Design Optimisation of Fenestration and Orientation for Daylighting and Energy Performance in Ghana Using Genetic Algorithm

Designing buildings to meet sustainability requirements have become the public focus globally. The paucity of building energy efficiency policies in most African countries has resulted in buildings designed without any recourse to the environmental impact, energy efficiency and thermal performance. Interestingly studies on building design optimisation within the warm-humid climates prevalent in most West-African countries are scarce. This study focuses on optimising daylighting and energy performance of an experimental block using genetic algorithm. The study achieved this aim by following a five-step methodological process. The process includes the design and construction of the experimental block and the analysis of the multi-objective optimisation (MOO) model. The experimental block was constructed in Kumasi and modelled using Rhinoceros and Grasshopper. The design variables used for the development of the MOO model were building orientation and window to wall ratio. The optimisation analysis was conducted using Non-Dominated Sorting Genetic Algorithm (NSGA-II). The findings of the study portray that within the warm-humid climate of Ghana, building orientation and fenestration have an impact on the cooling loads and daylighting potential. After the optimization the daylighting performance metric UDI is increased by 36.4% and the energy performance metric is decreased by 3.17%. The study sheds light on the impact made by form and aspect ratio in the orientation of a building. The study makes practical contributions by presenting developers, architects, engineers, and other stakeholders with information on how to overcome challenges pertaining to the design of energy efficient buildings.