Multi-objective optimization of a residential building envelope in the Bahamas

This paper uses a multi-objective optimization approach to assess building energy performance for residential homes in the Bahamas with the goal of providing objective data to policymakers to help achieve the country's sustainability goals. A non-sorting genetic algorithm (NSGA-II) is used to find optimal solutions to building design configurations such as wall types, insulation thickness, insulation type, etc. Building energy consumption and life cycle costs are the objectives. The study uses jEPlus+EA and EnergyPlus as simulation tools to perform the optimization to provide understanding of the interactions between the objectives and optimal design parameters. Optimal solutions obtained are compared with typical building designs to assess the performance of the optimal design configurations. The results indicate that the use of insulation in the envelope and improvements to the window fenestration are warranted. Also, the optimal solutions achieve energy reductions over current standards are up to 39% with a reduction in the life-cycle cost of up to 18.5%.