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

CPS：突破：协作研究：WARP：广域辅助弹性保护

• 批准号: 1855854
• 负责人: Sukumar Brahma
• 金额: $ 8.17万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855854&HistoricalAwards=false
• 关键词: CPS; Breakthrough; Collaborative; Research; WARP

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.

电网无时无刻都在经历着扰动，这些扰动可以通过系统保护措施进行常规控制、管理或消除——系统保护措施是经过仔细的工程研究设计的，并经过多年运行经验的微调。尽管如此，电网有时会遇到破坏性事件，这些事件会迅速且不可阻挡地导致系统陷入停电。阻止此类停电仍然难以实现——主要是因为继电器（保护装置）基于本地数据运行，并且很容易出现隐藏故障，这些故障在显现之前无法检测到，从而导致误操作，而这些误操作有时会成为停电的诱因或促成因素。受总统关于复原力的政策指令（意味着预测、准备、抵御破坏性事件并从中恢复的能力）的启发，该项目提出了“WARP：广域辅助复原力保护”，这是一个增加了一层更精细（监督）层的范例智能来补充传统的保护智慧——我们称之为弹性保护。利用高保真度测量和计算来计算和分析电力系统的能量函数组件以识别干扰，WARP将允许对继电器进行监督——将证实正确的操作，并通过在合理的时间内明智地反转继电器操作来纠正误操作——框架。该项目还设想使用先进的估计技术来预测不稳定性，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，减少停电的规模、范围和进展，并提高电网（我们国家最关键的基础设施）的稳健性和弹性。在 WARP 中，破坏性事件是通过粒子滤波使用同步相量数据、能量函数和动态信息进行解密。这些信息被融合起来，提供一个全局数据集和情报信号，用于监督继电器，并预测系统稳定性。当监控信号纠正继电器的误操作或在有效时认可其操作时，就实现了弹性。这赋予了继电器事件后自动纠正能力——这是保护与稳定性关系中从未被探索/理解的功能。提出了研究延迟和不良数据影响的架构。 WARP 引入了新概念：电力系统事件的全局可检测性和可区分性、基于能量函数分量敏感性的稳定性预测，并使用一种新颖的因式分解方法：（CUR）保留数据可解释性以降低数据维度。所有提议的工具都将被封装到一个模拟框架中，以评估可扩展性和准确性运行时的权衡，并量化所实现的弹性程度。所提出的方案在极端事件期间的有效性将通过重新制定两个有据可查的停电序列来衡量。此外，还将对基准系统进行模拟，以评估可扩展性和准确性与运行时的权衡，并量化所实现的弹性程度。