CPS: Breakthrough: Collaborative Research: WARP: Wide Area assisted Resilient Protection

电网一直都在经历干扰，这些干扰通过系统保护措施进行常规控制、管理或消除-这些措施通过仔细的工程研究进行设计，并通过凝聚多年的运行经验进行微调。尽管如此，电网有时会遇到破坏性事件，这些事件可以迅速地，并且在某种程度上无法阻止地将系统推向停电。阻止这种停电仍然是难以捉摸的-主要是因为继电器（保护设备）根据本地数据操作，并且容易出现隐藏的故障，这些故障在出现之前无法检测到，导致误操作，有时会成为停电的沉淀剂或贡献者。受总统关于弹性的政策指令的启发-意味着预测，准备，承受和从破坏性事件中恢复的能力，该项目提出了“WARP：广域辅助弹性保护”，这是一种增加一层更精细（监督）智能以补充传统保护智慧的范例-我们称之为弹性保护。利用高保真测量和计算来计算和分析电力系统的能量函数分量以识别扰动，WARP将允许继电器被监督-正确的操作将被证实，并且误操作将通过在合理的时间范围内明智地反转继电器操作来补救。该项目还设想使用先进的估计技术预测不稳定性，从而具有前瞻性。这将为电网提供自动纠正和从误操作中恢复的能力，减少停电的大小，规模和进展，提高电网的鲁棒性和弹性-我们国家最关键的基础设施。在WARP中，破坏性事件通过使用同步相量数据，能量函数和动态状态信息通过粒子滤波来破译。这些信息被融合，以提供一个全局数据集和智能信号，监督继电器，并预测系统的稳定性。当监控信号纠正继电器的误操作或在有效时认可其动作时，可实现弹性。这赋予继电器事后自动纠正能力#8232;--在保护-稳定关系中从未探索/理解的特征。提出了研究延迟和坏数据影响的架构。WARP引入了新的概念：电力系统事件的全局可检测性和全局可检测性，基于#8232的稳定性预测&;的能量函数分量的灵敏度，并使用一种新的因式分解方法：（CUR）保持数据的可解释性，以减少数据的维数。所有建议
工具将被包装到一个模拟框架中，以评估可扩展性和准确性-运行时间权衡，并量化所实现的弹性程度。建议的计划在极端事件的有效性将通过重新制定两个有据可查的停电序列。此外，将在基准系统上进行模拟，以评估可扩展性和准确性-运行时权衡，并量化所实现的弹性程度。

The electric power grid experiences disturbances all the time that are routinely controlled, managed, or eliminated by system protection measures- designed by careful engineering studies and fine-tuned by condensing years of operational experience. Despite this, the grid sometimes experiences disruptive events that can quickly, and somewhat unstoppably catapult the system towards a blackout. Arresting such blackouts has remained elusive - mainly because relays (protection devices) operate on local data, and are prone to hidden faults that are impossible to detect until they manifest, resulting in misoperations that have sometime been precipitators or contributors to blackouts. Inspired by the Presidential policy directive on resilience -- meaning the ability to anticipate, prepare, withstand, and recover from disruptive events, this project proposes "WARP: Wide Area assisted Resilient Protection", a paradigm that adds a layer of finer (supervisory) intelligence to supplement conventional protection wisdom - which we call resilient protection. Exploiting high fidelity measurements and computation to calculate and analyze energy function components of power systems to identify disturbances, WARP would allow relays to be supervised - correct operations would be corroborated, and misoperations will be remedied by judiciously reversing the relay operation in a rational time-frame. The project also envisions predicting instability using advanced estimation techniques, thus being proactive. This will provide power grid the ability to auto-correct and bounce back from misoperations, curtailing the size, scale and progression of blackouts and improving the robustness and resilience of the electric grid -- our nation's most critical infrastructure.In WARP, disruptive events are deciphered by using synchrophasor data, energy functions, and dynamic state information via particle filtering. The information is fused to provide a global data set and intelligence signal that supervises relays, and also to predict system stability. Resilience is achieved when the supervisory signal rectifies the misoperation of relays, or endorses their action when valid. This endows relays with post-event-auto-correct abilities 
- a feature that never been explored/understood in the protection-stability nexus. Architectures to study the effect of latency and bad data are proposed. WARP introduces new notions: global detectability and distinguishability for power system events, stability prediction based on
the sensitivity of the energy function components and uses a novel factorization method: (CUR) preserving data interpretability to reduce data dimensionality. All the proposed
tools will be wrapped into a simulation framework to assess scalability and accuracy-runtime tradeoffs, and quantify the degree of resilience achieved. The effectiveness of the proposed scheme during extreme events will be measured by reenacting two well-documented blackout sequences. In addition, simulations on benchmarked systems will be performed to assess scalability and accuracy-runtime tradeoffs, and quantify the degree of resilience achieved.