Smart sensor for online situational awareness in power grids
Abstract
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 prevailingmore »
- Inventors:
- Issue Date:
- Research Org.:
- George Washington Univ., Washington, DC (United States)
- Sponsoring Org.:
- USDOE Office of Electricity (OE)
- OSTI Identifier:
- 1986933
- Patent Number(s):
- 11527891
- Application Number:
- 16/699,602
- Assignee:
- The George Washington University (Washington, DC)
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 11/30/2019
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Dehghanian, Payman, and Wang, Shiyuan. Smart sensor for online situational awareness in power grids. United States: N. p., 2022.
Web.
Dehghanian, Payman, & Wang, Shiyuan. Smart sensor for online situational awareness in power grids. United States.
Dehghanian, Payman, and Wang, Shiyuan. Tue .
"Smart sensor for online situational awareness in power grids". United States. https://www.osti.gov/servlets/purl/1986933.
@article{osti_1986933,
title = {Smart sensor for online situational awareness in power grids},
author = {Dehghanian, Payman and Wang, Shiyuan},
abstractNote = {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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {12}
}
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