Abstract
The growing apprehension regarding greenhouse gas emission accompanied by fossil fuel depletion has instigated the electrification of transportation sector. As a consequence of this Electric Vehicle (EV) has emerged as an environment friendly solution for the automobile industry. For large scale deployment of EVs development of proper charging infrastructure is indispensable. Charging stations (CS) must be placed in the transport network in such a way that the distribution network parameters are least affected. This work proposes a novel approach for co-ordinated planning of EV charging infrastructures considering superimposition of both transport and distribution network. This approach is validated on IEEE 33 bus distribution network superimposed with 25 node road network. The capability of a new hybrid algorithm which is an amalgamation of Chicken Swarm Algorithm (CSO) and Teaching Learning Based Optimization Algorithm (TLBO) is utilized in this work for attaining optimal solution.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2017 Third IEEE International Conference on Research in Computational Intelligence and Communication Networks, ICRCICN 2017 |
| Publisher | IEEE |
| Pages | 84-89 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5386-1931-5 |
| DOIs | |
| Publication status | Published - 2017 |
| MoE publication type | A4 Conference publication |
| Event | International Conference on Research in Computational Intelligence and Communication Networks - Kolkata, India Duration: 3 Nov 2017 → 5 Nov 2017 Conference number: 3 http://icrcicn.in/ |
Conference
| Conference | International Conference on Research in Computational Intelligence and Communication Networks |
|---|---|
| Abbreviated title | ICRCICN |
| Country/Territory | India |
| City | Kolkata |
| Period | 03/11/2017 → 05/11/2017 |
| Internet address |
Keywords
- Distribution network
- CSO
- TLBO
- Hybrid algorithm
- Objective function
- Superimposition
- Transport network