PhD Oral Exam - Saeed Rayegan, Building Engineering

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

To achieve global carbon neutrality by the middle of the century, transformative action is required in the building sector, which currently accounts for nearly 37% of global energy-related carbon emissions. Since urban areas are concentrated in terms of emissions and energy demand, understanding and optimizing how buildings interact with each other and their environment is an integral part of urban planning. Consequently, urban building energy models (UBEMs) have become essential tools for evaluating large-scale energy retrofits, renewable integration, and policy initiatives. Existing UBEMs, however, often have limitations in terms of computational efficiency, data availability, and the ability to capture complex physical and financial interactions across cities.

In this PhD thesis, a computationally efficient, physics-based, and integrative framework has been developed that is capable of simulating energy dynamics across large urban areas at high spatial and temporal resolution. This thesis advances the science and application of urban building energy modeling. A major objective of this project was to design, validate, and apply a modeling approach that bridges building physics, renewable energy systems, and economic assessment in order to support the transition toward carbon-neutral cities. In this study, an advanced urban building energy modeling (UBEM) platform, the second version of CityBEM, is presented, which integrates thermal, electrical, and solar energy processes within a unified computational framework, which is supported by a numerical solver for the coupled governing equations.

CityBEM's first version was focused primarily on modeling building energy performance at the urban scale; its second version substantially expands its range of application. Among the improvements to the framework are transient rooftop photovoltaic (PV) electricity generation, detailed evaluations of solar radiation exchanges on building surfaces, a 3D ray-tracing solar shading model for urban areas, and modular structures that facilitate application across large areas. In comparison to conventional UBEMs, it is able to generate citywide transient simulations for buildings in cities with computation times nearly an order of magnitude faster. The modular architecture of the model enables adaptation across different cities, integration with geospatial and economic datasets, and integration with emerging digital twin technologies.

According to findings from this study, urban-scale PV retrofitting can significantly reduce building-related emissions and enhance local energy autonomy, although financial feasibility remains highly dependent on electricity tariffs and installation costs. This study proposes the Energy Self-Sufficiency Index (ESSI), a novel indicator designed to quantify the combined technical and financial performance of retrofit strategies, thus transforming UBEM into a quantitative decision-support tool. Integration of 3D shading and radiative models further enhances the estimation of solar potential, thereby facilitating the evaluation of geometric and morphological influences on energy performance and urban microclimate.

Aside from the methodological advances, the thesis establishes a scalable foundation for future interdisciplinary applications. This framework can be extended to include dynamic life-cycle carbon accounting, energy storage, demand-supply management, and integration with microclimate and grid models for holistic assessments of urban energy use modeling. In addition, its architecture supports the modeling of emerging technologies, including bifacial PV, building-integrated photovoltaics, and hybrid HVAC systems, establishing it as a living platform for ongoing innovation.

Ultimately, this work demonstrates that large-scale, physics-based models are capable of operating at the resolution and speed required for modern climate planning. By offering cities a practical, transparent, and reproducible pathway toward achieving carbon neutrality and climate resilience, the framework provides a bridge between scientific modeling and real-world policy.