Abstract

To achieve global carbon neutrality by mid-century, transformative action is required in the building sector, which accounts for nearly 37% of global energy-related carbon emissions. Urban areas concentrate both emissions and energy demand; therefore, understanding and optimizing building interactions with each other and their environment is critical for effective urban planning. Urban building energy models (UBEMs) have thus become essential tools for evaluating large-scale retrofits, renewable integration, and policy strategies. However, existing UBEMs often face limitations in computational efficiency, data availability, and the representation of complex physical and financial interactions.
This PhD thesis develops a computationally efficient, physics-based, and integrative framework capable of simulating energy dynamics across large urban areas at high spatial and temporal resolution. The work advances both the science and application of UBEM by designing, validating, and applying a modeling approach that bridges building physics, renewable energy systems, and economic assessment to support carbon-neutral urban transitions. An advanced platform, CityBEM (Version 2), is introduced, integrating thermal, electrical, and solar processes within a unified computational framework supported by a numerical solver for coupled governing equations.
Building on its earlier version, CityBEM V2 substantially expands functionality. Key enhancements include transient rooftop photovoltaic (PV) modeling, detailed solar radiation exchange on urban surfaces, a 3D ray-tracing shading model, and a modular architecture for large-scale applications. Compared to conventional UBEMs, the framework enables citywide transient simulations with computation times nearly an order of magnitude faster. Its modular structure supports adaptation across cities, integration with geospatial and economic datasets, and linkage with digital twin technologies.
Results show that urban-scale PV retrofitting can reduce emissions and improve local energy autonomy, although financial viability depends strongly on tariffs and installation costs. A new metric, the Energy Self-Sufficiency Index (ESSI), is proposed to quantify combined technical and economic performance, enabling UBEM as a decision-support tool. Incorporation of 3D shading and radiative modeling improves solar potential estimation and captures geometric and morphological effects.
Overall, this work demonstrates that large-scale physics-based models can operate at the resolution and speed required for modern climate planning, providing a practical and transparent pathway toward carbon-neutral and resilient cities.