【Building Simulation】未来气候变化影响下的城市建筑群能耗模拟

摘要

城市建筑群能耗模拟（urban building energy modeling, UBEM）是一种新兴技术，可以用于计算城市尺度的建筑群用能情况，并评估未来情景下的节能改造，为合理制定碳减排政策提供依据。目前，大多数研究都集中在评估典型建筑在各种未来气候情景下的能源性能，当扩大到城市/街区尺度时很难获取每栋建筑更精细的结果。

本研究利用UBEM 评估未来气候变化对城市建筑群用能的影响，选取瑞士日内瓦两个街区内的483栋住宅建筑作为案例研究。首先，收集GIS数据和当地建筑标准规范，建立典型建筑数据库。然后，采用先前开发的UBEM工具AutoBPS计算建筑的年度供暖需求，基于实测数据进行快速自动地校准，将平均误差显著降低至2.7%。最后，使用最新的共享社会经济路径（shared socioeconomic pathways，SSP）情景中的四个未来天气文件（SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5），评估气候变化对建筑群供暖、制冷需求和节能改造的影响。结果显示到2050年，两个街区的供暖需求分别减少22-31%和21-29%，制冷需求分别增加113-173%和95-144%。基于典型气象年模拟时，供暖需求的平均强度为81 kWh/m²，而在SSP5-8.5 中下降至57 kWh/m²，而制冷需求的平均强度从12 kWh/m² 增加至32 kWh/m²。在SSP情景下，围护结构整体升级将平均供暖和制冷需求分别降低了41.7%和18.6%。该研究结果为城市管理者在面对未来不同发展路径时，采取合适的能源规划方案提供重要信息。

关键词：城市建筑群能耗模拟；气候变化；模型校准；AutoBPS；供暖和制冷需求

The building sector is facing a challenge in achieving carbon neutrality due to climate change and urbanization. Urban building energy modeling (UBEM) is an effective method to understand the energy use of building stocks at an urban scale and evaluate retrofit scenarios against future weather variations, supporting the implementation of carbon emission reduction policies. Currently, most studies focus on the energy performance of archetype buildings under climate change, which is hard to obtain refined results for individual buildings when scaling up to an urban area. Therefore, this study integrates future weather data with an UBEM approach to assess the impacts of climate change on the energy performance of urban areas, by taking two urban neighborhoods comprising 483 buildings in Geneva, Switzerland as case studies. In this regard, GIS datasets and Swiss building norms were collected to develop an archetype library. The building heating energy consumption was calculated by the UBEM tool—AutoBPS, which was then calibrated against annual metered data. A rapid UBEM calibration method was applied to achieve a percentage error of 2.7%. The calibrated models were then used to assess the impacts of climate change using four future weather datasets out of Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results showed a decrease of 22%–31% and 21%–29% for heating energy consumption, an increase of 113%–173% and 95%–144% for cooling energy consumption in the two neighborhoods by 2050. The average annual heating intensity dropped from 81 kWh/m² in the current typical climate to 57 kWh/m² in the SSP5-8.5, while the cooling intensity rose from 12 kWh/m² to 32 kWh/m². The overall envelope system upgrade reduced the average heating and cooling energy consumption by 41.7% and 18.6%, respectively, in the SSP scenarios. The spatial and temporal distribution of energy consumption change can provide valuable information for future urban energy planning against climate change.

Keywords: urban building energy modeling, climate change, model calibration, AutoBPS, heating and cooling energy consumption

部分图表

Fig. 1 Research workflow

Fig. 8 Monthly average changes under different emission scenarios by 2050: (a) outdoor dry bulb temperature; (b) relative humidity; (c) global horizontal radiation

Fig. 9 Annual TEC-SH and TEC-SC under different future weather data

Fig. 12 Hourly heating and cooling demands in NBH 1: (a) the coldest winter day (February 3); (b) the hottest summer day (August 22)

Fig. 13 Annual energy consumption with ECMs in different future scenarios in NBH2: (a) heating; (b) cooling

Fig. 14 The specific annual TEC-SH intensity distribution in NBH 2: (a) TMY baseline; (b) SSP1-2.6 with M1; (c) SSP5-8.5 with M5

相关阅读：

长按二维码或点击左下角“阅读原文”访问全文

长按访问原文

未来气候变化影响下的城市建筑群能耗模拟