TY - JOUR
T1 - Definition of a useful minimal-set of accurately-specified input data for Building Energy Performance Simulation
AU - Egan, James
AU - Finn, Donal
AU - Deogene Soares, Pedro Henrique
AU - Rocha Baumann, Victor Andreas
AU - Aghamolaei, Reihaneh
AU - Beagon, Paul
AU - Neu, Olivier
AU - Pallonetto, Fabiano
AU - O'Donnell, James
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/4/15
Y1 - 2018/4/15
N2 - Developing BEPS models which predict energy usage to a high degree of accuracy can be extremely time consuming. As a result, assumptions are often made regarding the input data required. Making these assumptions without introducing a significant amount of uncertainty to the model can be difficult, and requires experience. Even so, rules of thumb from one geographic region are not automatically transferrable to other regions. This paper develops a methodology which can be used to determine useful guidelines for defining the most influential input data for an accurate BEPS model. Differential sensitivity analysis is carried out on parametric data gathered from five archetype dwelling models. The sensitivity analysis results are used in order to form a guideline minimum set of accurately defined input data. Although the guidelines formed apply specifically to Irish residential dwellings, the methodology and processes used in defining the guidelines is highly repeatable. The guideline minimum data set was applied to practical examples in order to be validated. Existing buildings were modelled, and only the parameters within the minimum data set are accurately defined. All building models predict annual energy usage to within 10% of actual measured data, with seasonal energy profiles well-matching.
AB - Developing BEPS models which predict energy usage to a high degree of accuracy can be extremely time consuming. As a result, assumptions are often made regarding the input data required. Making these assumptions without introducing a significant amount of uncertainty to the model can be difficult, and requires experience. Even so, rules of thumb from one geographic region are not automatically transferrable to other regions. This paper develops a methodology which can be used to determine useful guidelines for defining the most influential input data for an accurate BEPS model. Differential sensitivity analysis is carried out on parametric data gathered from five archetype dwelling models. The sensitivity analysis results are used in order to form a guideline minimum set of accurately defined input data. Although the guidelines formed apply specifically to Irish residential dwellings, the methodology and processes used in defining the guidelines is highly repeatable. The guideline minimum data set was applied to practical examples in order to be validated. Existing buildings were modelled, and only the parameters within the minimum data set are accurately defined. All building models predict annual energy usage to within 10% of actual measured data, with seasonal energy profiles well-matching.
KW - Building simulation
KW - Influence coefficient
KW - Input data
KW - Sensitivity analysis
KW - Simulation accuracy
UR - https://www.scopus.com/pages/publications/85041401960
U2 - 10.1016/j.enbuild.2018.01.012
DO - 10.1016/j.enbuild.2018.01.012
M3 - Article
AN - SCOPUS:85041401960
SN - 0378-7788
VL - 165
SP - 172
EP - 183
JO - Energy and Buildings
JF - Energy and Buildings
ER -