An Effective Metaheuristic Approach for Building Energy Optimization Problems

Mathematical optimization can be a useful strategy for minimizing energy usage while designing low-energy buildings. To handle building challenges, this study provides an effective hybrid technique based on the pelican algorithm (POA) and single candidate optimizer (SCO). The suggested (POSCO) benefits from both robust local search power of method efficient global capabilities optimization. conduct task, was developed integrated with EnergyPlus codes. effectiveness proposed POSCO verified using mathematical test functions, outcomes were contrasted those conventional POA other techniques. Application function reveals that, among thirteen considered best at finding solution seven providing superior results functions when compared competitive is applied reducing office buildings’ annual use. Comparing to procedures, reduced. Furthermore, simple algorithms, showing specific temperatures lighting conditions, approach outperforms selected state-of-the-art methods reduces usage. As result, all data suggests that very promising, dependable, feasible dealing models. Finally, findings various climatic conditions demonstrate changes weather dataset had limited effect efficiency procedure.