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dc.contributor.authorDietrich, Kristines-ES
dc.contributor.authorLatorre Canteli, Jesús Maríaes-ES
dc.contributor.authorOlmos Camacho, Luises-ES
dc.contributor.authorRamos Galán, Andréses-ES
dc.date.accessioned2016-10-18T12:05:37Z-
dc.date.available2016-10-18T12:05:37Z-
dc.identifier.urihttp://hdl.handle.net/11531/14204-
dc.description.abstractes-ES
dc.description.abstractElectric loads offer a great flexibility resource for electric systems. The exploitation of this resource may be necessary not only to reduce system variable costs but also to integrate high amounts of renewable energies. Demand Response (DR) mechanisms, in which demands reduce, increase or shift consumption, must be implemented to use this inherent flexibility. We use a two-part model consisting of a day-ahead unit commitment and a real-time simulation to represent a centralized approach of Direct Load control for residential and commercial consumption. Two parameters of the DR mechanism are especially interesting for its performance and will be analyzed in detail. First, DR potential, which indicates the share of total hourly consumption that can be modified. Second, the cost which incur consumers to change their electricity consumption. We find a lower impact of using various devices at once than summing up individual impacts of each device. Thus, concentrating on few devices with high DR potential coinciding with hours adjacent to peak or off-peak hours may increase the effectiveness of DR. Furthermore, we come up with positive net benefits to consumers when considering DR costs, but in practice these may result too low to persuade consumers to participate in DR programs.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.titleDemand response mechanism design and the impact of crucial parameters on its effectivenesses_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES
dc.description.versioninfo:eu-repo/semantics/draftes_ES
dc.rights.holderes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.keywordses-ES
dc.keywordsDemand Response, Load management, Power system modelingen-GB
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