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User-Constrained Algorithms for Aggregate Residential Demand Response Programs with Limited Feedback.

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dc.contributor.author Gray, Adam Charles
dc.date.accessioned 2015-03-27T22:20:18Z
dc.date.available 2015-03-27T22:20:18Z
dc.date.copyright 2015 en_US
dc.date.issued 2015-03-27
dc.identifier.uri http://hdl.handle.net/1828/5937
dc.description.abstract This thesis presents novel algorithms and a revised modeling framework to evaluate residential aggregate electrical demand response performance under scenarios with limited device-state feedback. These algorithms permit the provision of balancing reserves, or the smoothing of variable renewable energy generation, via an externally supplied target trajectory. The responsive load populations utilized were home heat pumps and deferred electric vehicle charging. As fewer devices in a responsive population report their state information, the error of the demand response program increases moderately but remains below 8%. The associated error of the demand response program is minimized with responsive load populations of approximately 4500 devices; the available capacity of the demand response system scales proportionally with population size. The results indicate that demand response programs with limited device-state feedback may provide a viable option to reduce overall system costs and address privacy concerns of individuals wishing to participate in a demand response program. en_US
dc.language English eng
dc.language.iso en en_US
dc.rights.uri http://creativecommons.org/publicdomain/zero/1.0/ *
dc.subject Demand Response en_US
dc.subject Smart Grid en_US
dc.subject Plug-in Electric Vehicles en_US
dc.subject BC Hydro en_US
dc.subject Electrical Generation en_US
dc.subject Renewable Energy en_US
dc.subject Wind Turbines en_US
dc.subject Limited Feedback Control en_US
dc.subject user-constrained algorithms en_US
dc.title User-Constrained Algorithms for Aggregate Residential Demand Response Programs with Limited Feedback. en_US
dc.type Thesis en_US
dc.contributor.supervisor Crawford, Curran
dc.degree.department Department of Mechanical Engineering en_US
dc.degree.level Master of Applied Science M.A.Sc. en_US
dc.rights.temp Available to the World Wide Web en_US
dc.description.scholarlevel Graduate en_US


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