| NSF Org: |
ECCS Division of Electrical, Communications and Cyber Systems |
| Recipient: |
|
| Initial Amendment Date: | November 12, 2020 |
| Latest Amendment Date: | August 24, 2021 |
| Award Number: | 2039701 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Eyad Abed
eabed@nsf.gov (703)292-2303 ECCS Division of Electrical, Communications and Cyber Systems ENG Directorate for Engineering |
| Start Date: | November 15, 2020 |
| End Date: | October 31, 2024 (Estimated) |
| Total Intended Award Amount: | $150,000.00 |
| Total Awarded Amount to Date: | $186,729.00 |
| Funds Obligated to Date: |
|
| History of Investigator: |
|
| Recipient Sponsored Research Office: |
800 WEST CAMPBELL RD. RICHARDSON TX US 75080-3021 (972)883-2313 |
| Sponsor Congressional District: |
|
| Primary Place of Performance: |
800 W Campbell Rd Richardson TX US 75080-3021 |
| Primary Place of
Performance Congressional District: |
|
| Unique Entity Identifier (UEI): |
|
| Parent UEI: |
|
| NSF Program(s): |
GOALI-Grnt Opp Acad Lia wIndus, EPCN-Energy-Power-Ctrl-Netwrks |
| Primary Program Source: |
|
| Program Reference Code(s): |
|
| Program Element Code(s): |
|
| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Modern infrastructure systems tend to be intrinsically interconnected and interdependent; as a result, failure of one system 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. Hence, understanding the infrastructure's ability to maintain its functionality and rapidly recover from a disruptive event is vital for developing efficient risk management strategies and, more broadly, for ensuring national security. Nowadays, the primary approach to address the system's resilience, particularly, in case of the energy sector, is to use synthetic power grid models which aim to mimic the properties of the real grids without disclosing sensitive data. However, such synthetic networks may not resemble many important characteristics of the real systems, especially in dynamic settings. Motivated by these problems rooted in the analysis of modern power grids but inherent to many other complex systems and given public availability of all blockchain transaction transactions, we used blockchain graphs as a test-bed for validation of functionality and resilience metrics on complex power grid networks.
Throughout the course of the project, we have explored such fundamental problems as similarity of topological and geometric properties of power grid networks and blockchain transaction graphs, topological tools for anomaly detection and early warning algorithms in blockchain graphs and critical infrastructures, as well as topological graph classification in a context of resiliency quantification. The project has provided numerous opportunities for professional development of early career researchers.
Last Modified: 01/22/2025
Modified by: Jie Zhang
Please report errors in award information by writing to: awardsearch@nsf.gov.
