An intelligent optimal charging stations placement on the grid system for the electric vehicle application

S.P.R. Swamy Polisetty, R. Jayanthi and M. Sai Veerraju

Energy, 2023, vol. 285, issue C

Abstract: In smart cities, electrified vehicle plays a vital role. Due to the number of electric vehicles increasing rate, the optimised deployment of the charging station without maximum loss and voltage imbalance is required. Many existing strategies studied for the optimal charging station deployment result in higher power utilisation, power loss, harmonic distortion and voltage imbalance. Therefore a novel Dove-based Recursive Deep Network (DbRDN) was planned to implement. The DG grid system is initially created by integrating hybrid wind, solar and hydropower sources. Subsequently, the DbRDN is designed for the optimal location for the placement of the EV charging station by analysing load and line data. Moreover, the efficiency of the developed system is evaluated at both the balanced and unbalanced conditions and the outcomes are computed in terms of power loss, harmonic distortion, voltage imbalance, error and accuracy. The results are compared with prevailing techniques to validate the improvement score.

Keywords: Electric vehicle charging station; Optimal placement; Power loss; Harmonic distortion; Balanced and unbalanced distribution system (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544223028943
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:285:y:2023:i:c:s0360544223028943

DOI: 10.1016/j.energy.2023.129500

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().