The influence of data quality on urban heating demand modeling using 3D city models
The influence of data quality on urban heating demand modeling using 3D city models
复制标题
数据质量对使用 3D 城市模型进行城市供暖需求建模的影响
DOI：
10.1016/j.compenvurbsys.2016.12.005
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
U. Eicker
中科院分区：
文献类型：
--
作者：
R. Nouvel;M. Zirak;V. Coors;U. Eicker
3D城市模型是城市能源分析的丰富数据集，提供了估计整个地区，城市甚至地区能源需求所需的几何和语义数据。然而，由于这些数据的可用性、不确定性和详细程度以及收集它们所需的资源不同，管理数据质量是城市能源建模的一个共同挑战。了解不同输入数据对不同配置和应用的影响，可以通过为最重要的参数分配资源来控制结果准确性，并推荐智能和适当的数据收集策略。以德国路德维希堡市为例，研究了几何、气象、语义和居住相关数据质量对城市能源模拟平台SimStadt估算的供暖需求的影响。重点放在一个地区的消费数据可在积木水平允许一个关键的比较估计和测量的能源需求。虽然本文中提出的量化信息是特定的案例研究，主要趋势和开发的方法是转移到其他城市能源分析研究的基础上的三维城市模型。
3D city models are rich data sets for urban energy analyses, providing geometrical and semantic data required to estimate the energy demand of entire districts, cities and even regions. However, given the diverse availability, uncertainty and Level of Details of these data and the resources required to collect them, managing data quality is a common challenge of urban energy modeling. Knowing the influences of the different input data for different configurations and applications enables to control the result accuracy and recommend intelligent and adequate data collecting strategies, by assigning resources on the most important parameters. This paper investigates the influences of geometrical, meteorological, semantic and occupancy related data quality on the heating demand estimated by the urban energy simulation platform SimStadt, applied to the City of Ludwigsburg in Germany. A focus on a district with consumption data available at building block level allows for a critical comparison between estimated and measured energy demands. Although the quantified information presented in this paper is specific to a case study, the main trends and developed methods are transferrable to other urban energy analysis studies based on 3D city models.