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Uncertainty-Aware Planning of EV Charging Infrastructure and Renewable Integration in Distribution Networks: A Review

datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.fosEngenharia e Tecnologia::Outras Engenharias e Tecnologias
datacite.subject.sdg12:Produção e Consumo Sustentáveis
datacite.subject.sdg13:Ação Climática
dc.contributor.authorTripathy, Sasmita
dc.contributor.authorFahnbulleh, Edwin Boima
dc.contributor.authorGhatak, Sriparna Roy
dc.contributor.authorLopes, Fernando
dc.contributor.authorAcharjee, Parimal
dc.date.accessioned2026-04-22T14:09:03Z
dc.date.available2026-04-22T14:09:03Z
dc.date.issued2026-02
dc.description.abstractABSTRACT: Transitioning from internal combustion engines to electric vehicles (EVs) is critical for fighting climate change. This requires widespread adoption of Electric Vehicle Charging Stations (EVCSs). Integrating EVCSs and renewable energy sources (RESs) into distribution networks (DNs) is vital for a sustainable transportation system while enhancing power generation in an environmentally friendly manner. This review explores challenges and opportunities of EVCS and RES integration, concentrating on EV charging-demand uncertainty modeling, forecasting algorithms, planning techniques, and the impacts on DN. It discusses forecasting algorithms in terms of learning-based and non-learning-based methods. EVCS planning algorithms are also discussed, involving deterministic and stochastic methods. The technical, environmental, reliability, and economic impacts of EVCS-RES on DNs are discussed. It explores optimization strategies to minimize these impacts, incorporating them as objective functions. Additionally, the survey examines the methods of incorporating EVs and RES in DN, optimizing EVCS allocation while addressing EVCS impacts on voltage regulation, power loss, and network reliability. The importance of energy management systems and advanced forecasting techniques in balancing power fluctuation and improving efficiency is emphasized. Finally, it identifies open problems and future directions for forecasting and optimizing EVCS-RES integration in the networks. These findings are highly relevant for designing resilient and efficient modern power systems that leverage RES and EVCS in the grids.eng
dc.identifier.citationTripathy, S., Fahnbulleh, E. B., Ghatak, S. R., Lopes, F., & Acharjee, P. (2026). Uncertainty-Aware Planning of EV Charging Infrastructure and Renewable Integration in Distribution Networks: A Review. In: Energies, 2026, vol. 19(5), article 1131. https://doi.org/10.3390/en19051131
dc.identifier.doi10.3390/en19051131
dc.identifier.eissn1996-1073
dc.identifier.urihttp://hdl.handle.net/10400.9/6352
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relation.hasversionhttps://www.mdpi.com/1996-1073/19/5/1131
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectRenewable energy sources
dc.subjectDistribution network
dc.subjectCharging station
dc.subjectElectric vehicle
dc.subjectUncertainty
dc.subjectOptimization
dc.subjectDistribution systems
dc.subjectEnergy management
dc.titleUncertainty-Aware Planning of EV Charging Infrastructure and Renewable Integration in Distribution Networks: A Revieweng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue5
oaire.citation.titleEnergies
oaire.citation.volume19
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameTripathy
person.familyNameLopes
person.givenNameSasmita
person.givenNameFernando
person.identifier.orcid0009-0005-5459-9199
person.identifier.orcid0000-0002-2967-627X
relation.isAuthorOfPublicationa4406e33-b959-4b8b-a2c5-cc6ab9efd4a9
relation.isAuthorOfPublicationa1153343-c1b9-406e-a83a-30dbee18d6a3
relation.isAuthorOfPublication.latestForDiscoverya4406e33-b959-4b8b-a2c5-cc6ab9efd4a9

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