CPS: Synergy: Collaborative Research: SMARTER - Smart Manager for Adaptive and Real-Time Decisions in Building ClustERs

CPS:协同:协作研究:SMARTER - 构建集群中自适应和实时决策的智能管理器

基本信息

  • 批准号:
    1239257
  • 负责人:
  • 金额:
    $ 40万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-10-01 至 2016-09-30
  • 项目状态:
    已结题

项目摘要

1239257 (Wu). Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools. In this research, a synergistic decision framework is established for temporally, spatially distributed building clusters to work as an adaptive and robust system within a smart grid. The framework includes innovative algorithms and tools for building energy modeling, intelligent data fusion, decentralized decisions and adaptive decisions to address theoretical and practical challenges in next-generation building systems. The research develops cyber-physical engineering tools for demand side load management which has been identified as a major challenge by energy industries. It fundamentally transforms the current centralized and uni-directional power distribution business model to a decentralized and multi-directional power sharing and distribution business model, reducing overall energy consumption and allowing for optimal decisions in changing operation environments. Education and outreach efforts include developing novel educational modules disseminated at the K-12 levels and through the ASEE eGFI repository. Further educational impact occurs through integration with multiple undergraduate and graduate courses at each institution, and with community service groups. Impact is also expanded to the broader energy industry and the operation of healthcare delivery and urban transportation systems through our industry collaborations. http://swag.engineering.asu.edu/ 1239247 (Wen). Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools. In this research, a synergistic decision framework is established for temporally, spatially distributed building clusters to work as an adaptive and robust system within a smart grid. The framework includes innovative algorithms and tools for building energy modeling, intelligent data fusion, decentralized decisions and adaptive decisions to address theoretical and practical challenges in next-generation building systems. The research develops cyber-physical engineering tools for demand side load management which has been identified as a major challenge by energy industries. It fundamentally transforms the current centralized and uni-directional power distribution business model to a decentralized and multi-directional power sharing and distribution business model, reducing overall energy consumption and allowing for optimal decisions in changing operation environments. Education and outreach efforts include developing novel educational modules disseminated at the K-12 levels and through the ASEE eGFI repository. Further educational impact occurs through integration with multiple undergraduate and graduate courses at each institution, and with community service groups. Impact is also expanded to the broader energy industry and the operation of healthcare delivery and urban transportation systems through our industry collaborations. http://swag.engineering.asu.edu/ 1239093 (Lewis). Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools. In this research, a synergistic decision framework is established for temporally, spatially distributed building clusters to work as an adaptive and robust system within a smart grid. The framework includes innovative algorithms and tools for building energy modeling, intelligent data fusion, decentralized decisions and adaptive decisions to address theoretical and practical challenges in next-generation building systems. The research develops cyber-physical engineering tools for demand side load management which has been identified as a major challenge by energy industries. It fundamentally transforms the current centralized and uni-directional power distribution business model to a decentralized and multi-directional power sharing and distribution business model, reducing overall energy consumption and allowing for optimal decisions in changing operation environments. Education and outreach efforts include developing novel educational modules disseminated at the K-12 levels and through the ASEE eGFI repository. Further educational impact occurs through integration with multiple undergraduate and graduate courses at each institution, and with community service groups. Impact is also expanded to the broader energy industry and the operation of healthcare delivery and urban transportation systems through our industry collaborations.
1239257(WU)。 传统上,建筑物被视为仅仅能源消费者。但是,借助新的电网基础设施和分布式能源,建筑物不仅可以消耗能源,而且可以输出能源。结果,该项目删除了同一集群或群集和电网之间的建筑物之间的传统界限,将单个智能建筑物转换为由网络支持工具启用的Netzero建筑集群。在这项研究中,建立了一个协同的决策框架,用于时间上,空间分布的建筑群集,以作为智能网格中的自适应和健壮的系统工作。 该框架包括用于构建能源建模的创新算法和工具,智能数据融合,分散的决策和自适应决策,以应对下一代建筑系统中的理论和实际挑战。 该研究开发了用于需求侧负荷管理的网络物理工程工具,该工具已被能源行业确定为主要挑战。它从根本上将当前的集中式和单向电源分销业务模型转变为分散和多向电源共享和分销业务模型,从而减少了整体能源消耗,并允许在不断变化的操作环境中做出最佳决策。教育和推广工作包括开发在K-12级别和ASEE EGFI存储库中传播的新型教育模块。通过与每个机构的多个本科和研究生课程以及与社区服务组的多个本科和研究生课程的融合,会产生进一步的教育影响。影响还扩大到更广泛的能源行业以及通过我们的行业合作的医疗保健交付和城市运输系统的运行。 http://swag.engineering.asu.edu/ 1239247(wen)。 传统上,建筑物被视为仅仅能源消费者。但是,借助新的电网基础设施和分布式能源,建筑物不仅可以消耗能源,而且可以输出能源。结果,该项目删除了同一集群或群集和电网之间的建筑物之间的传统界限,将单个智能建筑物转换为由网络支持工具启用的Netzero建筑集群。在这项研究中,建立了一个协同的决策框架,用于时间上,空间分布的建筑群集,以作为智能网格中的自适应和健壮的系统工作。该框架包括用于构建能源建模的创新算法和工具,智能数据融合,分散的决策和自适应决策,以应对下一代建筑系统中的理论和实际挑战。该研究开发了用于需求侧负荷管理的网络物理工程工具,该工具已被能源行业确定为主要挑战。它从根本上将当前的集中式和单向电源分销业务模型转变为分散和多向电源共享和分销业务模型,从而减少了整体能源消耗,并允许在不断变化的操作环境中做出最佳决策。教育和推广工作包括开发在K-12级别和ASEE EGFI存储库中传播的新型教育模块。通过与每个机构的多个本科和研究生课程以及与社区服务组的多个本科和研究生课程的融合,会产生进一步的教育影响。影响还扩大到更广泛的能源行业以及通过我们的行业合作的医疗保健交付和城市运输系统的运行。 http://swag.engineering.asu.edu/ 1239093(刘易斯)。 传统上,建筑物被视为仅仅能源消费者。但是,借助新的电网基础设施和分布式能源,建筑物不仅可以消耗能源,而且可以输出能源。结果,该项目删除了同一集群或群集和电网之间的建筑物之间的传统界限,将单个智能建筑物转换为由网络支持工具启用的Netzero建筑集群。在这项研究中,建立了一个协同的决策框架,用于时间上,空间分布的建筑群集,以作为智能网格中的自适应和健壮的系统工作。该框架包括用于构建能源建模的创新算法和工具,智能数据融合,分散的决策和自适应决策,以应对下一代建筑系统中的理论和实际挑战。该研究开发了用于需求侧负荷管理的网络物理工程工具,该工具已被能源行业确定为主要挑战。它从根本上将当前的集中式和单向电源分销业务模型转变为分散和多向电源共享和分销业务模型,从而减少了整体能源消耗,并允许在不断变化的操作环境中做出最佳决策。教育和推广工作包括开发在K-12级别和ASEE EGFI存储库中传播的新型教育模块。通过与每个机构的多个本科和研究生课程以及与社区服务组的多个本科和研究生课程的融合,会产生进一步的教育影响。影响还扩大到更广泛的能源行业以及通过我们的行业合作的医疗保健交付和城市运输系统的运行。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Teresa Wu其他文献

