Agent-based Modeling and Simulation on the Electric Vehicle Travelling Ability in the Smart Grid
- 10.2991/ameii-16.2016.1How to use a DOI?
- Intelligent Agent, Modeling and Simulation, Complex System, Electric Vehicle, Travelling Ability
The massive adoption of the electric vehicles in the near future with the rapid development of the smart grid shall significantly affair the resident transportation worldwide, while the modeling and simulation are the key approaches in analyzing the effect of the electrification of the vehicles. This paper firstly analyzed the procedures of the electric vehicles' refueling activities in the smart grid. Moreover, based on the complex adaptive system theory and agent-based modeling methodology, the paper further proposes the electric vehicle model through constructing the state-chart and rule base, and the agent-based electric vehicle model is derived. Furthermore, in order to compare the travelling ability between the electric vehicle and the original vehicle, the simulation platform is constructed and the corresponding interfaces, 3D module as well as the necessary functions are constituted. Based on the platform, this paper proposed two case scenes focus on the original internal combustion engine vehicle and electric vehicle respectively, and the simulation results denotes that the electrification of the vehicle shall reduce the travelling ability and confirms the effectiveness of the proposed model and simulation platform in studying the key phenomenon of the electric vehicles in the smart grid.
- © 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/).
Cite this article
TY - CONF AU - Yan Li AU - Peng Han AU - Jinkuan Wang AU - Xin Song PY - 2016/04 DA - 2016/04 TI - Agent-based Modeling and Simulation on the Electric Vehicle Travelling Ability in the Smart Grid BT - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) PB - Atlantis Press SP - 1 EP - 6 SN - 2352-5401 UR - https://doi.org/10.2991/ameii-16.2016.1 DO - 10.2991/ameii-16.2016.1 ID - Li2016/04 ER -