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dc.contributor.authorBasnet, Saurav Man Singh
dc.contributor.authorJewell, Ward T.
dc.identifier.citationS. M. Basnet and W. Jewell, "Residential Demand Response Program: Virtual Storage Model and Its Optimization," 2018 IEEE Conference on Technologies for Sustainability (SusTech), Long Beach, CA, USA, 2018, pp. 35-42en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractDemand response programs are becoming an integral part of the power system, helping create a closer alignment between the electrical service providers and customers. The research described in this paper uses the residential demand response (DR) program during a peak demand event to determine the demand reduction capacity as a virtual storage (VS). The amount of demand that is reduced due to the demand response program is analogous to the amount of energy discharged by storage to reduce the demand. Since there is no hard storage involved, demand reduction is taken as VS. The aggregator is a third party who communicates between the client (electrical service provider) and customers to utilize the virtual storage capacity. The aggregator provides incentive to customers to take control over their thermostat and receive a reward from the client for load reduction. Incentives must benefit both clients and customers in order for programs to succeed. A mathematical modeling of the load reduction capacity of a demand response program as a virtual storage system and its optimization is presented in this paper.en_US
dc.relation.ispartofseries2018 IEEE Conference on Technologies for Sustainability (SusTech);
dc.subjectDemand responseen_US
dc.subjectDirect load controlen_US
dc.subjectGenetic algorithmen_US
dc.subjectHeating ventilation and air conditioningen_US
dc.subjectThermal integrityen_US
dc.titleResidential demand response program: virtual storage model and its optimizationen_US
dc.typeConference paperen_US
dc.rights.holder© 2018, IEEEen_US

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