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dc.contributor.authorSeddig, Katrin
dc.date.accessioned2021-02-17T08:47:51Z
dc.date.available2021-02-17T08:47:51Z
dc.date.issued2021
dc.date.submitted2021-02-11T17:58:46Z
dc.identifierONIX_20210211_9783731510314_77
dc.identifierOCN: 1240532418
dc.identifierhttps://library.oapen.org/handle/20.500.12657/46708
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/63676
dc.description.abstractIn this book, a model is developed which can be used to identify the load shifting potential of electric vehicle fleets considering the integration of photovoltaic generation and uncertainty. Different approaches using simulation, deterministic and stochastic optimization are developed to schedule the charging of three different electric vehicle fleets at a common charging infrastructure under uncertainty.
dc.languageGerman
dc.relation.ispartofseriesProduktion und Energie
dc.rightsopen access
dc.subject.otherElektromobilität
dc.subject.otherE-Flotten
dc.subject.otherPhotovoltaik
dc.subject.otherUnsicherheit
dc.subject.otherOptimierungsmodell
dc.subject.otherelectromobility
dc.subject.othere-fleets
dc.subject.otherphotovoltaics
dc.subject.otheruncertainty
dc.subject.otheroptimization model
dc.subject.otherthema EDItEUR::K Economics, Finance, Business and Management::KC Economics
dc.titleElektromobile Flotten im lokalen Energiesystem mit Photovoltaikeinspeisung unter Berücksichtigung von Unsicherheiten
dc.typebook
oapen.identifier.doi10.5445/KSP/1000118692
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2
oapen.relation.isbn9783731510314*
oapen.collectionAG Universitätsverlage
oapen.pages218
oapen.place.publicationKarlsruhe
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
dc.seriesnumber34
dc.abstractotherlanguageIn this book, a model is developed which can be used to identify the load shifting potential of electric vehicle fleets considering the integration of photovoltaic generation and uncertainty. Different approaches using simulation, deterministic and stochastic optimization are developed to schedule the charging of three different electric vehicle fleets at a common charging infrastructure under uncertainty.
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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open access
Except where otherwise noted, this item's license is described as open access