Abstract
In recent years, China's electric vehicle industry and related infrastructure construction has entered a phase of rapid development, large-scale electric vehicle charging has become a practical problem in the grid operation and planning. The electric vehicle (EV) charging system is a complex adaptive system (CAS). We presented a multi-agent-based EV charging simulation system on SWARM platform for studying the impact of the large-scale electric vehicles integration into the power grid. We constructed two kinds of agents: the electric vehicle agent and the charging utility agent, and build the transportation and grid environments. We simulated the interaction among the agents, and that among the agents and the environments. The agents continuously optimize their decisions according to their learning. The results show that the simulation could reflects the actual EV charging conditions through the interaction modeling among the EV, charging utility, power grid and the transportation network. This provides a convenient tool for further studying of the EV related problems.
| Original language | English |
|---|---|
| Pages (from-to) | 68-77 |
| Number of pages | 10 |
| Journal | Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering |
| Volume | 32 |
| Issue number | 31 |
| Publication status | Published - 5 Nov 2012 |
| Externally published | Yes |
Keywords
- Complex adaptive system
- Electric vehicle
- Multi-agent system
- SWARM
- Simulation