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dc.contributor.authorLie, Ten_NZ
dc.contributor.authorAhmad, Aen_NZ
dc.contributor.authorAnderson, Ten_NZ
dc.contributor.authorSwain, Aen_NZ
dc.date.accessioned2019-04-09T03:17:32Z
dc.date.available2019-04-09T03:17:32Z
dc.date.copyright2017-10-26en_NZ
dc.identifier.citation2017 Asian Conference on Energy, Power and Transportation Electrification (ACEPT), Singapore, 2017, pp. 1-6. doi: 10.1109/ACEPT.2017.8168591
dc.identifier.urihttp://hdl.handle.net/10292/12431
dc.description.abstractIn this study, the problems of modeling, energy dispatching and Photovoltaic (PV) array energy priorities for a grid connected residential house with PV array and battery storage using model predictive control (MPC) have been investigated. Artificial neural network (ANN) based global solar radiation forecast was used to plan in advance for periods of low sunshine. MPC was able to reduce electricity consumption in the house when solar radiation forecast was unfavorable. Quadratic programming optimization was used to maximize usage of the PV system. Excess energy from the PV array was used to further raise hot water cylinder (HWC) temperature, rather than exporting it to the utility grid. Performance of the overall model predictive control system was verified using simulation results.
dc.publisherIEEE
dc.relation.urihttps://ieeexplore.ieee.org/document/8168591
dc.rightsCopyright © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.subjectBuilding energy management; Model predictive control; Energy efficiency; Photovoltaic energy systems; Solar radiation forecast
dc.titleMaximizing Photovoltaic Array Energy Usage Within a House Using Model Predictive Controlen_NZ
dc.typeConference Contribution
dc.rights.accessrightsOpenAccessen_NZ
pubs.elements-id316406
aut.relation.conferenceAsian Conference on Energy, Power and Transportation Electrification 2017en_NZ


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