BIM-Based Methodology for Supporting and Optimizing Photovoltaic System Integration and Economic Evaluation in Sustainable Buildings

This thesis presents a Building Information Modeling (BIM)-based methodology for the integrated surface specific design, optimization, and economic evaluation of photovoltaic (PV) systems on the entire envelope of sustainable buildings. The proposed workflow leverages the interoperability between Autodesk Revit, Dynamo, and Refinery, combining parametric modeling with generative design techniques to support data-driven decision-making in the early design phases, as well as retrofit design in existing structures. The methodology is structured around two complementary pathways: a user-driven simulation allowing deterministic control over design parameters, and a generative design approach enabling the automated exploration of multi-objective scenarios. A real-world case study conducted on the Stellantis PCMA industrial facility in San Benigno Canavese (Italy) validates the robustness and adaptability of the methodology. The complex geometry of the site, including multiple roof typologies and facade surfaces, provides a challenging test environment for assessing the accuracy of solar irradiance simulations, shading effects, and string configuration strategies. Results demonstrate the model’s ability to automatically generate optimized PV layouts, evaluate energy production, and provide accurate financial forecasts under varying boundary conditions. Additionally, advanced visualization and data management tools—such as Power BI for interactive dashboards and Speckle for 3D collaborative visualization, enhance the interpretability and communication of results among stakeholders. By bridging architectural modeling, energy performance simulation, and economic assessment within a unified framework, this work contributes to advancing BIM-integrated renewable energy design, offering a replicable and scalable methodology for PV system integration in both new and existing buildings.