基于遗传算法的近零能耗居住建筑多目标优化设计方法研究

近零能耗建筑是建设资源节约型社会的有效途径之一，符合我国建筑节能领域的发展方向。本研究针对我国不同气候区的不同居住建筑类型，提取关键参数，建立能耗预测基准模型。基于3E-GIS平台，建立不同气候区近零能耗居住建筑关键参数数据库，分析近零能耗居住建筑在全国各地区典型城市的可行性及级别划分。采用基于Grasshopper平台的数字化设计,内嵌 NSGA-Ⅱ遗传优化算法模块，进行以零能耗为导向的建筑能源需求最低、光伏发电量最大、增量成本最低的多目标优化，对影响三个目标函数的建筑各朝向窗墙比、围护结构、屋顶、外窗传热系统、外窗的太阳得热系数以及建筑朝向等控制变量进行量化分析。建立近零能耗居住建筑多目标优化设计流程，构建近零能耗居住建筑数字化设计的多参数多目标分析模型，对比分析不同气候区典型居住建筑类型实现近零能耗的可行性及技术路线，以期为我国不同地区的近零能耗居住建筑设计与实践提供理论及工具支撑。

Nearly Zero-energy buildings are one of the effective ways to build a resource-saving society, which is in line with the development direction of China's building energy conservation field. This study extracts key parameters for different types of residential buildings in different climate regions in China, and establishes a benchmark model for energy consumption prediction. Based on the 3E-GIS platform, a database of key parameters of nearly Zero-energy residential buildings will be established to analyze the feasibility and classification of nearly Zero-energy residential buildings in typical cities in different climate regions of China. Based on the digital design of the Grasshopper platform and the NSGA-Ⅱ genetic algorithm, with zero energy consumption as the guide, the multi-objective optimization is carried out with the goals of the lowest building energy demand, the largest photovoltaic power generation and the lowest incremental cost. Quantitative analysis of multiple control variables, such as the window-to-wall ratio of the building, the heat transfer coefficient of envelope structure, the roof and the external window , the solar heat gain coefficient of the external window, and the building orientation, etc. A multi-objective optimization design process for nearly Zero-energy buildings will be established, and a multi-objective analysis model for nearly Zero-energy building digital design will be constructed. The feasibility and technical route for nearly Zero-energy consumption of typical residential buildings in different climate zones will be compared and analyzed. The research results could provide theoretical and tool support for the design and practice of nearly Zero-energy residential buildings in different climate regions in China.