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dc.contributor.authorMomber, Ilan
dc.contributor.authorSiddiqui, Afzal
dc.contributor.authorGómez, Tómas
dc.contributor.authorSöder, Lennart
dc.date.accessioned2017-12-02T14:53:01Z
dc.date.available2017-12-02T14:53:01Z
dc.date.issued2015
dc.identifier.doi10.1109/TPWRS.2014.2330375
dc.identifier.urihttp://hdl.handle.net/20.500.12127/5092
dc.description.abstractResearch on electric power systems has considered the impact of foreseeable plug-in electric vehicle (PEV) penetration on its regulation, planning, and operation. Indeed, detailed treatment of PEV charging is necessary for efficient allocation of resources. It is envisaged that a coordinator of charging schedules, i.e., a PEV aggregator, could exercise some form of load control according to electricity market prices and network charges. In this context, it is important to consider the effects of uncertainty of key input parameters to optimization algorithms for PEV charging schedules. However, the modeling of the PEV aggregator's exposure to profit volatility has received less attention in detail. Hence, this paper develops a methodology to maximize PEV aggregator profits taking decisions in day-ahead and balancing markets while considering risk aversion. Under uncertain market prices and fleet mobility, the proposed two-stage linear stochastic program finds optimal PEV charging schedules at the vehicle level. A case study highlights the effects of including the conditional value-at-risk (CVaR) term in the objective function and calculates two metrics referred to as the expected value of aggregation and flexibility.
dc.language.isoen
dc.subjectVehicles
dc.subjectUncertainty
dc.subjectStochastic Processes
dc.subjectSystem-on-chip
dc.subjectElectricity Supply Industry
dc.subjectPower Systems
dc.subjectAvailability
dc.titleRisk averse scheduling by a PEV aggregator under uncertainty
dc.identifier.journalIEEE Transactions on Power Systems
dc.source.volume30
dc.source.issue2
dc.source.beginpage882
dc.source.endpage891
vlerick.knowledgedomainEntrepreneurship
vlerick.typearticleJournal article with impact factor
vlerick.vlerickdepartmentEGS
dc.identifier.vperid182572
dc.identifier.vperid179805
dc.identifier.vperid182570
dc.identifier.vperid182573
dc.identifier.vpubid6326


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