Multi-objective genetic optimization of embodied and operational energy and carbon impacts of buildings in current and future scenarios

Abstract

As climate change continues to pose significant challenges, redefining building design for enhanced lifecycle efficiency has become imperative. This paper investigates how different optimization objectives and varying climatic conditions shape optimal building configurations. This paper explores these performance objectives through an optimization framework that merges genetic algorithms with simulation techniques, leveraging the Energy Plus platform and incorporating embodied impact databases that include energy and carbon emission factors. This approach enables a comprehensive evaluation and optimization of operational and embodied energy, as well as carbon footprints. It also highlights the complexities of the energy-carbon relationship across different climate and energy scenarios. The methodology is applied to a representative office building model in two distinct optimization phases in current and future scenarios. The first phase optimizes the interconnected operational and embodied energy, whereas the second phase operational and embodied carbon emissions. Under current weather conditions, the first phase achieves a 28.17 % reduction in total primary energy consumption compared to the original design. In the second phase, the framework results in a 21.85 % decrease in the total carbon footprint. When future weather scenarios are examined, the first phase yields a 26.36 % reduction in total primary energy use, followed by a 17.9 % decrease in total carbon emissions in the second phase. These findings illustrate the significance of optimizing the energy and environmental impacts of buildings in current and future scenarios.