iNtelligent Urban Model for Built environment Energy Research (iNumber)

建筑环境能源研究的智能城市模型（iNumber）

• 批准号: EP/R008620/1
• 负责人: Paul Ruyssevelt
• 金额: $ 122.63万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR008620%2F1
• 关键词: iNtelligent; Urban; Model; Built; environment

Sustainable urbanisation requires the provision of secure energy for health and comfort. Key to planning sustainable energy services is an understanding of how energy demand changes over time and space and tools to help plan for its reduction. iNUMBER is a research programme to develop:1. A building stock and municipal service energy model to help plan a secure energy supply for urban populations to be thermally comfortable and healthy (via the provision of clean water and sanitation). The model will estimate total and disaggregated (in use, time and space) energy demand. Plus, assess the impacts of different mechanisms (e.g. shading, occupant behaviour and insulation) to reduce energy demand and the capacity to provide locally generated clean energy. 2. Linked new and existing data sets. Developing models is relatively simple, the challenge is acquiring the data to input and test the validity of models. iNUMBER tackles this challenge head on by developing state of the art data collection and analytic methods to overcome this challenge in a range of scenarios with different data availability. 3.Tools to help support the urban energy management process iNUMBER supports Indian municipalities and local partners to develop a data-driven intelligent urban model for built environment energy research and municipal planning. It supports India's deep decarbonisation pathway by mapping current and future energy demand reduction opportunities in the built environment. It will diagnose urban energy problems, test solutions, verify progress, and improve policy decisions utilising state of the art monitoring, data science and analytics. iNUMBER primarily focuses around meeting the India/UK Newton research topic "Integration of information, communication and renewable energy technologies at building, community, and city level interventions." and will also meet elements of the other two areas of the call "peak demand reduction" by contributing new high resolution data and "city and community technologies" by providing guidance to urban plannersiNUMBER will:-Undertake innovative research into: urban data collection (e.g. laser ranging combined with IR and visible images from unmanned vehicles), big data analytics, and innovative modelling. -Promote the economic development of and welfare of developing countries, as required by Newton funding, by helping India to transition to a smart sustainable energy system which is critical to economic development. -Engage users of different types. Our initial project partners include urban local bodies, energy software developers, energy meter hardware suppliers, residential construction companies, architectural firms, and user experience experts. Beyond these immediate partners, we will coordinate and collaborate with other research groups in the field, engage with policymakers, and benefit the public.-Leverage Newton and DST funding by ~£1m, with support from host universities and project partners who will provide data, test sites, equipment, and provide sector expertise.-Demonstrate usable solutions: online energy information systems; benchmarking backed up by large data sets; low-tech "smart-er" retrofits for electricity meters and sub-meters; reduction strategies for energy and the energy-water nexus tailored to cities of different shapes and sizes.-Build a collaborative India/UK interdisciplinary research project: This proposal builds on the strengths of India in Information Technology and the strengths of the UK in energy epidemiology to build a best with the best collaboration. The team includes leading academics from engineering, data science, information technology, energy analysis, architecture, building science, urban science, urban planning, energy management from leading institutions in India and the UK. All work packages will be delivered via teams from both UK and India and many work packages involve interdisciplinary collaboration.

可持续城市化需要为健康和舒适提供安全的能源。规划可持续能源服务的关键是了解能源需求如何随时间和空间变化，以及帮助规划减少能源需求的工具。innumber是一个开发的研究项目：1。建筑存量和市政服务能源模式，帮助规划安全的能源供应，使城市人口热舒适和健康（通过提供清洁水和卫生设施）。该模型将估算总能源需求和分解能源需求（在使用、时间和空间上）。此外，评估不同机制（例如遮阳、居住者行为和隔热）对减少能源需求和提供本地清洁能源的能力的影响。2. 链接新的和现有的数据集。开发模型相对简单，挑战在于获取数据以输入和测试模型的有效性。iNUMBER通过开发最先进的数据收集和分析方法来解决这一挑战，以克服在一系列具有不同数据可用性的场景中的这一挑战。3.iNUMBER支持印度市政当局和当地合作伙伴开发数据驱动的智能城市模型，用于建筑环境能源研究和市政规划。它通过绘制当前和未来建筑环境中减少能源需求的机会，支持印度的深度脱碳之路。它将诊断城市能源问题，测试解决方案，验证进展，并利用最先进的监测，数据科学和分析来改进政策决策。iNUMBER主要致力于满足印度/英国牛顿研究课题“在建筑、社区和城市层面干预中整合信息、通信和可再生能源技术”，并将通过提供新的高分辨率数据和“城市和社区技术”来满足称为“高峰需求减少”的其他两个领域的要素，为城市规划者提供指导。城市数据收集（例如，激光测距与无人驾驶车辆的红外和可见光图像相结合），大数据分析和创新建模。——按照牛顿基金的要求，通过帮助印度向对经济发展至关重要的智能可持续能源系统过渡，促进发展中国家的经济发展和福利。-吸引不同类型的用户。我们最初的项目合作伙伴包括城市地方机构、能源软件开发商、电能表硬件供应商、住宅建筑公司、建筑公司和用户体验专家。除了这些直接的合作伙伴之外，我们还将与该领域的其他研究小组协调和合作，与政策制定者接触，并使公众受益。-利用牛顿和DST基金约100万英镑，由主办大学和项目合作伙伴提供支持，他们将提供数据、测试场地、设备和行业专业知识。-展示可用的解决方案：在线能源信息系统；由大型数据集支持的基准测试；对电表和分表进行低技术含量的“智能”改造；为不同形状和规模的城市量身定制能源和能源-水关系的减少策略。-建立一个合作的印度/英国跨学科研究项目：该提案建立在印度在信息技术方面的优势和英国在能源流行病学方面的优势的基础上，以最好的合作建立一个最好的项目。该团队包括来自印度和英国领先机构的工程、数据科学、信息技术、能源分析、建筑、建筑科学、城市科学、城市规划、能源管理等领域的顶尖学者。所有工作包将通过来自英国和印度的团队交付，许多工作包涉及跨学科合作。

项目成果

Challenges and lessons learned in applying Sensitivity Analysis to Building Stock Energy Models

将敏感性分析应用于建筑存量能源模型的挑战和经验教训

• 发表时间: 2021
• 作者: Fennell PJ

A comparison of performance of three variance-based sensitivity analysis methods on an urban-scale building energy model

城市规模建筑能源模型上三种基于方差的敏感性分析方法的性能比较

• DOI: 10.26868/25222708.2021.30959
• 发表时间: 2021
• 期刊: Building Simulation Conference Proceedings
• 作者: Pamela Jane Fennell;I. Korolija;P. Ruyssevelt
• 通讯作者: P. Ruyssevelt

A Review of the Status of Uncertainty and Sensitivity Analysis in Building-stock Energy Models

建筑能量模型中不确定性和敏感性分析的现状综述

• 发表时间: 2020
• 作者: Fennell PJ

Determining The Most Appropriate Form Of Urban Building Energy Model For The City Of Ahmedabad

确定艾哈迈达巴德市最合适的城市建筑能源模型形式

• DOI: 10.26868/25222708.2019.210663
• 作者: Fennell P

City Level Fuel Energy Efficiency in Municipal Solid Waste Collection: A Case of Ahmedabad

城市固体废物收集中的城市级燃料能源效率：以艾哈迈达巴德为例

• 发表时间: 2020
• 作者: Bhattacharyya S.