Zemero Bruno Ramos, Tostes Maria Emília de Lima, Bezerra Ubiratan Holanda, Batista Vitor Dos Santos, Carvalho Carminda Célia M M
Centro de Excelência em Eficiência Energética da Amazônia (CEAMAZON), Instituto de Tecnologia (ITEC), Universidade Federal do Pará (UFPA), Campus Universitário do Guamá, Belém, Pará 66025-772, Brazil e-mail:
Centro de Excelência em Eficiência Energética da Amazônia (CEAMAZON), Instituto de Tecnologia (ITEC), Universidade Federal do Pará (UFPA), Campus Universitário do Guamá, Belém 66025-772, Pará, Brazil e-mail:
J Sol Energy Eng. 2019 Aug;141(4):0408011-4080112. doi: 10.1115/1.4042244. Epub 2019 Jan 8.
Buildings' energy consumption has a great energetic and environmental impact worldwide. The architectural design has great potential to solve this problem because the building envelope exerts influence on the overall system performance, but this is a task that involves many objectives and constraints. In the last two decades, optimization studies applied to energy efficiency of buildings have helped specialists to choose the best design options. However, there is still a lack of optimization approaches applied to the design stage, which is the most influential stage for building energy efficiency over its entire life cycle. Therefore, this article presents a multi-objective optimization model to assist designers in the schematic building design, by means of the Pareto archived evolutionary strategies (PAES) algorithm with the EnergyPlus simulator coupled to evaluate the solutions. The search process is executed by a binary array where the array components evolve over the generations, together with the other building components. The methodology aims to find optimal solutions (OSs) with the lowest constructive cost associated with greater energy efficiency. In the case study, it was possible to simulate the process of using the optimization model and analyze the results in relation to: a standard building; energy consumption classification levels; passive design guidelines; usability and accuracy, proving that the tool serves as support in building design. The OSs reached an average of 50% energy savings over typical consumption, 50% reduction in CO operating emissions, and investment return less than 3 years in the four different weathers.
建筑物的能源消耗在全球范围内对能源和环境都有重大影响。建筑设计在解决这一问题方面具有巨大潜力，因为建筑围护结构会对整个系统性能产生影响，但这是一项涉及众多目标和限制条件的任务。在过去二十年中，应用于建筑物能源效率的优化研究帮助专家们选择最佳设计方案。然而，在设计阶段仍缺乏优化方法，而设计阶段是建筑物在其整个生命周期内对能源效率影响最大的阶段。因此，本文提出了一种多目标优化模型，借助帕累托存档进化策略（PAES）算法与EnergyPlus模拟器相结合来评估解决方案，以协助设计师进行建筑方案设计。搜索过程由一个二进制数组执行，数组元素与其他建筑组件一起在几代中不断进化。该方法旨在找到具有最低建设成本且能源效率更高的最优解（OSs）。在案例研究中，可以模拟使用优化模型的过程，并分析与以下方面相关的结果：一座标准建筑；能源消耗分类水平；被动式设计指南；可用性和准确性，证明该工具可为建筑设计提供支持。在四种不同气候条件下，最优解的能耗比典型能耗平均节省50%，运营碳排放减少50%，投资回报期不到3年。
