CRISP 2.0 Type 2: Collaborative Research: Exploiting Interdependencies Between Computing and Electrical Power Infrastructures to Maximize Resilience and Flexibility
CRISP 2.0 Type 2: Collaborative Research: Exploiting Interdependencies Between Computing and Electrical Power Infrastructures to Maximize Resilience and Flexibility
批准号:
1832230
负责人:
Andrew Chien
金额:
$111.7万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2023-08-31
中文摘要
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英文摘要
Electrical power and computing infrastructures are increasingly interdependent. Computing provides information that enables decision-making, commerce, government, and social interaction, and disruptions in power supply may trigger critical losses of information and decision-making capabilities, resulting in the potential for significant economic losses. To reduce critical risks and identify synergies from the growing interdependence of these infrastructures, the objective of this Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) project is to increase the resilience and efficiency of the electrical power and computing infrastructures by understanding how to exploit and maximize emerging synergies between the two infrastructures. The project will have broad impact in computing and power grid research and industrial practice, enabling better design of power and computing infrastructures, leading to improved management and benefiting their resilience and efficiency. Project results will be disseminated to the research and industrial communities via papers, talks, and models as open-source software. Students and postdoctoral fellows involved will gain a holistic systems-level understanding, giving them the ability to combine concepts in optimization and energy markets.This project will develop optimization formulations for theoretical insights on resiliency and economic benefits that can result from infrastructure coordination. It will also investigate new market designs that properly incentivize the provision of spatio-temporal load modulation flexibility at large-scale (in the form of virtual power flows) among various kinds of computing assets, exploring different levels of coordination (because distinct business and regulatory constitutions govern them) and feasible computing flexibility. To achieve these goals, the project will embed those optimization formulations within stochastic programming models to identify optimal system layouts that benefit both infrastructures. In addition, the project will develop suitable utility functions for varied types of computing providers that the ISOs (Independent System Operators under Federal Energy Regulatory Commission) can use to quantify costs associated with load flexibility.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(9)
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DOI:
10.1145/3575813.3595197
发表时间:
2023-01
期刊:
Proceedings of the 14th ACM International Conference on Future Energy Systems
影响因子:
--
作者:
[Liuzixuan Lin;A. Chien]
通讯作者:
Liuzixuan Lin;A. Chien
DOI:
10.1109/cdc45484.2021.9683117
发表时间:
2021
期刊:
2021 60th IEEE Conference on Decision and Control (CDC
影响因子:
--
作者:
[Gao, Zuguang, Alshehri, Khaled, Birge, John R.]
通讯作者:
Birge, John R.
DOI:
10.1145/3447555.3464868
发表时间:
2021-06
期刊:
Proceedings of the Twelfth ACM International Conference on Future Energy Systems
影响因子:
--
作者:
[Liuzixuan Lin;V. Zavala;A. Chien]
通讯作者:
Liuzixuan Lin;V. Zavala;A. Chien
Network Structure and its Impact on Commodity Markets †
网络结构及其对商品市场的影响 –
DOI:
10.1111/poms.13513
发表时间:
2021
期刊:
Production and Operations Management
影响因子:
5
作者:
[Birge, John R.]
通讯作者:
Birge, John R.
Beyond PUE: Flexible Datacenters Empowering the Cloud to Decarbonize
超越 PUE:灵活的数据中心使云脱碳
DOI:
--
发表时间:
2022
期刊:
USENIX Hot Carbon
影响因子:
--
作者:
[Andrew A. Chien, Chaojie Zhang, Liuzixuan Lin]
通讯作者:
Chaojie Zhang, Liuzixuan Lin
共 9 条
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NSF Young Investigator: Concurrent Object-Oriented Programming Support for Irregular Parallel Applications
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PDS: A Flexible Architecture for Executing Component Software at 100 Teraops
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NSF Young Investigator: Concurrent Object-Oriented Programming Support for Irregular Parallel Applications
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High-Performance, Adaptive Routing in Multiprocessor Networks
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Efficient Execution of Fine-Grained Concurrent Programs
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依托单位:
国内基金
海外基金
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