EAGER: Collaborative Research:Blockchain Graphs as Testbeds of Power Grid Resilience and Functionality Metrics
EAGER: Collaborative Research:Blockchain Graphs as Testbeds of Power Grid Resilience and Functionality Metrics
批准号:
2039701
负责人:
Jie Zhang
金额:
$15.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-11-15 至 2024-10-31
中文摘要
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英文摘要
Rapid adoption of renewable energy, growth of distributed generation technologies and microgrid deployment, widespread implementations of IoT devices and associated cybersecurity concerns have led to an ever expanding risk landscape and have, in turn, shifted the focus from energy system protection to resilience. Furthermore, the past two decades have seen a consistently increasing interest in the application of tools developed in the interdisciplinary field of complex network analysis to enhance our understanding of functionality, security, and reliability of power systems and critical infrastructures in which power grid networks serve as an integral constituent. Such systems are intrinsically interconnected and interdependent, and as a result, failure of one component due to manmade and natural cause, e.g., adverse weather, aging, and intentional attacks such as terrorism, can lead to a catastrophic cascade of failures. However, one of the key obstacles for developing systematic and reliable assessment of power grid and critical infrastructure resiliency under various threats is unavailability of ground truth data on system response to adversaries due to data security, privacy and confidentiality. Motivated by these problems rooted in the analysis of modern power grids but inherent to many other complex network systems and given public availability of all blockchain transaction transactions, we propose to use blockchain graphs as a test-bed for validation of functionality and resilience metrics on complex power grid networks.Exploring power grid sensitivity to targeted attacks and failures in scenarios allowing for validation of any proposed methodology against ground truth is the key toward developing reliable risk mitigation strategies for power systems. The novel research approaches to be developed in this project aim to lay foundations for deeper knowledge integration and transfer across power systems, finance, social sciences and other disciplines by utilizing graph-theoretic analysis and adopting a common mathematical language of computational topology. By promoting new synergistic research initiatives, the project will further advance knowledge creation not only on power grids and blockchain but on modern complex networks, from brain connectome to social media platforms to telecommunication-- thereby facilitating resilience and sustainability of our society.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.
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DOI:
10.48550/arxiv.2211.13708
发表时间:
2022-11
期刊:
ArXiv
影响因子:
--
作者:
[C. Akcora;Murat Kantarcioglu;Y. Gel;Baris Coskunuzer]
通讯作者:
C. Akcora;Murat Kantarcioglu;Y. Gel;Baris Coskunuzer
DOI:
--
发表时间:
2022
期刊:
影响因子:
--
作者:
[Kiarash Shamsi;Friedhelm Victor;Murat Kantarcioglu;Y. Gel;C. Akcora]
通讯作者:
Kiarash Shamsi;Friedhelm Victor;Murat Kantarcioglu;Y. Gel;C. Akcora
Tlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep Learning
Tlife-GDN:通过持久同源性和几何深度学习检测和预测时空异常
DOI:
--
发表时间:
2022
期刊:
Pacific-Asia Conference on Knowledge Discovery and Data Mining
影响因子:
--
作者:
[Zhen, Zhiwei, Chen, Yuzhou, Segovia-Dominguez, Ignacio, Gel, Yulia R.]
通讯作者:
Gel, Yulia R.
DOI:
--
发表时间:
2021-10
期刊:
影响因子:
--
作者:
[Yuzhou Chen;Baris Coskunuzer;Y. Gel]
通讯作者:
Yuzhou Chen;Baris Coskunuzer;Y. Gel
DOI:
10.1609/aaai.v36i6.20583
发表时间:
2021-12
期刊:
影响因子:
--
作者:
[Yuzhou Chen;Y. Gel;H. Poor]
通讯作者:
Yuzhou Chen;Y. Gel;H. Poor
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Neural mechanisms for phonological alternation with high and low productivity - a case study on tone sandhi
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SHINE: Understanding Characteristics of Coronal Mass Ejections (CMEs)
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