Εμφάνιση απλής εγγραφής

dc.creatorKoutsopoulos I., Papaioannou T.G., Hatzi V.en
dc.date.accessioned2023-01-31T08:46:22Z
dc.date.available2023-01-31T08:46:22Z
dc.date.issued2016
dc.identifier10.1561/1300000042
dc.identifier.issn1554057X
dc.identifier.urihttp://hdl.handle.net/11615/75426
dc.description.abstractThe smart energy grid has evolved into a complex ecosystem, with new entering actors such as aggregators, and traditional ones like consumers, operators and generators having fundamentally different, active roles in the system. In addition, advances in key technologies such as renewables, energy storage, communication and control have paved the way to new research directions and problems. In this work we attempt to give some structure to the complex ecosystem above, and we present key research problems that shape the area. The emphasis is on the control and optimization methodology toward approaching these problems. The first thread we consider is demand-response where the central theme is to optimize the demand load of consumers. The basic problem is the scheduling of demand load of consumers with the aim to minimize a cost function from the point of view of the utility operator or the consumer. Next, we review fundamental problems in energy storage management. The basic energy storage management problem amounts to deciding when and how much to charge and discharge the battery in order to achieve a certain optimization objective, either in terms of a generation cost or a mismatch between energy demand and supply, which again may capture the goals of the consumer or the utility. We also discuss the market interactions of various entities in the smart grid ecosystem and the impact of their strategic decisions on the market structure. Finally, we study key aspects of consumer behavior such as response to gamification models, and uncertainty due to consumer decisions that influence the system, and we discuss the role of data in building data-driven models for predicting consumer behavior. For each problem instance above, we provide an exposition that places emphasis on the related model and on key aspects of the analysis. © 2016 I. Koutsopoulos, T. P. Papaioannou, and V. Hatzi.en
dc.language.isoenen
dc.sourceFoundations and Trends in Networkingen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84976298016&doi=10.1561%2f1300000042&partnerID=40&md5=86f624b0b13854657564825f1df2a2b5
dc.subjectCommerceen
dc.subjectCost functionsen
dc.subjectDigital storageen
dc.subjectEcologyen
dc.subjectEcosystemsen
dc.subjectElectric power transmission networksen
dc.subjectEnergy storageen
dc.subjectSmart power gridsen
dc.subjectStorage managementen
dc.subjectCharge and dischargeen
dc.subjectCommunication and controlen
dc.subjectComplex ecosystemsen
dc.subjectControl and optimizationen
dc.subjectMarket interactionsen
dc.subjectModeling and optimizationen
dc.subjectResearch problemsen
dc.subjectStrategic decisionsen
dc.subjectConsumer behavioren
dc.subjectNow Publishers Incen
dc.titleModeling and optimization of the smart grid ecosystemen
dc.typejournalArticleen


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