House thermal model parameter estimation method for Model Predictive Control applications

Richard Pieter van Leeuwen, J.B. de Wit, J. Fink, Gerardus Johannes Maria Smit

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    6 Citations (Scopus)

    Abstract

    In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results in relation to model order and the order which yields a sufficient level of accuracy is determined. The paper presents a semi-physical estimation method which is used to improve correlation of model parameters with physical determined values. The thermal network model can be used for various simulation studies or for Model Predictive Control (MPC) of house heating or cooling systems. The paper investigates accuracy of the model for MPC by comparing MPC-results with results from TRNSYS simulations, including ventilation heat losses.
    Original languageUndefined
    Title of host publicationIEEE PowerTech Eindhoven 2015
    Place of PublicationUSA
    PublisherIEEE Power & Energy Society
    Pages1-6
    Number of pages6
    ISBN (Print)978-1-4673-5667-1
    DOIs
    Publication statusPublished - Jun 2015
    EventIEEE PowerTech 2015 - Eindhoven University of Technology, Eindhoven, Netherlands
    Duration: 29 Jun 20152 Jul 2015

    Publication series

    Name
    PublisherIEEE Power & Energy Society

    Conference

    ConferenceIEEE PowerTech 2015
    CountryNetherlands
    CityEindhoven
    Period29/06/152/07/15

    Keywords

    • EWI-26590
    • METIS-315109
    • low-energy house types
    • house thermal model parameter estimation method
    • model predictive control applications
    • Smart Grid
    • Parameter estimation
    • System Identification
    • Thermal Network Model
    • Predictive control
    • Predictive models
    • buildings (structures)
    • interior thermal mass
    • thermal network models
    • Mathematical model
    • Atmospheric modeling
    • Floor Heating
    • Model Predictive Control
    • Data models
    • Heat pumps
    • Heating
    • IR-98716
    • Accuracy
    • ventilation

    Cite this

    van Leeuwen, R. P., de Wit, J. B., Fink, J., & Smit, G. J. M. (2015). House thermal model parameter estimation method for Model Predictive Control applications. In IEEE PowerTech Eindhoven 2015 (pp. 1-6). USA: IEEE Power & Energy Society. https://doi.org/10.1109/PTC.2015.7232335