Impact of interactions between buildings and their outdoor conditions on the calibration of an urban building energy model

Conference paper (2024)

Authors

M. Martin Urban Data Science - Architecture and the Built Environment

Mario Berges Carnegie Mellon University

J.E. Stoter Urban Data Science - Architecture and the Built Environment

C. Garcia Sanchez Urban Data Science - Architecture and the Built Environment

Research Group

Urban Data Science (Architecture and the Built Environment) (TU Delft)

Machine learning Statistical analysis Model calibration Urban building energy modelling

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Published Date

2024

Language

English

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Faculty

Architecture and the Built Environment

Department

Urbanism

Research Group

Urban Data Science

Abstract

Urban building energy modelling aims at studying different approaches to estimate the energy consumed by buildings. However, most urban building energy models introduced in the literature ignore the impact that buildings have on their outdoor conditions, and inversely. Therefore, the paper determines whether interactions between buildings and outdoor conditions affects simulations performed using an urban building energy model, in particular during their calibration. Results suggest that interactions between buildings and their outdoor conditions affect the sensitivity of outcomes provided by an urban building energy model towards uncertain parameters and the probability to calibrate the model in accordance to some standards.

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