Result: Application of sensitivity analysis in building energy simulations: Combining first- and second-order elementary effects methods

Title:
Application of sensitivity analysis in building energy simulations: Combining first- and second-order elementary effects methods
Source:
Energy and buildings. 68:741-750
Publisher Information:
Oxford: Elsevier, 2014.
Publication Year:
2014
Physical Description:
print, 24 ref c
Original Material:
INIST-CNRS
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Ecole des Mines de Nantes, 4 rue Alfred Kastler, 44300 Nantes, France
UMR GEPEA - FR IRSTV, 4 rue Alfred Kastler, 44300 Nantes, France
Ecole Nationale Supérieure d'Architecture de Nantes, 6 Quai F. Mitterrand, 44000 Nantes, France
UMR CERMA - FR IRSTV, 6 Quai F. Mitterrand, 44000 Nantes, France
ISSN:
0378-7788
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Building. Public works. Transport. Civil engineering
Accession Number:
edscal.28067937
Database:
PASCAL Archive

Further Information

Sensitivity analysis plays an important role in the understanding of complex models. It helps to identify the influence of input parameters in relation to the outputs. It can also be a tool to understand the behavior of the model and can then facilitate its development stage. This study aims to analyze and illustrate the potential usefulness of combining first and second-order sensitivity analysis, applied to a building energy model (ESP-r). Through the example of an apartment building, a sensitivity analysis is performed using the method of elementary effects (also known as the Morris method), including an analysis of the interactions between the input parameters (second-order analysis). The usefulness of higher-order analysis is highlighted to support the results of the first-order analysis better. Several aspects are tackled to implement the multi-order sensitivity analysis efficiently: interval size of the variables, the management of non-linearity and the usefulness of various outputs. .