A novel modified tunicate swarm algorithm for optimal charge scheduling and pricing of electric vehicles with user priority‐based charging station selection. (16th December 2022)

• Record Type: Journal Article
• Authors: Nair, Lakshmi M.; D. M., Mary Synthia Regis Prabha
• Is Part Of: Concurrency and computation. Volume 35:Number 3(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-16
• Subjects: charge scheduling -- EV -- optimal pricing -- priority based charger allocation -- tunicate swarm algorithm; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.7494
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: In recent days, electric vehicles (EVs) are seen as a viable transportation alternative by industry people to minimize the greenhouse gas emissions problems of regular fuel vehicles. While EVs' performance is limited due to their restricted battery power, charging wait for service, and high resource costs, they are still a viable option. To enhance the EV's performance, this work introduced an optimized priority‐based charge scheduling with dynamic pricing model. For this, a novel modified tunicate swarm algorithm method, which is the enhanced form of the standard tunicate swarm algorithm, is proposed. When an EV arrives at the charging station, the EV user is permitted to choose the type of charging based on his/her requirements. In general, when charging EVs in public stations or during peak hours, customers must be patient and wait for significant periods of time. The introduced model ignores this negative effect. EV users have also mentioned the issue of controlled charging rates as a key barrier. This is a difficult task, but it is accomplished in this study, which optimizes total charge costs. Finally, the results acquired are discussed under overall cost and energy consumption.