Climatic zoning for energy efficiency applications in buildings based on multivariate statistics: The case of the Brazilian semiarid region

Abstract

This study aimed to propose climatic zones in the Brazilian semiarid region using multivariate statistical techniques and to characterize these zones for energy efficiency applications in buildings. Principal component analysis (PCA) was used to select the variables with the greatest practical relevance. From this selection, hierarchical cluster analysis (HCA) was used to spatially define climatically homogeneous zones. For each defined zone, the most feasible constructive thermal conditioning strategies were defined, and the thermal indexes of heat and degree-hours of cooling and heating were calculated. As result, PCA reduced the dimensionality of the initial database from 104 to 48 variables, among which the climatic and bioclimatic variables related to temperature stood out. From the HCA, three climatic zones were defined for the Brazilian semiarid region. For all zones, there was a high demand for constructive conditioning strategies, which have to be adopted in more than half of the total annual hours. The proposed zoning is adapted to the climatic aspects of the Brazilian semiarid and has significant potential for applications in construction planning in this region. Moreover, the methodology presented can be applied for establishing climatic zones in other regions, which can contribute to increasing the energy efficiency of buildings.

Keywords

Principal component analysis / Hierarchical cluster analysis / Psychrometric chart / Heat index / Degree-hours

RIGHTS & PERMISSIONS

2021 2021 Higher Education Press Limited Company. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).