Bottom-Up Urban Building Energy Modelling II

Dear Colleagues,

Buildings are one of the main contributors to energy and materials used in urban areas all over the world; however, the lack of information about the energy status and energy potential of building stocks of cities is widespread. Research in urban building energy modelling (UBEM) is thus gaining momentum.

UBEM approaches are usually classified into two main categories: top-down and bottom-up. This Special Issue targets the bottom-up approach, which includes engineering, data-driven, and hybrid energy modelling, where large datasets are used to estimate the energy use of individual buildings, then aggregated to define the energy use at district and urban scales. The engineering models exploit energy balance equations, derived by single-building energy modelling (BEM), to calculate the energy use at single-building scale and then aggregate the results at district and urban scales. The data-driven approach makes it possible to connect building characteristics and other influencing parameters to the energy use by means of statistical analysis or artificial intelligence methods. Both of the approaches have advantages and limitations. Data-driven energy modelling may predict annual energy consumption and provide accurate representation of urban energy use, but it fails in simulating scenarios (e.g., retrofitting, climate change, etc.) when solely driven by historical data. Engineering-based UBEMs simulate energy demand with high spatiotemporal resolution, allowing for scenario development, but require detailed and often unknown input that may affect the reliability of aggregated results. Hybrid modelling attempts to overcome the limits of the previous approaches by integrating both of them in the analysis.

Since this is a nascent field of research, many open questions are still in need of an answer. The main open topics for research include but are not limited to (i) dataset definition and description of buildings (archetypes, prototypes), (ii) modelling of people movements and actions in buildings and in the city, (iii) different modelling for district energy systems, energy storage, and energy networks, (iv) modelling of city microclimate, green and blue infrastructures, and their integration with comfort assessment, (v) heat transfer among buildings and with the external environment, (vi) calibration and validation of models, (vii) life cycle assessment at the urban scale, and (vii) hybrid modelling approaches.

Dr. Francesco Causone
Dr. Alfonso Capozzoli
Guest Editors

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• new data-driven UBEM tools
• new engineering-based UBEM tools
• dataset definition and use
• archetype and prototype generation and use
• modelling of people’s actions and movements for UBEM
• use of UBEM to simulate city or district energy strategies (e.g., district energy systems, storage, etc.)
• modelling urban microclimate and outdoor thermal comfort assessment via UBEM
• calibration and validation
• buildings life cycle assessment at the district and urban scales