method is proposed to predict the load of electric vehicles (EVs) on highway. In this method, a simplified highway network containing charging stations is established, based on which we can generate an adjacency matrix. Then the origin and destination (OD) of vehicles are extracted according to the probability density function (PDF) built by the statistic of highway toll station. Floyd algorithm is used to determine the routine of EVs. Departure time, state of charge (SOC), battery capacity, driving speed and other parameters are all extracted according to PDF. Monte Carlo method is attached to simulate large-scale EV load on highway. Highway network of Jiangsu province is proposed as an example, and impact of EV load on power grid is evaluated by voltage deviation and loss.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huiyi Wang
AU  - Xueliang Huang
AU  - Lixin Chen
AU  - Yuqi Zhou
PY  - 2016/01
DA  - 2016/01
TI  - Highway Electric Vehicle Charging Load Prediction and its Impact on the Grid
BT  - Proceedings of the 2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015)
PB  - Atlantis Press
SP  - 110
EP  - 116
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifeea-15.2016.23
DO  - 10.2991/ifeea-15.2016.23
ID  - Wang2016/01
ER  -