The increasing demand for global energy and the urgent requirement for sustainable urban development necessitate the integration of renewable energy sources into city infrastructure. Given the declining costs and technological advancements in the solar energy sector, this presents a viable solution for enhancing urban energy sustainability. However, the optimal placement of photovoltaic (PV) panels requires a detailed understanding of the urban landscape, solar irradiation patterns and various economic and environmental factors. This research proposes an integrated framework using semantic 3DCity models and Multi-Criteria Decision Analysis (MCDA) methods to facilitate the selection, placement and visualization of PV panels on building roofs and facades. A PV library is developed based on extensive literature research and the MCDA methods, AHP and TOPSIS are used to rank PV panels based on electrical, financial, structural and environmental criteria using user designed scenarios. On the other hand, this study makes use of SunPot tool developed at the Technical University of Munich to calculate solar irradiance using CityGML LoD2 models, while a novel approach is introduced to adapt the tool to accommodate LoD3 models. A visual programming workflow in Grasshopper/Rhino is implemented for semi-automated panel placement on roofs and facades. The methodology is tested on multiple existing buildings in Ingolstadt and Munich, Germany demonstrating its feasibility and adaptability. Key contributions include enabling LoD3 models for solar irradiance calculations, developing a automated pipeline for 3D model generation from a 3DCityDB database while retaining semantic information and implementing a flexible PV placement workflow for energy generation and costs calculation. The results highlight the potential for integrating semantic 3D city models into urban energy planning to enable informed decision-making for city planners and building owners. Future work will focus on expanding the PV database, refining the algorithm for generation of complex geometries and improving the semi-automatic PV placement workflow. Thus, this research provides an integrated framework for optimizing solar energy utilization in urban environments.     «

The increasing demand for global energy and the urgent requirement for sustainable urban development necessitate the integration of renewable energy sources into city infrastructure. Given the declining costs and technological advancements in the solar energy sector, this presents a viable solution for enhancing urban energy sustainability. However, the optimal placement of photovoltaic (PV) panels requires a detailed understanding of the urban landscape, solar irradiation patterns and various...     »