CPS: Synergy: Preserving Confidentiality of Sensitive Information in Power System Models

CPS：协同：保护电力系统模型中敏感信息的机密性

• 批准号: 1329452
• 负责人: Parameswaran Ramanathan
• 金额: $ 67.84万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329452&HistoricalAwards=false
• 关键词: CPS; Synergy; Preserving; Confidentiality; Sensitive

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.

电网是国家的关键基础设施，越来越容易受到恶意的物理和网络攻击。因此，描述电网拓扑和组件的详细数据被认为是高度敏感的信息，只能在严格的保密协议下共享。此外，越来越需要促进微电网电力市场越来越多的参与者之间的合作。然而，为了保持其经济竞争力，市场参与者不倾向于与其他参与者共享有关其电网的敏感信息。出于对提高网络物理安全和经济机密性的需求，该项目正在开发技术，以混淆电力系统模型中的敏感设计信息，而不会损害从这些模型中获得的解决方案的质量。具体而言，解决方案的方法已经开发，以隐藏敏感的结构信息在直流（DC）最优潮流模型。这些方法目前正在扩展到交流（AC）最优潮流模型。该项目还在开发安全的多方方法，市场参与者在共享加密的私人敏感信息的同时共同优化电网运营。最后，该项目正在将安全的市场操作纳入联合解决最优电力调度问题，而不会将每个参与者的敏感私人信息泄露给其他参与者。该项目开发的技术有可能广泛影响电力系统以外的领域。该项目中开发的一般原则可用于屏蔽许多问题中的敏感信息，这些问题可被表述为线性或非线性规划优化。