Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Multiobjective Optimization Method for Energy-Saving Design of Green Buildings
A multiobjective optimization model for energy-saving design of green buildings is established by considering the two key indicators (energy efficiency and comfort) that are important for the design of green buildings. Using the energy consumption simulation software EnergyPlus to evaluate the fitness value of individuals, a multiobjective evolutionary optimization algorithm based on decomposition is used to optimize the above model. A multiobjective evolutionary optimization algorithm and its execution method are proposed for building energy efficiency, which integrates EnergyPlus. Taking a common multiroom residential building in northern China as an example, a multiobjective optimization is carried out. The results show that compared to classic intelligent optimization design algorithms such as nondominated sorting genetic algorithm II (NSGA-II), the proposed method reduces discomfort time by 1.29% while only increasing energy consumption by 0.61%.
Multiobjective Optimization Method for Energy-Saving Design of Green Buildings
A multiobjective optimization model for energy-saving design of green buildings is established by considering the two key indicators (energy efficiency and comfort) that are important for the design of green buildings. Using the energy consumption simulation software EnergyPlus to evaluate the fitness value of individuals, a multiobjective evolutionary optimization algorithm based on decomposition is used to optimize the above model. A multiobjective evolutionary optimization algorithm and its execution method are proposed for building energy efficiency, which integrates EnergyPlus. Taking a common multiroom residential building in northern China as an example, a multiobjective optimization is carried out. The results show that compared to classic intelligent optimization design algorithms such as nondominated sorting genetic algorithm II (NSGA-II), the proposed method reduces discomfort time by 1.29% while only increasing energy consumption by 0.61%.
Multiobjective Optimization Method for Energy-Saving Design of Green Buildings
Yuanting Yang (Autor:in) / Fengxiang Lu (Autor:in) / Lan Qing (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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