Enhancing Industrial Buildings’ Performance through Informed Decision Making: A Generative Design for Building-Integrated Photovoltaic and Shading System Optimization

Abstract

The Italian industrial sector contains 22% of the final energy demand due to the poor energy performance of manufacturing buildings. This proposed study aimed to evaluate retrofit interventions for existing industrial buildings integrating photovoltaic solutions into the external envelope to improve both the environmental sustainability and the facade performance. The methodology is based on an innovative procedure including BIM and generative design tools. Starting from the Revit model of a representative case study, interoperability with energy analysis plugins via Grasshopper were exploited to optimize the differently oriented facade layout of photovoltaic modules to maximize the electricity production. In the case of comparable facade sizes, the building orientation had a minor impact on the results, although a southern exposure was preferable. The optimized configuration involved the installation of PV panels with a tilt angle ranging from −35° to −75°. The best compromise solution between the panel surface area and energy production during the summer solstice involves 466 m2 of PV modules. The design-optioneering approach was used to define possible alternatives to be explored for the possible installation of solar shading systems on existing windows. In this case, the impact on visual comfort within the working environment was chosen as a reference parameter, along with the value of the indoor air temperature. A decrease in this parameter equal to 0.46 was registered for the solution with horizontal (or nearly horizontal) shaders and a spacing ranging between 0.2 and 0.4. The integration of the BIM environment with generative design tools effectively assists decision-making processes for the selection of technological solutions in the building sector.

Keywords

• BIPV
• BIM
• optimization
• industrial buildings
• Grasshopper