Modelling and predictive control techniques for building heating systems

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dc.contributor.advisor Lightbody, Gordon en
dc.contributor.author O'Dwyer, Edward
dc.date.accessioned 2017-01-16T15:32:16Z
dc.date.available 2017-01-16T15:32:16Z
dc.date.issued 2016
dc.date.submitted 2016
dc.identifier.citation O'Dwyer, E. 2016. Modelling and predictive control techniques for building heating systems. PhD Thesis, University College Cork. en
dc.identifier.endpage 202 en
dc.identifier.uri http://hdl.handle.net/10468/3472
dc.description.abstract Model predictive control (MPC) has often been referred to in literature as a potential method for more efficient control of building heating systems. Though a significant performance improvement can be achieved with an MPC strategy, the complexity introduced to the commissioning of the system is often prohibitive. Models are required which can capture the thermodynamic properties of the building with sufficient accuracy for meaningful predictions to be made. Furthermore, a large number of tuning weights may need to be determined to achieve a desired performance. For MPC to become a practicable alternative, these issues must be addressed. Acknowledging the impact of the external environment as well as the interaction of occupants on the thermal behaviour of the building, in this work, techniques have been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive high-order simulation models, capable of replicating the thermal dynamics of a building. While a high-order simulation model allowed for control strategies to be analysed and compared, low-order models were required for use within the MPC strategy itself. The disturbance estimation techniques were adapted for use with system-identification methods to derive such models. MPC formulations were then derived to enable a more straightforward commissioning process and implemented in a validated simulation platform. A prioritised-objective strategy was developed which allowed for the tuning parameters typically associated with an MPC cost function to be omitted from the formulation by separation of the conflicting requirements of comfort satisfaction and energy reduction within a lexicographic framework. The improved ability of the formulation to be set-up and reconfigured in faulted conditions was shown. en
dc.description.sponsorship Irish Research Council (Enterprise Partnership Scheme) en
dc.format.mimetype application/pdf en
dc.language English en
dc.language.iso en en
dc.publisher University College Cork en
dc.rights © 2016, Edward O'Dwyer. en
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/ en
dc.subject Model predictive control en
dc.subject Data-driven modelling en
dc.subject Building heating systems en
dc.title Modelling and predictive control techniques for building heating systems en
dc.type Doctoral thesis en
dc.type.qualificationlevel Doctoral en
dc.type.qualificationname PHD (Engineering) en
dc.internal.availability Full text available en
dc.check.info No embargo required en
dc.description.version Accepted Version
dc.contributor.funder Irish Research Council en
dc.contributor.funder United Technologies Research Center, Ireland en
dc.description.status Not peer reviewed en
dc.internal.school Electrical and Electronic Engineering en
dc.check.type No Embargo Required
dc.check.reason No embargo required en
dc.check.opt-out No en
dc.thesis.opt-out false
dc.check.embargoformat Not applicable en
ucc.workflow.supervisor g.lightbody@ucc.ie
dc.internal.conferring Autumn 2016 en


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© 2016, Edward O'Dwyer. Except where otherwise noted, this item's license is described as © 2016, Edward O'Dwyer.
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