A sparse partitioned-regression model for nonlinear system–environment interactions
非线性系统-环境相互作用的稀疏分区回归模型
  • DOI:
    10.1080/24725854.2017.1299955
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Shuluo Ning;E. Byon;Teresa Wu;Jing Li
  • 通讯作者:
    Jing Li
Uncertainty Quantification in Radiogenomics: EGFR Amplification in Glioblastoma
放射基因组学中的不确定性定量:胶质母细胞瘤中的 EGFR 扩增
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Leland S. Hu;Lujia Wang;A. Hawkins;Jenny M. Eschbacher;K. Singleton;P. Jackson;K. Clark;Christopher P. Sereduk;Sen Peng;Panwen Wang;Junwen Wang;L. Baxter;Kris A. Smith;Gina L. Mazza;Ashley M. Stokes;B. Bendok;Richard S. Zimmerman;C. Krishna;Alyx Porter;M. Mrugala;J. Hoxworth;Teresa Wu;Nhan L Tran;Kristin R Swanson;Jing Li
  • 通讯作者:
    Jing Li
Multi-stage DEA as a Measurement of Progress in Environmentally Benign Manufacturing
多阶段 DEA 作为环保制造进展的衡量标准
  • DOI:
  • 发表时间:
    2006
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Teresa Wu;J. Fowler;Thomas E. Callarman;A. Moorehead
  • 通讯作者:
    A. Moorehead
A Mutual Knowledge Distillation-Empowered AI Framework for Early Detection of Alzheimer’s Disease Using Incomplete Multi-Modal Images
一种基于相互知识蒸馏的人工智能框架,利用不完整的多模态图像早期检测阿尔茨海默病
  • DOI:
    10.1101/2023.08.24.23294574
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Min Gu Kwak;Yindan Su;Kewei Chen;D. Weidman;Teresa Wu;F. Lure;Jing Li
  • 通讯作者:
    Jing Li
Exercise test-induced arrhythmias.
运动试验诱发的心律失常。
  • DOI:
    10.1016/j.pcad.2005.02.011
  • 发表时间:
    2005
  • 期刊:
  • 影响因子:
    9.1
  • 作者:
    James G Beckerman;Teresa Wu;S. Jones;V. Froelicher
  • 通讯作者:
    V. Froelicher

