Challenges and Lessons Learned in Applying Sensitivity Analysis to Building Stock Energy Models

Pamela Fennell, Matthias Van Hove, Lia Weinberg, George Bennett, Marc Delghust, Sebastian Forthuber, Martin Jakob, Erika Mata, Claudio Nageli, Janet Reyna, Giacomo Catenazzi

Research output: Contribution to conferencePaperpeer-review

Abstract

Uncertainty Analysis (UA) and Sensitivity Analysis (SA) offer essential tools to determine the limits of inference of a model and explore the factors which have the most effect on the model outputs. However, despite a well-established body of work applying UA and SA to models of individual buildings, a review of the literature relating to energy models for larger groups of buildings undertaken by Fennell et al. (2019) highlighted very limited application at larger scales. This contribution describes the efforts undertaken by a group of research teams in the context of IEA-EBC Annex 70 working with a diverse set of Building Stock Models (BSMs) to apply global sensitivity analysis methods and compare their results. Since BSMs are a class of model defined by their output and coverage rather than their structure and inputs, they represent a diverse set of modelling approaches. Key challenges for the application of SA are identified and explored, including the influence of model form, input data types and model outputs. This study combines results from 7 different modelling teams, each using different models across a range of urban areas to explore these challenges and begin the process of developing standardised workflows for SA of BSMs.

Original languageAmerican English
Pages2203-2210
Number of pages8
DOIs
StatePublished - 2022
Event17th IBPSA Conference on Building Simulation, BS 2021 - Bruges, Belgium
Duration: 1 Sep 20213 Sep 2021

Conference

Conference17th IBPSA Conference on Building Simulation, BS 2021
Country/TerritoryBelgium
CityBruges
Period1/09/213/09/21

Bibliographical note

Publisher Copyright:
© International Building Performance Simulation Association, 2022

NREL Publication Number

  • NREL/CP-5500-86082

Keywords

  • Global Sensitivity Analysis
  • input uncertainty
  • model amalgams
  • structural uncertainty
  • UBEM

Fingerprint

Dive into the research topics of 'Challenges and Lessons Learned in Applying Sensitivity Analysis to Building Stock Energy Models'. Together they form a unique fingerprint.

Cite this