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Intelligent optimization for charging scheduling of electric vehicle using exponential Harris Hawks technique

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dc.citedby6
dc.contributor.authorDevendiran R.en_US
dc.contributor.authorKasinathan P.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorSubramaniam U.en_US
dc.contributor.authorGovindarajan U.en_US
dc.contributor.authorFernando X.en_US
dc.contributor.authorid56142031000en_US
dc.contributor.authorid57194393495en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid57199091461en_US
dc.contributor.authorid6603473566en_US
dc.contributor.authorid6701314089en_US
dc.date.accessioned2023-05-29T09:05:54Z
dc.date.available2023-05-29T09:05:54Z
dc.date.issued2021
dc.descriptionCharging (batteries); Electric vehicles; Scheduling; Secondary batteries; Economic contribution; Electric Vehicles (EVs); Exponential weighted moving average; Green transportations; Intelligent optimization; Intelligent techniques; Optimization strategy; Transportation system; Vehicular ad hoc networksen_US
dc.description.abstractThe coordination of modern transportation system depends heavily on intelligent techniques, information assortment, and its analysis. Sensors play a crucial role in information assortment in charging scheduling of electric vehicles (EVs). EVs are destined to become inevitable due to their innate economic contribution, climate improvement, and social attributes as per United Nation's sustainable development goals. Innovation in EV has gained the interest of many researchers since it is one of the novel green transportation sectors. Moreover, EVs are essential to preserve conventional fuels and to maximize the utilization of renewable sources. Nevertheless, EVs have short driving ranges due to their battery limitation, which hinders the reliability. The charging stations (CS) for EVs are also unevenly distributed. This paper presents a novel strategy to schedule the charging points in EV CSs. The goal is to determine the convenient CS for EVs through Vehicular Ad-hoc Network (VANET) model. In this model, the CSs are determined and prioritized using four phases, such as driving, charge planning, charging scheduling, and battery charging. Charging scheduling was designed using a newly developed optimization strategy, exponential Harris Hawks optimization (Exponential HHO) algorithm, which combines two algorithms, Harris Hawks optimization (HHO) and exponential weighted moving average (EWMA). Furthermore, the fitness function was also newly devised by considering parameters such as average waiting time, remaining energy, number of EVs, and distance. The proposed Exponential HHO was validated using VANET simulation and the performance was improved with maximum remaining energy of 52.709 Whr, minimal distance of 27.256 km, and a maximum average waiting time of 0.352 min in comparison with existing methods. To be specific, the proposed Exponential HHO yielded better improvement, especially when considering a large number of vehicles. � 2021 Wiley Periodicals LLCen_US
dc.description.natureFinalen_US
dc.identifier.doi10.1002/int.22531
dc.identifier.epage5844
dc.identifier.issue10
dc.identifier.scopus2-s2.0-85107344732
dc.identifier.spage5816
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85107344732&doi=10.1002%2fint.22531&partnerID=40&md5=3994a07301756a8492f72bcf7685258b
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25984
dc.identifier.volume36
dc.publisherJohn Wiley and Sons Ltden_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Intelligent Systems
dc.titleIntelligent optimization for charging scheduling of electric vehicle using exponential Harris Hawks techniqueen_US
dc.typeArticleen_US
dspace.entity.typePublication
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