CPS: Synergy: Collaborative Research: Cognitive Green Building: A Holistic Cyber-Physical Analytic Paradigm for Energy Sustainability
CPS:协同:协作研究:认知绿色建筑:能源可持续性的整体网络物理分析范式
基本信息
- 批准号:1446582
- 负责人:
- 金额:$ 60.6万
- 依托单位:
- 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:2015-01-01 至 2019-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
1446582 (Shroff) and 1446478 (Hou). Buildings in the U.S. contribute to 39% of energy use, consume approximately 70% of the electricity, and account for 39% of CO2 emissions. Hence, developing green building architectures is an extremely critical component in energy sustainability. The investigators will develop a unified analytical approach for green building design that comprehensively manages energy sustainability by taking into account the complex interactions between these systems of systems, providing a high degree of security, agility and robust to extreme events. The project will serve to advance the general science in CPS, help bridge the gap between the cyber and civil infrastructure communities, educate students across different disciplines, include topics in curriculum development, and actively recruit underrepresented minority and undergraduate students. The main thesis of this research is that ad hoc green energy designs are often myopic, not taking into account key interdependencies between subsystems and users, and thus often lead to undesirable solutions. In fact, studies have shown that 28%-35% of LEED-certified buildings consumed more energy than their conventional counterparts, all of which calls for the development of a comprehensive analytical foundation for designing green buildings. In particular, the investigators will focus on three interrelated thrust areas: (i) Integrated energy management for a single-building, where the goal is to jointly consider the complex interactions among building subsystems. The investigators will develop novel control schemes that opportunistically exploit the energy demand elasticity of the building subsystems and adapt to occupancy patterns, human comfort zones, and ambient environments. (ii) Managing multi-building interactions to develop (near) optimal distributed control and coordination schemes that provide performance guarantees. (iii) Designing for anomalous conditions such as extreme weather and malicious attacks, where power grid connections and/or cyber-networks are disrupted. The research will provide directions at developing an analytical foundation and cross-cutting principles that will shed insight on the design and control of not only building systems, but also general CPS systems. An important goal is to help bridge the gap between the networking, controls, and civil infrastructure communities by giving talks and publishing works in all of these forums. The investigators will disseminate the research findings to industry as well as offer education and outreach programs to the K-12 students in STEM disciplines. The investigators will also actively continue their already strong existing efforts in recruiting women and underrepresented minorities, as well as providing rich research experience to undergraduate REU students. This project will provide fertile training for students spanning civil infrastructure research, networking, controls, optimization, and algorithmic development. The investigators will also actively include the outcomes of the research in existing and new courses at both the Ohio State University and Virginia Tech.
