Simplified Building Thermal Model Development and Parameters Evaluation Using a Stochastic Approach

Abhinandana Boodi, Karim Beddiar, Yassine Amirat and Mohamed Benbouzid
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Abhinandana Boodi: LINEACT CESI, 29200 Brest, France
Karim Beddiar: LINEACT CESI, 29200 Brest, France
Yassine Amirat: Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), ISEN Yncréa Ouest, 29200 Brest, France
Mohamed Benbouzid: Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, 29238 Brest, France

Energies, 2020, vol. 13, issue 11, 1-23

Abstract: This paper proposes an approach to develop building dynamic thermal models that are of paramount importance for controller application. In this context, controller requires a low-order, computationally efficient, and accurate models to achieve higher performance. An efficient building model is developed by having proper structural knowledge of low-order model and identifying its parameter values. Simplified low-order systems can be developed using thermal network models using thermal resistances and capacitances. In order to determine the low-order model parameter values, a specific approach is proposed using a stochastic particle swarm optimization. This method provides a significant approximation of the parameters when compared to the reference model whilst allowing low-order model to achieve 40% to 50% computational efficiency than the reference one. Additionally, extensive simulations are carried to evaluate the proposed simplified model with solar radiation and identified model parameters. The developed simplified model is afterward validated with real data from a case study building where the achieved results clearly show a high degree of accuracy compared to the actual data.

Keywords: building model; 3R2C model; parameters identification; Crank-Nicolson finite difference method; dynamic building simulation; particle swarm optimization; thermal network model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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