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A hybrid model predictive control scheme for energy and cost savings in commercial buildings: simulation and experiment

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dc.contributor.authorHuang, H.
dc.contributor.authorChen, L.
dc.contributor.authorHu, E.
dc.contributor.conference2015 American Control Conference (ACC) (1 Jul 2015 - 3 Jul 2015 : Chicago, USA)
dc.date.issued2015
dc.description.abstractThis paper presents a hybrid model predictive control (MPC) scheme for energy-saving control in commercial buildings. The proposed method combines a linear MPC with a neural network feedback linearisation (NNFL) method. The control model for the linear MPC is developed using a simplified physical model, while nonlinearities associated with the building system are handled by an affine recurrent neural network (ARNN) model through system feedback. The proposed MPC integrates several advanced air-conditioning control strategies, such as an economizer control, an optimal start-stop control, and a pre-cooling control. The developed MPC has been tested in the check-in hall of T-1 building, Adelaide Airport, through both simulation and field experiment. The result shows that the proposed control scheme can achieve a considerable amount of savings without violating occupants’ thermal comfort.
dc.description.statementofresponsibilityHao Huang, Lei Chen, and Eric Hu
dc.identifier.citationProceedings of the ... American Control Conference. American Control Conference, 2015, vol.2015-July, pp.256-261
dc.identifier.doi10.1109/ACC.2015.7170745
dc.identifier.isbn9781479986859
dc.identifier.issn0743-1619
dc.identifier.issn2378-5861
dc.identifier.orcidChen, L. [0000-0002-2269-2912]
dc.identifier.orcidHu, E. [0000-0002-7390-0961]
dc.identifier.urihttp://hdl.handle.net/2440/93470
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofseriesProceedings of the American Control Conference
dc.rights© 2015 AACC
dc.source.urihttps://doi.org/10.1109/acc.2015.7170745
dc.titleA hybrid model predictive control scheme for energy and cost savings in commercial buildings: simulation and experiment
dc.typeConference paper
pubs.publication-statusPublished

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