Building energy optimization using butterfly optimization algorithm

Abstract

The butterfly optimization algorithm (BOA) is a novel meta-heuristic optimization algorithm, inspired by the intelligence foraging performance of butterflies. The aim of the current research is to minimize the energy consumption of an office building in Seattle using BOA. A heat transfer model of the building was modeled in EnergyPluse software and annual energy demand of the building was computed. A two-way coupling was established between EnergyPluse and BOA. The EnergyPluse takes into account the non-linear interaction of design variables and computes the energy demand of the building. Then the computed amount of energy demand would be transferred to the BOA, where the optimization algorithm decides about changing the design variables. Then, a new set of design variables would be transferred to EnergyPluse for a new simulation. Through the dynamic interaction of BOA and EnergyPluse, a building with minimum energy demand was designed. The impact of the number of butterflies on the performance of the optimization algorithm was also investigated. It was found that using 50 butterflies would lead to the best optimization performance. A comparison between the present method and literature optimization methods was made, which showed that BOA with 15 butterflies or higher could adequately avoid local minimums and reach the best minimum with a reasonable computation effort.