An efficient sensitivity analysis for energy performance of a building envelope: a continuous derivative based approach

TL;DR

This paper introduces a fast, derivative-based sensitivity analysis method for building envelope energy models, enabling efficient parameter influence evaluation and reduction, with high accuracy and significantly lower computational cost.

Contribution

It presents a novel continuous derivative-based sensitivity analysis approach that is faster and comparably accurate to traditional methods for building energy assessment.

Findings

The method is 100 times faster than variance-based techniques.

It accurately ranks parameter influence on thermal loads.

Effective in analyzing walls with and without windows.

Abstract

Within the framework of building energy assessment, this article proposes to use a derivative based sensitivity analysis of heat transfer models in a building envelope. Two, global and local, estimators are obtained at low computational cost, to evaluate the influence of the parameters on the model outputs. Ranking of these estimators values allows to reduce the number of model unknown parameters by excluding non-significant parameters. A comparison with variance and regression-based methods is carried out and the results highlight the satisfactory accuracy of the continuous-based approach. Moreover, for the carried investigations the approach is $100$ times faster compared to the variance-based methods. A case study applies the method to a real-world building wall. The sensitivity of the thermal loads to local or global variations of the wall thermal is investigated. Additionally, a case study of wall with window is analyzed.