Open AccessBuilding energy optimization using butterfly optimization algorithm
Author(s) -
Mehdi Ghalambaz,
Yengeje Reza Jalilzadeh,
Amir Hossein Davami
Publication year - 2022
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci210402306g
Subject(s) - computer science , mathematical optimization , heuristic , set (abstract data type) , optimization algorithm , energy consumption , optimization problem , computation , software , energy (signal processing) , algorithm , mathematics , artificial intelligence , engineering , statistics , electrical engineering , programming language
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 (EP) software and annual energy demand of the building was computed. A two-way coupling was established between EP and BOA. The EP 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 EP for a new simulation. Through the dynamic interaction of BOA and EP, 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.