Hybrid genetic algorithm-simulated annealing based electric vehicle charging station placement for optimizing distribution network resilience

Boya Anil Kumar, B. Jyothi, Arvind R. Singh, Mohit Bajaj*, Rajkumar Singh Rathore, Milkias Berhanu Tuka*

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

7 Dyfyniadau (Scopus)
4 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

Rapid placement of electric vehicle charging stations (EVCSs) is essential for the transportation industry in response to the growing electric vehicle (EV) fleet. The widespread usage of EVs is an essential strategy for reducing greenhouse gas emissions from traditional vehicles. The focus of this study is the challenge of smoothly integrating Plug-in EV Charging Stations (PEVCS) into distribution networks, especially when distributed photovoltaic (PV) systems are involved. A hybrid Genetic Algorithm and Simulated Annealing method (GA-SAA) are used in the research to strategically find the optimal locations for PEVCS in order to overcome this integration difficulty. This paper investigates PV system situations, presenting the problem as a multicriteria task with two primary objectives: reducing power losses and maintaining acceptable voltage levels. By optimizing the placement of EVCS and balancing their integration with distributed generation, this approach enhances the sustainability and reliability of distribution networks.
Iaith wreiddiolSaesneg
Rhif yr erthygl7637
CyfnodolynScientific Reports
Cyfrol14
Rhif cyhoeddi1
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 1 Ebr 2024

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