1446582 (Shroff)和1446478 (Hou)。在美国,建筑贡献了39%的能源使用,消耗了大约70%的电力,并占了39%的二氧化碳排放量。因此,发展绿色建筑是能源可持续性的一个极其重要的组成部分。研究人员将为绿色建筑设计开发一种统一的分析方法,通过考虑到这些系统之间复杂的相互作用,全面管理能源可持续性,提供高度的安全性,灵活性和对极端事件的鲁棒性。该项目将有助于推进CPS的一般科学,帮助弥合网络和民用基础设施社区之间的差距,教育不同学科的学生,在课程开发中纳入主题,并积极招募代表性不足的少数民族和本科生。本研究的主要论点是,特别的绿色能源设计往往是短视的,没有考虑到子系统和用户之间的关键相互依赖关系,因此往往导致不受欢迎的解决方案。事实上,研究表明,28%-35%的leed认证建筑比普通建筑消耗更多的能源,所有这些都需要发展一个综合的分析基础来设计绿色建筑。特别是,研究人员将集中于三个相互关联的重点领域:(i)单个建筑物的综合能源管理,其目标是共同考虑建筑物子系统之间复杂的相互作用。研究人员将开发新的控制方案,利用建筑子系统的能源需求弹性,适应占用模式、人类舒适区和环境。(ii)管理多个建筑的相互作用,以开发(接近)最优的分布式控制和协调方案,提供性能保证。(iii)针对异常情况(如极端天气和恶意攻击,电网连接和/或网络中断)进行设计。该研究将为开发分析基础和交叉原则提供方向,这些原则将为不仅建筑系统,而且一般CPS系统的设计和控制提供见解。一个重要的目标是通过在所有这些论坛上发表演讲和出版作品,帮助弥合网络、控制和民用基础设施社区之间的差距。调查人员将向业界传播研究成果,并为STEM学科的K-12学生提供教育和推广计划。研究人员还将积极地继续他们已经强有力的现有努力,招募妇女和代表性不足的少数民族,并为REU的本科生提供丰富的研究经验。该项目将为学生提供丰富的培训,涵盖民用基础设施研究、网络、控制、优化和算法开发。研究人员还将积极地将研究成果纳入俄亥俄州立大学和弗吉尼亚理工大学的现有课程和新课程。
项目成果
期刊论文数量(0)
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Ness Shroff其他文献
Performance analysis of virtual circuit connections for bursty data sources in ATM networks
- DOI:
10.1007/bf02024995 - 发表时间:
1992-08-01 - 期刊:
- 影响因子:4.500
- 作者:
Ness Shroff;Magda El Zarki - 通讯作者:
Magda El Zarki
Ness Shroff的其他文献
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{{ truncateString('Ness Shroff', 18)}}的其他基金
Collaborative Research: NeTS: Medium: Black-box Optimization of White-box Networks: Online Learning for Autonomous Resource Management in NextG Wireless Networks
合作研究:NeTS:中:白盒网络的黑盒优化:下一代无线网络中自主资源管理的在线学习
- 批准号:
2312836 - 财政年份:2023
- 资助金额:
$ 60.6万 - 项目类别:
Standard Grant
AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE)
未来边缘网络和分布式智能人工智能研究所 (AI-EDGE)
- 批准号:
2112471 - 财政年份:2021
- 资助金额:
$ 60.6万 - 项目类别:
Cooperative Agreement
Collaborative Research: CNS Core: Medium: Analytics and Online Optimization at Scale for Cellular Networks
合作研究:CNS 核心:中:蜂窝网络大规模分析和在线优化
- 批准号:
2106933 - 财政年份:2021
- 资助金额:
$ 60.6万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Information Freshness in Scalable and Energy Constrained Machine to Machine Wireless Networks
合作研究:CNS 核心:中:可扩展且能量受限的机器对机器无线网络中的信息新鲜度
- 批准号:
2106932 - 财政年份:2021
- 资助金额:
$ 60.6万 - 项目类别:
Continuing Grant
RAPID: Acoustic Communications and Sensing for COVID-19 Data Collection
RAPID:用于 COVID-19 数据收集的声学通信和传感
- 批准号:
2028547 - 财政年份:2020
- 资助金额:
$ 60.6万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Combating Latency and Disconnectivity in mmWave Networks: From Theory to Implementation
合作研究:CNS 核心:中:对抗毫米波网络中的延迟和断开连接:从理论到实施
- 批准号:
1955535 - 财政年份:2020
- 资助金额:
$ 60.6万 - 项目类别:
Continuing Grant
CNS Core: Small: New Caching Paradigms for Distributed and Dynamic Networks
CNS 核心:小型:分布式和动态网络的新缓存范例
- 批准号:
2007231 - 财政年份:2020
- 资助金额:
$ 60.6万 - 项目类别:
Standard Grant
CNS Core: Medium: Collaborative: Exploring and Exploiting Learning for Efficient Network Control: Non-Stationarity, Inter-Dependence, and Domain-Knowledge
CNS 核心:中:协作:探索和利用学习实现高效网络控制:非平稳性、相互依赖和领域知识
- 批准号:
1901057 - 财政年份:2019
- 资助金额:
$ 60.6万 - 项目类别:
Standard Grant
ICN-WEN: Collaborative Research: SPLICE: Secure Predictive Low-Latency Information Centric Edge for Next Generation Wireless Networks
ICN-WEN:协作研究:SPLICE:下一代无线网络的安全预测低延迟信息中心边缘
- 批准号:
1719371 - 财政年份:2017
- 资助金额:
$ 60.6万 - 项目类别:
Continuing Grant
CSR: NeTS: Small: Theoretical Foundations for Cache Networks: Performance Models, Algorithms, and Applications
CSR:NeTS:小型:缓存网络的理论基础:性能模型、算法和应用
- 批准号:
1717060 - 财政年份:2017
- 资助金额:
$ 60.6万 - 项目类别:
Standard Grant
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