城市规模的住宅能源消耗预测,采用多模式方法
Yulan Sheng1,2, Hadi Arbabi3, Wil O C Ward4
1School of Earth and Environment, University of Leeds, Leeds, UK. y.sheng1@leeds.ac.uk.
Scientific reports
|February 12, 2025
概括
了解住房能源消耗是减少气候影响的关键. 较大,较旧的房屋外墙较差,最需要改造,特别是在密集的地区.
科学领域:
- 建筑科学 建筑科学
- 能源效率 能源效率 能源效率
- 可持续的建筑 可持续的建筑
背景情况:
- 建筑物对气候变化做出了重大贡献,需要改善现有住房库的能源效率.
- 准确评估住房能源消耗对于有效和经济高效的改造战略至关重要.
- 确定影响能源使用的关键特征指导了减少环境影响的有针对性的干预措施.
研究的目的:
- 研究空间,形态和热特性对住宅能源消耗的影响.
- 开发一种快速评估工具,用于识别适合改装的物业和建筑元件.
- 为现有住房提供节能改造措施的信息.
主要方法:
- 一个涉及大约143,000个在谢菲尔德的住宅物业的案例研究.
- 应用自动机器学习方法来估计建筑物的能源消耗.
- 对特征变量分析的重要性和部分依赖性,以确定影响能源的关键因素.
主要成果:
- 机器学习模型在估计能源消耗方面取得了高准确性 ([公式:参见文本]得分为0.828).
- 房屋的大小和外墙的状况被确定为影响能源消耗的最重要特征.
- 在建筑密集的社区里,较旧,较大的单独住宅显示了通过改造来减少能源的最大潜力.
结论:
- 空间和基于条件的特征,特别是住房大小和外墙状况,对于预测住宅能源消耗至关重要.
- 一个快速评估工具可以有效地指导改造重点,以减少住房储备中的能源.
- 密集地区较大,较旧的独立住宅的有针对性的改造为缓解气候变化提供了巨大的机会.
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