Building performance robustness assessment: Comparative study and demonstration using scenario analysis

R.R. Kotireddy (Corresponding author), Roel Loonen, Pieter-Jan Hoes, Jan Hensen

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
36 Downloads (Pure)

Abstract

During the design phase, it can be of great value to quantify the performance robustness of proposed building designs in order to arrive at buildings that deliver the desired performance over their lifespan. Design-support approaches that take performance robustness into account need to find appropriate ways of transforming the large number of unknowns in future scenarios regarding building operation and external conditions into actionable information for decision-makers. Many robustness assessment methods for environmental impact and indoor comfort are currently available, but there is very little guidance about the suitability of these methods under different conditions. Through the use of a mixed-methods research approach, combining cross-disciplinary literature review and a simulation-based case study, this article aims at comparing different approaches for analyzing the propagation of uncertainties and their impact on building performance in a systematic manner.
Different uncertainty sources are reviewed and the characteristics of different reasons and corresponding metrics to quantify the impact of these uncertainties are analyzed. The findings are complemented by results from a simulation study that highlights the usefulness of scenarios as formulated alternatives in cases when probabilities of occurrence are unknown. Moreover, the wide application potential of considering performance robustness is illustrated by demonstrating how the choice for a metric that is either based on performance spread or on performance regret can be matched in response to the risk-taking attitude of different decision makers.
Original languageEnglish
Article number109362
Number of pages20
JournalEnergy and Buildings
Volume202
Issue number109362
DOIs
Publication statusPublished - 1 Nov 2019

Keywords

  • Uncertainties
  • Scenarios
  • Performance prediction
  • Robustness assessment
  • Design decision making
  • Robust designs

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