Abstract
Electric vehicles (EV) is a promising solution for reducing the environment adverse effect of road transport. In this study, a multi-objective, multi-stage collaborative planning model is proposed for the integrated EV charging stations and power distribution network. The proposed model aims to minimize the investment & operation costs of the distribution system and maximize the annually captured traffic flow. The uncertainties for both slow charging load and fast charging load are considered. The MOEA/D algorithm is employed to find the Pareto frontier of the proposed model. Simulations based on a case study of a 54-node distribution system and a 25-node traffic network system proves the effectiveness of proposed method.
| Original language | English |
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| Title of host publication | 2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 |
| Publisher | IEEE |
| Pages | 503-508 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509040759 |
| DOIs | |
| Publication status | Published - 8 Dec 2016 |
| Event | 7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 - Sydney, Australia Duration: 6 Nov 2016 → 9 Nov 2016 |
Conference
| Conference | 7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 |
|---|---|
| Country/Territory | Australia |
| City | Sydney |
| Period | 6/11/16 → 9/11/16 |
Keywords
- charging station
- distribution system planning
- Electric vehicle
- multi-objective optimization
- vehicle-to-grid
ASJC Scopus subject areas
- Computer Networks and Communications
- Energy Engineering and Power Technology
- Control and Optimization
- Signal Processing