UNS: Intelligent Multi-Criteria Building Ventilation Control within Dynamic Urban Environments

UNS：动态城市环境中的智能多标准建筑通风控制

• 批准号: 1511151
• 负责人: Michael Waring
• 金额: $ 29.97万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1511151&HistoricalAwards=false
• 关键词: UNS; Intelligent; Multi; Criteria; Building

1511151 (Waring) Americans spend 90% of our time indoors, where poor indoor air quality (IAQ) is a top risk to human health and productivity. Maintaining acceptable IAQ requires ventilation, or replacing indoor with outdoor air, usually by mechanical systems. Ventilation rates are set as minimum standards for commercial buildings (e.g. 8.5 L/s/person for offices), though new research suggests that higher rates increase occupant productivity and decrease absenteeism. However, increasing ventilation requires energy to move and condition the air, can strain the electricity grid, and can degrade IAQ in polluted urban areas. The current minimum ventilation rate paradigm is simplistic, with no framework for evaluating most of these numerous and competing positive and negative consequences. As such, many opportunities are missed for promoting environmental sustainability, including increasing occupant wellbeing, improving energy efficiency, and reducing greenhouse gas and local pollutant emissions. The purpose of this project is to capitalize on these opportunities by researching next-generation, intelligent ventilation strategies for high performance green buildings.Since elements such as weather, pollution, and energy prices have diurnal and seasonal profiles, large benefits may be realized at minimal energy costs with systems-level strategies that capitalize on transient behaviors within a dynamic control framework. This project will research dynamic, holistic, multi-criteria ventilation control in green office buildings. It will: (1) Formalize a user-oriented, multi-criteria decision-making framework with a comprehensive and flexible utility function, and evaluate the impacts of intelligent ventilation in a variety of settings with special attention to the influence of building and location characteristics, and (2) Investigate self-learning, plug-and-play dynamic ventilation control methods that can adapt to specific office buildings and meet the unique challenges of the building industry. It will assess impacts and develop control algorithms with detailed simulations, as well as validate the work in a real building in Philadelphia that is already instrumented to measure pollutants and energy use. Results will be disseminated to (i) the public through a web display of the real-time state of the experimental building; to (ii) the scientific community through conference and journal publications and investigator affiliations with the Consortium for Building Energy Innovation; and to (iii) industry through affiliations with technical committees in the American Society for Heating, Refrigeration, and Air-conditioning Engineers (ASHRAE).

1511151（警告）美国人90%的时间都在室内度过，糟糕的室内空气质量（IAQ）是人类健康和生产力的最大风险。维持可接受的室内空气质素需要通风，或用室外空气代替室内空气，通常采用机械系统。商业建筑的通风率被设定为最低标准（例如，办公室的通风率为8.5 L/s/人），尽管新的研究表明，较高的通风率可以提高居住者的工作效率并减少缺勤。然而，增加通风需要能量来移动和调节空气，可能会给电网带来压力，并可能降低污染城市地区的室内空气质量。目前的最小通风量模式过于简单，没有框架来评估这些众多的和相互竞争的积极和消极的后果。因此，许多促进环境可持续性的机会被错过了，包括增加居住者的福祉，提高能源效率，减少温室气体和当地污染物的排放。该项目的目的是通过研究下一代高性能绿色建筑的智能通风策略来利用这些机会。由于天气、污染和能源价格等因素具有昼夜和季节性特征，因此在动态控制框架内利用瞬态行为的系统级策略可以以最小的能源成本实现巨大的效益。本项目将研究绿色办公建筑的动态、整体、多准则通风控制。它将：(1)形成一个以用户为导向，具有综合灵活效用功能的多标准决策框架，并评估智能通风在各种设置中的影响，特别关注建筑和位置特征的影响；(2)研究适应特定办公建筑并满足建筑行业独特挑战的自学习，即插即用动态通风控制方法。它将通过详细的模拟来评估影响和开发控制算法，并在费城的一座真实建筑中验证这项工作，该建筑已经配备了测量污染物和能源使用的仪器。研究结果将通过网页向公众展示实验建筑的实时状态；（ii）通过会议和期刊出版物以及与建筑能源创新联盟的调查员关系向科学界；通过与美国采暖、制冷和空调工程师协会（ASHRAE）的技术委员会的隶属关系向行业提供服务。