Abstract
Electric vehicles (EVs) have recently gotten a lot of attention from the government and the auto industry. This is because EVs produce less CO2 and cost less to run and maintain. However, as EV adoption rises, the pressure on the distribution network increases due to changes in power loss, voltage profile, etc. So, EV fast charging stations (FCSs) must be put in the right places for the distribution network to work well. As a result, a two-stage technique is suggested for the deployment of FCSs in this paper. The Land Cost Index (LCI) and the EV Population Index have been taken into consideration while introducing the Charging Station Investor Decision Index (CSIDI) in the first stage (EVPI). Further, the CSIDI was developed to determine the location of FCS in the electrical distribution system while minimizing the cost of land and maximizing the EV population. The distribution system restrictions are considered while formulating an optimization problem in the following step to minimize the overall active power loss. The improved version of the bald eagle search (IBES) algorithm has also been used to solve the minimization issue, and the outcomes have been contrasted with those of the particle swarm optimization (PSO) technique.
| Original language | English |
|---|---|
| Title of host publication | 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350399769 |
| DOIs | |
| State | Published - 2023 |
| Externally published | Yes |
| Event | 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 - Aligarh, India Duration: 10 Feb 2023 → 12 Feb 2023 |
Publication series
| Name | 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 |
|---|
Conference
| Conference | 2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023 |
|---|---|
| Country/Territory | India |
| City | Aligarh |
| Period | 10/02/23 → 12/02/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Algorithm
- Distribution system
- Electric vehicle
- Fast charging station
- optimization
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Automotive Engineering
- Control and Optimization
- Instrumentation
Fingerprint
Dive into the research topics of 'Placement of FCS Considering Power Loss, Land Cost, and EV Population'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver