An Automated Tool for Urban Building Energy Modelling: From Sparse Datasets to CityJSON

Urban Energy System Models (UESMs) development has become necessary to conduct quantitative performance analysis and support decision-making for adopting local energy-saving strategies. UESMs require a large amount of data from different sources. Designers and planners have to deal with several challenges related to data accessibility, availability, and standardisation. Often when modeling Urban Energy System (UES) for simulation purposes, lack of data, data incomplete-ness and data heterogeneity are major obstacles. In addition to that, available datasets or City Information Model (CIM) usually follow different standardisation and formats, making reproducibility on different simulation engines difficult. This work aims at developing a modular tool for creating standard CIMs with very few input constraints. The purpose is to create a flexible and configurable workflow to transform sparse data into a complete information model for urban energy simulations. The framework has been tested on an Italian study case, relying on a few georeferenced information, census data, and a power grid case file. The tool is designed to build the information model and to configure it based on the data availability of the users, in case some information is missing the tool performs data gathering and data filling through theoretical and statistical assumptions. This workflow has been designed to prepare information model for energy simulation in urban contexts thus tackling some specific aspects (e.g. building envelopes, utility networks, building systems, etc.), but its modularity allows further extensions and easy model integration.