Teresa Wu的其他文献

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{{ truncateString('Teresa Wu', 18)}}的其他基金

Collaborative Research: CPS: TTP Option: Medium: i-HEAR: immersive Human-On-the-Loop Environmental Adaptation for Stress Reduction
合作研究:CPS:TTP 选项:中:i-HEAR:沉浸式人类循环环境适应以减轻压力
  • 批准号:
    2038905
  • 财政年份:
    2021
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant
Collaborative Research: AccelNet: An International Network of Networks for Well-being in the Built Environment (IN2WIBE)
合作研究:AccelNet:建筑环境福祉国际网络 (IN2WIBE)
  • 批准号:
    1931254
  • 财政年份:
    2019
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant
SCC-Planning: Smart, Connected, Engaged Senior Communities
SCC 规划:智能、互联、参与的老年人社区
  • 批准号:
    1737454
  • 财政年份:
    2017
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant
CAREER: Design and Implementation of a Virtual Product Development Environment
职业:虚拟产品开发环境的设计和实现
  • 批准号:
    0239276
  • 财政年份:
    2003
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant

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多源环境能量协同作用的微功率高效整流机制研究
  • 批准号:
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SiO2@LDH核壳晶种协同提升海工大掺量固废混凝土早期强度与抗氯离子渗透性的作用机制
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水中放电产生微纳气泡的空化形成机制、强化传质作用和协同生物效应
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基于微区异构基元有序化精准构筑提高交通铝合金形/性的协同作用机制
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香精油微胶囊黏流态内芯构建及氢键作用协同粘度增强实现超长留香机制研究
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CPS:Medium:Collaborative Research: High-Fidelity High-Resolution and Secure Monitoring and Control of Future Grids: a synergy of AI, data science, and hardware security
CPS:中:协作研究:未来电网的高保真高分辨率和安全监控:人工智能、数据科学和硬件安全的协同作用
  • 批准号:
    1932196
  • 财政年份:
    2019
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CPS:Medium:Collaborative Research:High-Fidelity High-Resolution and Secure Monitoring and Control of Future Grids: a synergy of AI, data science, and hardware security
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  • 批准号:
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CPS: Synergy: Collaborative Research: Towards Effective and Efficient Sensing-Motion Co-Design of Swarming Cyber-Physical Systems
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  • 批准号:
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CPS: Synergy: Collaborative Research: DEUS: Distributed, Efficient, Ubiquitous and Secure Data Delivery Using Autonomous Underwater Vehicles
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CPS: Synergy: Collaborative Research: TickTalk: Timing API for Federated Cyberphysical Systems
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    1645578
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    2018
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