An integrated urban platform is the essential software infrastructure for smart, sustainable and resilient city planning, operation and maintenance. Today such platforms are mostly designed to handle and analyze large and heterogeneous urban data sets from very different domains. Modeling and optimization functionalities are usually not part of the software concepts. However, such functionalities are considered crucial by the authors to develop transformation scenarios and to optimize smart city operation. An urban platform needs to handle multiple scales in the time and spatial domain, ranging from long term population and land use change to hourly or sub-hourly matching of renewable energy supply and urban energy demand.

The paper discusses software architecture concepts for data and modeling urban platforms, which allow to analyze and optimize the urban infrastructure with their energy, water and further resources such as food or goods consumption. Building, commerce and industry as well as the transport sector are in the focus of the efficiency and renewable supply analysis. The main driver is to derive zero carbon strategies for cities while including all major sectors of CO₂ generation.

So far, two software architecture concepts have been implemented and tested, both using a 3D CityGML geometry data model: A workflow management system for city scale building energy modeling using a monthly energy balance calculation method and a micro service orchestration for dynamic building simulation modeling. The GIS based data analysis methodology and building energy workflow modeling method are applied to a case study district in New York City to demonstrate the implementation status and derive CO₂ mitigation strategies. The results showed how data gathered from different sources for the relevant sectors can be translated into CO₂-emissions. For a district in Brooklyn connected to a large electric substation with electricity monitoring data available, every individual building´s heating and cooling demand was simulated and resulted in a total annual heating demand of 1.72 TWh/a and 0.11 TWh/a of cooling. It could be shown that the building sector cooling demand can by reduced by 63 % by a change of set point temperature for cooling and reduced infiltration rate, while reducing the heat demand by 12 %. In addition, carbon accounting of the food and wastewater sector was done using the same GIS based modeling framework. The analysis showed that the food related electricity consumption for refrigeration corresponds to about 5 % of the overall electricity consumption and requires 2.6 GWh/a for transport. Using food waste in co-digestion of wastewater treatment plants could contribute another 7.4 GWh/a of combined heat and power. Such quantification of demand and energy sources could contribute to prioritize actions for CO₂ mitigation strategies in urban areas.

集成的城市平台是用于智能，可持续和灵活的城市规划，运营和维护的重要软件基础架构。如今，此类平台主要用于处理和分析来自非常不同领域的大型且异构的城市数据集。建模和优化功能通常不属于软件概念的一部分。但是，作者认为这些功能对于开发转型方案和优化智慧城市运营至关重要。一个城市平台需要在时空范围内处理多种尺度，范围从长期的人口和土地使用变化到可再生能源供应和城市能源需求的每小时或不到一小时的匹配。

本文讨论了用于数据和城市平台建模的软件体系结构概念，这些概念可以分析和优化城市基础设施的能源，水和其他资源，例如食物或商品的消耗。建筑，商业和工业以及运输部门是效率和可再生能源供应分析的重点。主要驱动力是为城市制定零碳战略，同时涵盖所有主要的CO ₂产生领域。

到目前为止，已经使用3D CityGML几何数据模型实施和测试了两个软件体系结构概念：使用月度能源平衡计算方法的城市规模建筑能源建模的工作流管理系统，以及用于动态建筑模拟建模的微服务编排。将基于GIS的数据分析方法和建筑能耗工作流建模方法应用于纽约市的一个案例研究区，以展示其实施状况并得出CO ₂缓解策略。结果表明，如何将从相关部门的不同来源收集的数据转换为CO ₂-排放。对于连接到大型变电站并具有可用电力监控数据的布鲁克林区，每个建筑物的供热和制冷需求都经过模拟，得出的年总供热需求为1.72 TWh / a和0.11 TWh / a。可以看出，通过改变制冷设定点温度和降低渗透率，可以将建筑部门的制冷需求减少63％，同时将热量需求减少12％。此外，使用相同的基于GIS的建模框架对食品和废水部门进行碳核算。分析表明，与食品有关的制冷用电量约占总用电量的5％，运输需要2.6 GWh / a。将食物垃圾用于废水处理厂的共消化，可另外产生7.4 GWh / a的热电联产。需求和能源的这种量化可能有助于确定CO的优先行动₂城市地区的缓解策略。