Abstract

In architectural building design, finding an equilibrium between energy consumption and thermal comfort poses a challenge due to their inherent conflict. To effectively incorporate both aspects, their integration into the decision-making process is crucial. This study demonstrates the optimization of architectural building design parameters for a single-story educational building within a warm temperate climate in New South Wales, Australia. A meticulous validation process was undertaken using the Monte Carlo approach and scrutinizing 2,000 distinct scenarios for each parameter. This validation compared simulation outcomes with field-measured data, confirming the model’s prediction accuracy. The optimization endeavour employed the non-dominated sorting genetic algorithm to facilitate multiobjective optimization , working with the Pareto front solution. When compared with the baseline building simulation model, the optimized architectural design parameter configuration yields significant reductions of up to 24% in total EC and up to 16.5% in thermal discomfort hours.

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