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http://10.1.7.192:80/jspui/handle/123456789/12468
Title: | Performance Analysis of Distribution System with Optimal Allocation of EV Charging Station |
Authors: | Kacha, Anantkumar Jivanlal |
Keywords: | Electrical 2022 Project Report Project Report 2022 Electrical Project Report 22MEE 22MEEV 22MEEV02 EVT 2022 EE (EVT) Electric Vehicular Technology |
Issue Date: | 1-Jun-2024 |
Publisher: | Institute of Technology |
Series/Report no.: | 22MEEV02; |
Abstract: | The electric vehicle (EV) market is rapidly increasing in this era, because of its lower operating as well as maintenance costs other to conventional vehicles on the EV owner side as well as globally reduced carbon emissions. As per the no. of EVs increases the load requirement in the grid also increases. This additional load puts stress on the grid in particular peak demand hours and also faces some power quality issues like voltage fluctuation in the grid. This issue also affects charging station operation. Through appropriate energy management strategies used in EV charging stations, these issues can be overcome. The initial objective of this project is to appropriate a literature survey about advanced energy management strategies for EV charging stations. Through this literature survey, learn the importance of appropriate allocation of EV-CS and decide the objective of the project. To achieve this objective, a comprehensive analysis of PSO, GA, BOA algorithms, and load flow techniques are studied. The Backward-Forward sweep technique was utilized for LFA analysis to determine the allocation of EV charging stations thought two case studies. The IEEE-33 and IEEE-69 bus RD network system is utilized to test the effects of the given method. The MATLAB coding was used to analyze the proposed algorithms. By comparing the performance of PSO, GA, and BOA algorithms, BOA produces superior results and converges more quickly than PSO and GA. |
URI: | http://10.1.7.192:80/jspui/handle/123456789/12468 |
Appears in Collections: | Dissertation, EE (EVT) |
Files in This Item:
File | Description | Size | Format | |
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22MEEV02.pdf | 22MEEV02 | 5.79 MB | Adobe PDF | View/Open |
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