Generative methods for optimizing daylight, electric lighting, energy use and carbon emissions

Abstract

Energy and daylight simulations can be computationally intensive and time consuming, especially if their main aim is to inform the design process in the early stages. In addition, the collaboration between different disciplines have become even more important to ensure that the building design can successfully reach low carbon and energy targets while ensuring good daylight levels. This research proposes an investigation about a new methodology to run both daylight and energy simulations simultaneously while optimizing the façade parameters to find the best solutions for good daylight, low energy demand and low carbon emissions from the energy use. Overall, the outcomes demonstrated that the support of multi-objective optimization engines could successfully assist in choosing between different facade solutions with high performance indicators. Moreover, it is possible to rank the different results according to their key performance indicator (KPI), so the architects have more options to choose.