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论文推荐 | 基于建筑形态分类和参数化建模的多尺度设计参数对近零能耗办公楼性能的协同影响分析

北京城市实验室BCL  · 公众号  ·  · 2024-12-27 10:00

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本期为大家推荐的内容为论文《 Analysis of synergistic influence of multi-scale design parameters on nearly-zero energy office blocks performance based on architectural morphological classification and parametric modeling 》( 基于建筑形态分类和参数化建模的多尺度设计参数对近零能耗办公楼性能的 协同影响 分析 ),发表在 Building Simulation 期刊,欢迎大家学习与交流。

设计阶段不同尺度的设计参数在前期设计阶段可能显著影响建筑能耗和光伏(PV)发电潜力。然而,现有研究在评估这些方面时往往忽视了跨多个尺度(街区-建筑-立面尺度)设计参数的协同效应。本文旨在提出一种工作流程,用于在前概念设计阶段评估办公楼块的建筑能耗和光伏发电潜力,考虑多尺度设计参数的协同影响,采用建筑类型学和参数化建模方法。研究提出了一种结合参数化建模的多尺度设计参数分类系统。以武汉的80个办公楼块为案例进行了研究,这些楼块被分类为阵列型和封闭型。通过相关分析和多元回归方程量化了不同尺度设计参数的单独效应与协同效应。结果表明,仅在前期设计阶段关注单一尺度通常不足以理解建筑的能量潜力。相比之下,多尺度协同分析将能耗强度(EUI)提高了7.56%,净能耗强度(NEUI)提高了33.96%。在多尺度协同条件下,阵列型的EUI更受建筑设计参数的影响,而NEUI则受到多尺度设计参数平衡的影响。封闭型的EUI在多尺度设计参数间表现出平衡的影响,且NEUI结果与光伏发电潜力密切相关。多元回归方程强调了建筑密度和形状因子是阵列型和封闭型布局的关键影响因素。本研究为设计师在前期设计阶段评估建筑能耗和光伏发电潜力提供了一个灵活且可扩展的工作流程。研究结果可指导近零能耗城市街区规划,实现能源供需的平衡




论文相关

题目: Analysis of synergistic influence of multi-scale design parameters on nearly-zero energy office blocks performance based on architectural morphological classification and parametric modeling

基于建筑形态分类和参数化建模的多尺度设计参数对近零能耗办公楼性能的 协同影响 分析

作者:Shen Xu, Han Yang, Rongpeng Zhang, Minghao Wang, Thushini Mendis, Ying Long and Gaomei Li *

发表刊物:

Building Simulation

DOI:

https://doi.org/10.1007/s12273-024-1156-z


摘要 ABSTRACT

Design parameters at different scales in the pre-design phase could significantly impact both building energy consumption and photovoltaic (PV) power generation potential. However, existing studies often overlook the synergistic effects of design parameters across multiple scales (block-building-facade scales) when evaluating these aspects. This paper aims to propose a workflow for the assessing building energy consumption and PV power generation potential of office blocks applicable in the pre-schematic design phase considering the synergistic influence of multi-scale design parameters, using building typology and parametric modelling approach. The study proposed a multi-scale design parameter classification system combined with parametric modelling. The study investigated 80 office blocks in Wuhan as the study case, which were classified into array type and enclosed type. Correlation analysis and multiple regression equations were used to quantify the single versus synergistic effects of different scale design parameters. Results suggest that focusing solely on a single scale during the pre-design stage is typically inadequate for understanding building energy potential. In contrast, multi-scale synergistic analysis boosts energy use intensity (EUI) by 7.56% and net energy use intensity (NEUI) by 33.96%. Under multi-scale synergistic conditions, the EUI of array type is more influenced by the building design parameters, while the NEUI is effected by the balance of multi-scales design parameters. While the EUI of enclosed types exhibit balanced effects across multi-scale design parameters, with NEUI results aligning closely with PV power generation potential. Multiple regression equations highlight building density and shape factor as key influencers for both array and enclosure layouts. This study offers designers a flexible and scalable workflow for evaluating building energy consumption and PV power generation potential in the pre-design phase. The findings can guide nearly-zero energy urban block planning to achieve a balance between energy supply and demand.



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