Highway Electric Vehicle Charging Load Prediction and its Impact on the Grid
Huiyi Wang, Xueliang Huang, Lixin Chen, Yuqi Zhou
Available Online January 2016.
- https://doi.org/10.2991/ifeea-15.2016.23How to use a DOI?
- highway, electric vehicles, load prediction, Floyd algorithm, Monte Carlo method, the impact on grid.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 2015 2nd International Forum on Electrical Engineering and Automation (IFEEA 2015) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/ifeea-15.2016.23 DO - https://doi.org/10.2991/ifeea-15.2016.23 ID - Wang2016/01 ER -