2012
DOI: 10.1016/j.rser.2012.02.019
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Grid integration of intermittent renewable energy sources using price-responsive plug-in electric vehicles

Abstract: Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in… Show more

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Cited by 191 publications
(99 citation statements)
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“…Vehicles are modeled as agents receiving a control signal that consists of a price forecast of the electricity auction and an individual price component depending on the transformer utilization of a distributed grid [38]. A graph search optimization algorithm is used to find the charging spots with the lowest price [5].…”
Section: Simulation Methodsmentioning
confidence: 99%
“…Vehicles are modeled as agents receiving a control signal that consists of a price forecast of the electricity auction and an individual price component depending on the transformer utilization of a distributed grid [38]. A graph search optimization algorithm is used to find the charging spots with the lowest price [5].…”
Section: Simulation Methodsmentioning
confidence: 99%
“…The PEVs' contribution to enhance the intermittent RESs integration in the electric grid depends on technical factors such as storage capacity, the capacity connected to the grid and the driving behavior. The above mentioned issues determine the available energy for load shifting and also influence the economic and social aspects of participating in load shifting program [104]. PHEVs and PEVs are able to balance the variations of thermal units loading through altering the grid load profile and also providing an appreciable storage to the system.…”
Section: -Wind With Phevsmentioning
confidence: 99%
“…DSM and increased PEV demand together increase the share of RES (7.38% versus 1.40%). DSM reduces the peak load and balances the intermittency in the grid (see [12]). However, with the given power plant park, DSM also increases total CO 2 emissions.…”
Section: Scenario 1: -Least Marginal Cost Dispatchmentioning
confidence: 99%