TWC: Small: Privacy Preserving Cooperation among Microgrids for Efficient Load Management on the Grid

智能电网将传感器和通信基础设施集成到现有电网中，以实现运营智能。微电网的概念是与智能电网结合出现的，其中电网的小部分可以被隔离成自给自足的岛屿，以用它们的本地能量供给它们自己的需求负载，例如，风能太阳能迄今为止，微电网开始开发协作模型以进一步提高全局和局部负载管理的性能，例如全局/局部负载平衡、能量交换以及与微电网集成的输电网络拓扑设计/升级。然而，微电网之间的合作要求它们显式地共享本地敏感的电网运行信息以实现全局性能优化，从而损害了微电网的隐私性。然后，微电网的隐私问题将阻碍合作模型的开发和实施，使得通过微电网在电网上的合作的显著益处可能不可用。该项目解决了这种合作中的隐私问题，使微电网能够有效地管理其本地负载，以及促进主电网操纵全球负载与有限的披露。该项目提出了一套新颖的隐私保护合作模型/技术，分布式微电网，有效地推进电力网络的负载管理。可证明的隐私/安全性是确保在端到端的合作过程中，包括私人分析从不同的微电网收集的数据和私人实施的方案/解决方案来自合作模型，通过组成密码原语与安全多方计算（SMC）理论和/或强加定义严格的隐私概念。以严格的标准确保隐私保护将允许以先前由于隐私问题而禁止的方式收集和使用数据，然后提高运营效率和用户接受度。通过隐私保护合作的负载管理进一步优化分配分布式能源，并在更安全，可靠和高效的智能电网基础设施中最大限度地降低传输和存储成本。该项目还通过激发本科生加入科学，技术，工程和数学（STEM）研究来整合研究和教育。

Smart grid integrates sensors and communication infrastructure into the existing power grid to enable operational intelligence. The concept of microgrid is emerging in conjunction with the smart grid wherein small segments of the grid can be isolated into self-sufficient islands to feed their own demand load with their local energy, e.g., wind, solar. To date, microgrids begin to develop cooperative models for further improving the performance of global and local load management, such as global/local load balancing, energy exchange, and power transmission network topology design/upgrade with the integration of microgrids. However, all the cooperation among microgrids requests them to explicitly share their local sensitive grid operational information for global performance optimization, and thus compromises the privacy of microgrids. Then, microgrids' privacy concerns would impede the development and implementation of the cooperative models such that significant benefits via microgrids' cooperation on the power grid may not be available. This project tackles the privacy concerns in such cooperation, and enables microgrids to efficiently manage their local loads as well as facilitate the main grid to manipulate the global load with limited disclosure.This project proposes a suite of novel privacy preserving cooperative models/techniques for distributed microgrids to efficiently advance load management on the power grid. Provable privacy/security is ensured in the end-to-end process of cooperation, including privately analyzing data collected from different microgrids and privately implementing the schemes/solutions derived from the cooperative models, by composing cryptographic primitives with the secure multiparty computation (SMC) theory and/or imposing defined rigorous privacy notions. Ensuring privacy protection with rigorous standards will allow data to be collected and used in ways that were prohibitive earlier due to the privacy concerns, and then improve both operational efficiency and user acceptance. Load management via privacy preserving cooperation further optimally allocates distributed energy and minimizes the transmission and storage costs in a more secure, reliable and efficient smart grid infrastructure. This project also integrates research and education by exciting undergraduates to join the Science, Technology, Engineering and Math (STEM) research.