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

5 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
van Leeuwen, Richard Pieter ; de Wit, J.B. ; Fink, J. ; Smit, Gerardus Johannes Maria. / House thermal model parameter estimation method for Model Predictive Control applications. IEEE PowerTech Eindhoven 2015. USA : IEEE Power & Energy Society, 2015. pp. 1-6
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title = "House thermal model parameter estimation method for Model Predictive Control applications",
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.",
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",
author = "{van Leeuwen}, {Richard Pieter} and {de Wit}, J.B. and J. Fink and Smit, {Gerardus Johannes Maria}",
note = "10.1109/PTC.2015.7232335",
year = "2015",
month = "6",
doi = "10.1109/PTC.2015.7232335",
language = "Undefined",
isbn = "978-1-4673-5667-1",
publisher = "IEEE Power & Energy Society",
pages = "1--6",
booktitle = "IEEE PowerTech Eindhoven 2015",

}

van Leeuwen, RP, de Wit, JB, Fink, J & Smit, GJM 2015, House thermal model parameter estimation method for Model Predictive Control applications. in IEEE PowerTech Eindhoven 2015. IEEE Power & Energy Society, USA, pp. 1-6, IEEE PowerTech 2015, Eindhoven, Netherlands, 29/06/15. https://doi.org/10.1109/PTC.2015.7232335

House thermal model parameter estimation method for Model Predictive Control applications. / van Leeuwen, Richard Pieter; de Wit, J.B.; Fink, J.; Smit, Gerardus Johannes Maria.

IEEE PowerTech Eindhoven 2015. USA : IEEE Power & Energy Society, 2015. p. 1-6.

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

TY - GEN

T1 - House thermal model parameter estimation method for Model Predictive Control applications

AU - van Leeuwen, Richard Pieter

AU - de Wit, J.B.

AU - Fink, J.

AU - Smit, Gerardus Johannes Maria

N1 - 10.1109/PTC.2015.7232335

PY - 2015/6

Y1 - 2015/6

N2 - 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.

AB - 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.

KW - EWI-26590

KW - METIS-315109

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KW - house thermal model parameter estimation method

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KW - Smart Grid

KW - Parameter estimation

KW - System Identification

KW - Thermal Network Model

KW - Predictive control

KW - Predictive models

KW - buildings (structures)

KW - interior thermal mass

KW - thermal network models

KW - Mathematical model

KW - Atmospheric modeling

KW - Floor Heating

KW - Model Predictive Control

KW - Data models

KW - Heat pumps

KW - Heating

KW - IR-98716

KW - Accuracy

KW - ventilation

U2 - 10.1109/PTC.2015.7232335

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BT - IEEE PowerTech Eindhoven 2015

PB - IEEE Power & Energy Society

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van Leeuwen RP, de Wit JB, Fink J, Smit GJM. House thermal model parameter estimation method for Model Predictive Control applications. In IEEE PowerTech Eindhoven 2015. USA: IEEE Power & Energy Society. 2015. p. 1-6 https://doi.org/10.1109/PTC.2015.7232335