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dc.contributor.authorMartín Martínez, Franciscoes-ES
dc.contributor.authorSánchez Miralles, Alvaroes-ES
dc.date.accessioned2025-11-21T05:09:37Z
dc.date.available2025-11-21T05:09:37Z
dc.identifier.urihttp://hdl.handle.net/11531/107288
dc.description.abstractThis paper explores the participation of an Independent Aggregator (IA) managing energy resources of residential prosumers in both the energy and secondary reserve markets and analyses the resulting impacts on the electricity supplier. A two-stage optimization model is proposed to exploit the flexibility of the prosumers. The aim is to determine the optimized baseline in the energy market considering the retailer tariffs and to determine the optimal secondary reserve bids to minimize the net cost of the prosumer buying and selling energy. Two types of equipment and two tariff schemes are evaluated to assess their revenue potential in the Spanish secondary reserve market. Numerical results demonstrate that both prosumers and the IA consistently benefit from market participation. Residential users can reduce their energy bills by 19 to 43. Finally, the results indicate that the IA can capture up to 80 of market revenues if rebound costs are mitigated.es-ES
dc.description.abstractThis paper explores the participation of an Independent Aggregator (IA) managing energy resources of residential prosumers in both the energy and secondary reserve markets and analyses the resulting impacts on the electricity supplier. A two-stage optimization model is proposed to exploit the flexibility of the prosumers. The aim is to determine the optimized baseline in the energy market considering the retailer tariffs and to determine the optimal secondary reserve bids to minimize the net cost of the prosumer buying and selling energy. Two types of equipment and two tariff schemes are evaluated to assess their revenue potential in the Spanish secondary reserve market. Numerical results demonstrate that both prosumers and the IA consistently benefit from market participation. Residential users can reduce their energy bills by 19 to 43. Finally, the results indicate that the IA can capture up to 80 of market revenues if rebound costs are mitigated.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.titleAssessing Revenue Potential of Demand-Side Flexibility in the Residential Sectores_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES
dc.description.versioninfo:eu-repo/semantics/draftes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordsDemand response, buildings flexibility, profitability analysis.es-ES
dc.keywordsDemand response, buildings flexibility, profitability analysis.en-GB


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