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.

电网是国家关键基础设施，越来越容易受到恶意物理和网络攻击。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，只有在严格的保密协议下才能共享。在微电网支持的电力市场中，越来越多的参与者也越来越需要促进合作。然而，为了保持经济竞争力，市场参与者不愿意与其他参与者共享有关其电网的敏感信息。出于提高网络物理安全性和经济保密性的需求，该项目正在开发技术来混淆电力系统模型中的敏感设计信息，而不会危及从此类模型获得的解决方案的质量。具体来说，已经开发了解决方案来隐藏直流 (DC) 最佳潮流模型中的敏感结构信息。这些方法目前正在扩展到交流 (AC) 最佳潮流模型。该项目还正在开发安全的多方方法，市场参与者共同优化电网运营，同时仅共享加密的私人敏感信息。最后，该项目正在结合安全的市场运作来共同解决最佳电力调度问题，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掩盖许多问题中的敏感信息，这些问题可以表述为线性或非线性规划优化。