Occupant Comfort Versus Building Energy Performance: Generalisable Artificial Intelligence Frameworks for Optimum Trade-offs

Achieving the optimum balance between occupant comfort and energy efficiency in buildings is a complicated process. This is due to the unique function, location, and design of each building. In addition, comfort and energy efficiency are contradicting objectives in most cases that makes trade-offs inevitable. Despite recent advancements in the modelling and simulation of buildings performance, there is an opportunity for exploiting advancements in the artificial intelligence domain to develop accurate and swift frameworks that achieve optimum trade-offs between occupant comfort and energy efficiency. Therefore, this thesis aims to develop modern-generalisable frameworks that assess and optimise buildings for improved occupant comfort and building energy performance levels.