Preserving Confidentiality of Sensitive Information in Power System Models
Abstract:
The electric power grid is a critical national infrastructure that is increasing vulnerable to malicious physical and cyber attacks. To alleviate the likelihood such attacks, national security policy severely restricts the disclosure of sensitive information such as grid topology and operational parameters. In addition, there is also a critical need to foster cooperation among the growing number of participants in a microgrid‐enabled electric marketplace. However, the market participants are not inclined to share information about their grid with other participants so as to not jeopardize their economic competitiveness. Motivated by this need for increased cyber‐physical security and economic confidentiality, we are developing techniques to obfuscate sensitive design information in power system models without sacrificing the quality of the solutions obtained from such models. Specifically, solution approaches are being developed to hide sensitive structural information in Direct Current (DC) and Alternating Current (AC) Optimal Power Flow and Optimal Power Dispatch models. The project is also developing secure multi‐party methods where the market participants collectively optimize the grid operations while only sharing encrypted private sensitive information. 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.
Submitted by Parmesh Ramanathan
on
Abstract:
The electric power grid is a critical national infrastructure that is increasing vulnerable to malicious physical and cyber attacks. To alleviate the likelihood such attacks, national security policy severely restricts the disclosure of sensitive information such as grid topology and operational parameters. In addition, there is also a critical need to foster cooperation among the growing number of participants in a microgrid‐enabled electric marketplace. However, the market participants are not inclined to share information about their grid with other participants so as to not jeopardize their economic competitiveness. Motivated by this need for increased cyber‐physical security and economic confidentiality, we are developing techniques to obfuscate sensitive design information in power system models without sacrificing the quality of the solutions obtained from such models. Specifically, solution approaches are being developed to hide sensitive structural information in Direct Current (DC) and Alternating Current (AC) Optimal Power Flow and Optimal Power Dispatch models. The project is also developing secure multi‐party methods where the market participants collectively optimize the grid operations while only sharing encrypted private sensitive information. 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.