顾客体验导向的商业综合体中庭节能设计优化研究——以乌鲁木齐某商业综合体为例

Customer experience-oriented optimization of energy-efficient atrium design in commercial complexes: A case study of a commercial complex in Urumqi

摘要

严寒地区商业综合体普遍面临运营能耗高、空间物理环境舒适度不足等问题,严重影响顾客体验与建筑能效。立足于顾客物理环境舒适体验与建筑节能的双重需求,构建了一套针对严寒地区商业综合体中庭公共空间的性能优化设计框架,并以乌鲁木齐汇嘉时代广场为实证对象,通过文献回顾、专家访谈及配有直观图示引导的顾客问卷调查,识别出影响体验的关键几何参数,再通过优化确定室内热舒适达标百分比 (TCP )、有效自然采光照度 (UDI)及中庭冬夏两季太阳辐射的热差值 (D-RAD)3项核心评价指标;采用 Grasshopper平台构建了包含中庭空腔及其相邻商业热区的耦合参数化模型,在限定建筑总高与主体结构的前提下,结合 Ladybug与 Honeybee工具进行建筑性能模拟;然后运用遗传算法进行多目标优化,并选用K-means聚类方法对 Pareto 解集进行分类特征提取,其中为实现“算法性能优化”与“人为主观偏好”的决策协同,引入第2次问卷反馈对算法生成的解集进行人工辅助筛选与局部修正,结果表明:计算得到的综合最优解较原建筑TCP提升4.91%,UDI 提升7.9%,D-RAD下降 99.37 kW·m^-2,而在加入顾客体验偏好的人机协同修正后,最终优化模型的TCP比较原建筑提升达 25.36%。本研究为严寒地区既有商业建筑的精细化改造提供了一种可量化的设计决策参考。

Abstract

Commercial complexes in severe cold regions generally exhibit high operational energy consumption and inadequate spatial physical environmental comfort,which significantly compromise customer experience and building energy efficiency. Addressing the dual demands of customer physical thermal comfort experience and building energy conservation,this study developed a performance optimization design framework specifically for atrium public spaces in commercial complexes in severe cold regions. Taking Wanda Plaza in Urumqi as the empirical case,key geometric parameters affecting customer experience were identified through literature review,expert interviews,and customer questionnaire surveys assisted by visual diagrammatic guidance. Based on these identified parameters,three core evaluation indicators were established: Percentage of compliance with thermal comfort standards (TCP ),useful daylight illuminance (UDI),and the seasonal solar radiation difference (D-RAD) between winter and summer in the atrium. A parametric model coupling the atrium cavity and adjacent commercial thermal zones was constructed using the Grasshopper platform,with building performance simulations conducted by Ladybug and Honeybee tools,keeping the total building height and primary structural constraints unchanged. Multi-objective optimization was performed using a genetic algorithm,followed by categorical feature extraction of the Pareto solution set via K-means clustering. To achieve a synergy between algorithmic performance optimization and human subjective preferences,a second-round questionnaire was administered to facilitate human-assisted screening and local refinement of the algorithm-generated solution set. The results showed that the identified comprehensive optimal solution improved TCP by 4.91%,increased UDI by 7.9%,and reduced D-RAD by 99.37 kWh·m^-2 compared to the original building. Following human-machine collaborative refinement incorporating customer experience preferences,the final optimized model achieved a 25.36% improvement in TCP compared to the original building. This study provides a quantifiable design decision-making reference for the refined renovation of existing commercial buildings in severe cold regions.

关键词

商业综合体 / 空间体验设计优化 / 能耗性能优化 / 参数化设计 / 遗传算法 / 多目标优化

Key words

Commercial complex / spatial experience design / energy-efficient design / parametric design / genetic algorithms / multi-objective optimization

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基金资助

国家自然科学基金项目(52068065),新疆维吾尔自治区自然科学基金(青年基金)(2020D01C059)