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SMART SENSOR FOR ONLINE SITUATION AWARENESS IN POWER GRIDS

机译:用于电网的在线状态感知的智能传感器

摘要

Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.
机译:电网中的波形通常会显示由系统运行条件,内部和外部不确定性等因素驱动的具有特定特征和特性的特定模式。这促使在测量点(变电站)观察到不同类型的波形。创新的下一代智能传感器技术包括一个嵌入了复杂分析功能的测量单元,用于电网在线监视和态势感知。智能传感器为现有的相量测量单元(PMU)和智能电子设备(IED)带来了更高的智能水平。它释放了高级信号处理和机器学习的全部潜力,可用于分布式范例中的在线电网监控。在智能传感器中,有几个相互连接的单元,用于信号采集,特征提取,基于机器学习的事件检测以及一组多种测量算法,其中,根据检测到的工作条件实时选择最佳拟合算法。分布式智能机制将此类分析嵌入传感器内并更靠近生成数据的地方,从而减轻了通信失败和等待时间以及恶意网络威胁的潜在风险,这些风险否则将损害最终用途应用在远程的可信赖性控制中心。智能传感器在电网中的多种主要条件下实现了令人满意的分类精度,并因此提高了整个电网的测量质量。

著录项

  • 公开/公告号US2020212676A1

    专利类型

  • 公开/公告日2020-07-02

    原文格式PDF

  • 申请/专利权人 THE GEORGE WASHINGTON UNIVERSITY;

    申请/专利号US201916699602

  • 发明设计人 PAYMAN DEHGHANIAN;SHIYUAN WANG;

    申请日2019-11-30

  • 分类号H02J3/26;G06F17/14;H03M7/30;G06N3/04;

  • 国家 US

  • 入库时间 2022-08-21 11:21:24

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