Abstract
Climate change, increasing emissions and rising global temperatures have gradually affected the way we think about the future of our planet. Urban areas possess significant potential for reducing the energy consumption of the overall energy system. In recent years, there is an increasing number of research initiatives related to Urban Building Energy Modelling (UBEM) that focus on simulation processes and validation techniques. Although input data are crucial for the modelling process as well as for the validity of the results, the availability of input data and associated data formats were not analysed in detail. This paper closes the identified knowledge gap by presenting a taxonomic analysis of key UBEM components including: input data formats, simulation tools, simulation results and validation techniques. This paper concludes that over ∼95% of the studies analysed were not reproducible due to the absence of information relating to key aspects of the respective methodologies such as data sources and simulation workflows. This paper also qualifies how weak levels of interoperability, with respect to input and output data, is present in all phases of UBEM.
Highlights
In 2014, the United Nations projected an increase in the number of people living in cities from 54% in 2014 to 66% in 2050 [1,2]
We present the key findings from the taxonomy based analysis; this includes an analysis of data models (Section 4.1), simulation tools (Section 4.2), simulation results and validation techniques (Section 4.3), and reproducibility (Section 4.4)
As City Geographic Markup Language (CityGML) data sets are often openly available, future developments should focus on the enrichment of open data sets and on storing the information as common data formats such as Green building XML (gbXML) and CityGML Energy ADE
Summary
In 2014, the United Nations projected an increase in the number of people living in cities from 54% in 2014 to 66% in 2050 [1,2]. Predicting future energy balances and energy flows at a urban scale requires significant resources. One key component of this urban energy mix is the buildings sector, with respect to the associated energy demand and emissions. We provide an introduction to input data models (Section 2.1), building data models and formats (Section 2.2 and Section 2.3), and simulation tools (Section 2.4). Input data models for city quarter information modelling. Physics-based UBEM simulations require detailed input data at the individual building level. These input data facilitate modelling of buildings’ thermodynamic behaviour and their energy systems. Digital representations of buildings are a key aspect of UBEM and require structuring and organisation of raw input data. The key input data categories used for UBEM are taken from noted studies by Reihnart et al [15] and Chen et al [18] (Table 1)
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