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Cyber-Physical Systems Virtual Organization
Read-only archive of site from September 29, 2023.
CPS-VO
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Projects
CPS: Synergy: Preserving Confidentiality of Sensitive Information in Power System Models
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Submitted by parmesh on Fri, 12/18/2015 - 6:02pm
Project Details
Lead PI:
Parmesh Ramanathan
Co-PI(s):
Bernard Lesieutre
Performance Period:
10/01/13
-
09/30/16
Institution(s):
University of Wisconsin-Madison
Sponsor(s):
National Science Foundation
Award Number:
1329452
1316 Reads. Placed 242 out of 804 NSF CPS Projects based on total reads on all related artifacts.
Abstract:
The electric power grid is a national critical infrastructure that is increasing vulnerable to malicious physical and cyber attacks. As a result, detailed data describing grid topology and components is considered highly sensitive information that can be shared only under strict non-disclosure agreements. There is also increasing need to foster cooperation among the growing number of participants in microgrid-enabled electric marketplace. However, to maintain their economic competitiveness, the market participants are not inclined to share sensitive information about their grid with other participants. Motivated by this need for increased cyber-physical security and economic confidentiality, the project is developing techniques to obfuscate sensitive design information in power system models without jeopardizing the quality of the solutions obtained from such models. Specifically, solution approaches have been developed to hide sensitive structural information in Direct Current (DC) Optimal Power Flow models. These approaches are currently being extended to Alternating Current (AC) Optimal Power Flow models. The project is also developing secure multi-party methods where the market participants collectively optimize the grid operation while only sharing encrypted private sensitive information. Finally, the project is incorporating secure market operations in jointly solving the Optimal Power Dispatch problem without revealing sensitive private information from each participant to other participants. The techniques developed in this project have the potential to broadly impact areas beyond power systems. The general principles developed in the project can be used to mask sensitive information in many problems that can be formulated as a linear or non-linear programming optimization.
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CPS Domains
Energy Sector
Modeling
Critical Infrastructure
Foundations