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26590 House thermal model parameter estimation method for Model Predictive Control applications
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van Leeuwen, R.P. and de wit, J.B. and Fink, J. and Smit, G.J.M. (2015) House thermal model parameter estimation method for Model Predictive Control applications. In: IEEE PowerTech Eindhoven 2015, 29 June - 02 July 2015, Einhoven, The Netherlands. pp. 1-6. IEEE Power & Energy Society. ISBN 978-1-4673-5667-1

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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.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-CAES: Computer Architecture for Embedded Systems
Research Program:CTIT-General
Research Project:Smart Grid Meppel Energie
Uncontrolled Keywords:buildings (structures), parameter estimation, predictive control, ventilation, floor heating, house thermal model parameter estimation method, interior thermal mass, low-energy house types, model predictive control applications, thermal network models, Accuracy, Atmospheric modeling, Data models, Heat pumps, Heating, Mathematical model, Predictive models, model predictive control, parameter estimation, smart grid, system identification, thermal network model
ID Code:26590
Deposited On:21 December 2015
More Information:statisticsmetis

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