Utilization of an improved crow search algorithm to solve building energy optimization problems: Cases of Australia

To design low-energy buildings, mathematical optimization can be an effective method for the minimization of energy consumption. Due to the nonlinear thermal operation of buildings, simulation-based optimizations have been used in recent studies. In the building industry, achieving optimum solutions with acceptable calculation cost is an important factor. Therefore, in this paper, an Improved Crow Search Algorithm (ICSA) coupled with the EnergyPlus simulation tool is used to optimize an office building in four cities of Australia. Based on the achievements more than 11.8% of energy consumption can be decreased by employing energy-saving actions. The proposed algorithm was compared to some benchmark algorithms and it has resulted that ICSA gives more proper solutions with lower calculation time.

Automated summary

In this study, an Improved Crow Search Algorithm (ICSA) combined with EnergyPlus simulation tool was used to optimize office buildings in four cities in Australia, resulting in over 11.8% reduction in energy consumption through energy-saving measures. Comparisons with benchmark algorithms showed that ICSA provides more suitable solutions with shorter calculation time.