A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms

Basit Öğe Kaydı
dc.authoridPouria Ahmadi / 0000-0001-8829-133X
dc.authorscopusidPouria Ahmadi / 23569183500
dc.authorwosidPouria Ahmadi / G-6879-2013
dc.contributor.authorRajamoorthy, Rajasekaran
dc.contributor.authorArunachalam, Gokulalakshmi
dc.contributor.authorKasinathan, Padmanathan
dc.contributor.authorDevendiran, Ramkumar
dc.contributor.authorAhmadi, Pouria
dc.contributor.authorPandiyan, Santhiya
dc.contributor.authorMuthusamy, Suresh
dc.contributor.authorPanchal, Hitesh
dc.contributor.authorKazem, Hussein A.
dc.contributor.authorSharma, Prabhakar
dc.date.accessioned2022-06-09T13:43:52Z
dc.date.available2022-06-09T13:43:52Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Biyomedikal Mühendisliği Bölümüen_US
dc.description.abstractIntelligent Transport System (ITS) intentions to attain traffic efficiency by diminishing traffic difficulties. It supplies information like traffic issues, real-time traveling information, parking availability, etc., in advance to the users who are connected with the smart cities that ensure travelers' safety and comfort. This ITS technique should merge with Electric Vehicles (EVs) because nowadays, EVs have become familiar in the last decade owing to the requirement to cut greenhouse gas emissions and fossil fuels. However, traffic jams caused by EVs driven to the charging stations (CSs) can result in the complex charging scheduling of EVs. Therefore, an effective algorithm is developed for optimal charging scheduling using the proposed Grey Sail Fish Optimization (GSFO). The proposed charging scheduling algorithm integrates Grey Wolf Optimizer (GWO) and Sail Fish Optimization (SFO). For each EV, the demand when charging is computed. The path used by the EV to travel to the charging station is determined by computing the path decision factor. In comparison to existing techniques, the proposed GSFO-based charging algorithm schedules EVs to charging stations based on the fitness function, and the performance was improved with a traffic density of 26.11 km, a distance of 0.0278 kW, and a power of 2.3377. To be more specific, the proposed GSFO improved when many vehicles were considered.en_US
dc.identifier.citationRajamoorthy, R., Arunachalam, G., Kasinathan, P., Devendiran, R., Ahmadi, P., Pandiyan, S., Muthusamy, S., Panchal, H., Kazem, H.A., Sharma, P. (2022). A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(2), 3555–3575.en_US
dc.identifier.doi10.1080/15567036.2022.2067268en_US
dc.identifier.endpage3575en_US
dc.identifier.issn1556-7036en_US
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85128927565en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage3555en_US
dc.identifier.urihttps://doi.org/10.1080/15567036.2022.2067268
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2856
dc.identifier.volume44en_US
dc.identifier.wosWOS:000794281100001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAhmadi, Pouria
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCISen_US
dc.relation.ispartofENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectElectric Vehicle (EV)en_US
dc.subjectGrey Wolf Optimizer (GWO)en_US
dc.subjectCharging Schedulesen_US
dc.subjectSail Fish Optimization (SFO)en_US
dc.subjectTransport Systemen_US
dc.titleA novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithmsen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
15567036.2022 (1).pdf
Boyut:
8.83 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Biyomedikal Mühendisliği Bölümü Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu