http://www.diva-portal.org
This is the published version of a paper presented at EST, Energy Science Technology, International Conference & Exhibition, 20-22 May 2015, Karlsruhe, Germany.
Citation for the original published paper:
Brembilla, C., Lacoursiere, C., Soleimani-Mohseni, M., Olofsson, T. (2015) Investigation of thermal parameters addressed to a building simulation model.
In: Karlsruher Institute of Technology (KIT) (ed.), Energy, Science and Technology 2015: Book of Abstracts. The energy conference for scientists and researchers (pp. 128-). Karlsruher, Germany:
Karlsruher Institute of Technology (KIT)
N.B. When citing this work, cite the original published paper.
Permanent link to this version:
http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-109880
Investigations of thermal parameters addressed to a building simulation model
Ph.D. student Christian Brembilla, Department of Applied Physics and Electronics, Umeå University, christian.brembilla@umu.se
Dr. Claude Lacoursiere, High Performance Computing Centre North (HPC2N), Umeå University, claude.lacoursiere@hpc2n.umu.se
Dr. Mohsen Soleimanni-Mohseni, Department of Applied Physics and Electronics, Umeå University, mohsen.soleimanni-mohseni@umu.se
Prof. Thomas Olofsson, Department of Applied Physics and Electronics, Umeå University, thomas.olofsson@umu.se
Keywords: Tolerance of thermal parameters, Hybrid model, Differential sensitivity analysis, Proportional control
Introduction
The uncertainty of setting input parameters in a building model can have a major impact on the simulated output.
The tolerance of thermal parameters is a necessary information that helps modeler to know the influence of each factors on the outcomes. This paper shows the allowable tolerance of thermal parameters in order to build an accurate building model. Differential sensitivity analysis of thermal parameters of a room yields the values of acceptable tolerance. A hybrid model is the approach used to simulate the room temperature over the year.
Model
Figure 1 shows the hybrid model of a room made by two thermal capacitances and simulated input data from TRNSYS software. Total hourly solar radiation on horizontal surface, outdoor temperature and internal loads are the input data. The solar radiation that strikes the external wall is split in three components: direct, diffuse and reflected from surroundings. Transmission coefficients for surfaces transfer the heat loads from sun inside the air volume. Standard profile of residential occupancy are patterns of internal loads. The two lumped thermal capacities represent the room air volume and active thermal mass. The heating system consists of panel radiator.
A heating curve controls the supplied energy to the radiator. A proportional controller adjust the amount of energy from the panel radiator according to a proportional band of 2˚C.
Fig. 1: Hybrid model Fig. 2: Sensitivity bands Fig. 3 S.A. of convective heat gains
Figure 2 shows the uncertainty bands of the indoor air. The model reruns at each single perturbed thermal parameter keeping all the other factors constant [1,2]. Figure 3 shows the sensitivity analysis of the convective heat supplied to the room. The perturbation is ±1% of the nominal value of each thermal parameter. The model is more sensitive to perturbations of environment parameters and thermal loads from free sources and panel radiator.
Conclusions
The allowable tolerance is calculated with the coefficient of variation of root mean square error. Inverting the problem, the model can be perturbed with a magnitude over ±1% till the threshold limit is reached. As final result, the allowable tolerance tells to the modeller that he/she has to asses carefully environment parameters, thermal loads from free sources and panel radiator, meanwhile he/she can neglect deep investigations of the building envelope.
References:
[1] Hopfe C., Augenbroe, G., Hensen J.; Multi-criteria decision making under uncertainty in building performance assessment, Building and Environment; 2013; vol. 69, pp. 81-90
[2]Spitza, C., Morab, L., Wurtzc, E., Jayc, A.; Practical application of uncertainty analysis and sensitivity analysis on an experimental house, Energy and Buildings, 2012; vol. 55, pp. 459–470