Multiscale urban modeling and monitoring strategies for urban CO2 reduction

城市二氧化碳减排的多尺度城市建模和监测策略

• 批准号: RGPIN-2020-06780
• 负责人: Eicker, Ursula
• 金额: $ 4.01万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=746380
• 关键词: Multiscale; urban; modeling; monitoring; strategies

District level zero or low carbon concepts require integrated modeling approaches for the building sector consumption, the urban waste and water infrastructure, the energy supply and distribution systems and the energy requirements from local transport. Mathematical models for dynamic building performance analysis, energy generation and storage including waste water and waste to energy systems and network-based distributions need to be adaptable on both a spatial scale from building to district to the city and temporal scales. While there has been abundant research on building scale energy modeling in the last decades with many available and validated tools, much work is still needed to address combined energy modeling of different sectors in a city. The long-term objective of the proposed research program is to deliver an integrated urban modeling and data analytics framework for sustainable and resilient city planning and operation. Such a framework requires the modeling and analysis of the main energy-consuming sectors in the city, i.e. the built environment, network, urban waste and water infrastructure, industrial and commercial activities and transportation. The short-term research objectives are as follows: - Development of new mathematical optimization models and control strategies for multi-scale applications at the urban scale - Development of integrated modelling approaches for different sector coupling - Real-time monitoring database creation and development of data analytics frameworks using dynamic data-driven models and machine learning for knowledge discovery - Development of smart energy management systems. - Test the strategies, methods, and tools in real case studies of different scales The development goal of an open-source urban data management and modeling platform is to create an international community of next-generation cities modelers that cooperate on the complex task of integrating supply, demand and distribution network electricity models across the sectors. The platform should make it easy to develop and integrate new features from the data, modeling or visualization domain and contribute to net zero carbon city transformation strategies.

地区级零碳或低碳概念需要对建筑部门的消费、城市废物和水基础设施、能源供应和分配系统以及当地交通的能源需求采用综合建模方法。动态建筑性能分析，能源生产和存储，包括废水和废物的能源系统和基于网络的分布的数学模型需要适应从建筑到地区到城市的空间尺度和时间尺度。虽然在过去的几十年里，已经有了大量的研究，建筑规模的能源建模与许多可用的和验证的工具，仍然需要做很多工作，以解决在一个城市的不同部门的组合能源建模。拟议研究计划的长期目标是为可持续和有弹性的城市规划和运营提供综合城市建模和数据分析框架。这种框架要求对城市的主要能源消耗部门进行建模和分析，即建筑环境、网络、城市废物和水基础设施、工业和商业活动以及交通。短期研究目标如下：-为城市规模的多尺度应用开发新的数学优化模型和控制策略-为不同部门耦合开发综合建模方法-实时监测数据库创建和开发数据分析框架，使用动态数据驱动模型和机器学习进行知识发现-开发智能能源管理系统。- 在不同规模的真实的案例研究中测试策略、方法和工具开源城市数据管理和建模平台的开发目标是创建一个由下一代城市建模人员组成的国际社区，这些建模人员将合作完成跨行业集成供应、需求和配电网络电力模型的复杂任务。该平台应便于开发和整合数据、建模或可视化领域的新功能，并为净零碳城市转型战略做出贡献。