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.

电力电网一直都经历了由系统保护措施常规控制，管理或消除的干扰，并通过仔细的工程研究设计，并通过浓缩多年的运营经验进行了微调。尽管如此，网格有时会遇到可以快速而有些不可阻挡的系统弹射到停电的破坏性事件。逮捕这种停电仍然难以捉摸 - 主要是因为继电器（保护设备）在当地数据上运行，并且很容易被隐藏的断层，直到它们表现出来，这些断层却导致误传导致有时是阻止者或停电的贡献者。受到弹性的总统政策指令的启发，这意味着能够预测，准备，承受和从破坏性事件中恢复过来，该项目提出了“ Warp：广泛的区域辅助弹性保护”，这是一种范式，该范式增加了一层优质（监督）智能，以补充常规保护智慧 - 我们称之为弹性保护。利用高保真度的测量和计算来计算和分析功率系统的能量功能组成部分以识别干扰，扭曲将允许继电器受到监督 - 正确的操作将得到佐证，并通过在合理的时间情节中明智地逆转中继操作来纠正误差。该项目还设想使用高级估计技术预测不稳定，因此是主动的。这将为电网提供自动纠正和反弹的能力，从疏忽，减少停电的大小，规模和进步，并提高电网的鲁棒性和弹性 - 我们国家最关键的基础架构。在经来说，扭曲，颠覆性事件通过使用同步的数据，能量数据，以及动态粒子滤过的能源数据来破译，并通过synchrophasor数据进行破译。将信息融合在一起，以提供监督继电器的全局数据集和智能信号，并预测系统稳定性。当监督信号纠正继电器的疏忽或在有效时认可其行动时，可以实现弹性。这赋予了事后自动校正能力＆＃8232; - 在保护稳定性Nexus中从未探索过/理解的功能。提出了研究潜伏期和不良数据影响的体系结构。 WARP引入了新的概念：全球可检测性和电力系统事件的区分性，基于＆＃8232;能量函数组件的敏感性的稳定性预测，并使用一种新颖的分解方法：（CUR）保留数据解释性以降低数据维度。所有提议的工具将包裹在模拟框架中，以评估可扩展性和准确度的折衷方案，并量化实现的弹性程度。在极端事件期间提出的方案的有效性将通过重演两个有据可查的停电序列来衡量。此外，将对基准系统进行模拟，以评估可伸缩性和准确度的折衷方案，并量化实现的弹性程度。