Licensing Opportunity: Envelope Detector-based Phase Fault Detection for Smart Grid Systems

Location: Tennessee
Posted: Sep 11, 2024
Due: Oct 26, 2024
Agency: ENERGY, DEPARTMENT OF
Type of Government: Federal
Category:
  • A - Research and development
Solicitation No: 2024-09-11-J
Publication URL: To access bid details, please log in.
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Licensing Opportunity: Envelope Detector-based Phase Fault Detection for Smart Grid Systems
Active
Contract Opportunity
Notice ID
2024-09-11-J
Related Notice
Department/Ind. Agency
ENERGY, DEPARTMENT OF
Sub-tier
ENERGY, DEPARTMENT OF
Office
ORNL UT-BATTELLE LLC-DOE CONTRACTOR
General Information
  • Contract Opportunity Type: Special Notice (Original)
  • All Dates/Times are: (UTC-04:00) EASTERN STANDARD TIME, NEW YORK, USA
  • Original Published Date: Sep 11, 2024 10:23 am EDT
  • Original Response Date: Oct 26, 2024 05:00 pm EDT
  • Inactive Policy: Manual
  • Original Inactive Date: Oct 27, 2024
  • Initiative:
Classification
  • Original Set Aside:
  • Product Service Code:
  • NAICS Code:
  • Place of Performance:
    Oak Ridge , TN 37830
    USA
Description

Invention Reference Number: 202405667



Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality. However, conventional fault detection systems are vulnerable and do not work on real-world data. This technology is an envelope-detector-based phase fault detection algorithm that can accurately identify the fault region compared to conventional methods.



Description



This technology is a phase fault detection algorithm for power grids developed by employing an envelope detector method. This method diagnoses faults among phases and defines fault areas in the incoming signal. The designed algorithm consists of three steps: analytical signal conversion, complex magnitude, and fault detection. First an analytical signal is obtained from the incoming power signal to determine the amplitude and phase of the signal. Then a complex magnitude operation is applied to display changes in amplitude. Then it identifies the distortion signal in terms of the type of error and size. The technology not only detects the fault region but also diagnoses whether the detected fault is a ground error or not. This technology works with both simulated substation data containing faults that occurred in the power sensor and real-world data. The technology can be used to train machine learning algorithms, providing good data without excess data that’s not useful.



Benefits




  • Accurately detects fault region compared to conventional methods

  • Can also diagnose if fault is a ground error

  • Detects distortions and anomalies accurately and precisely

  • Can detect problems even with no previous knowledge about data

  • Captures area of interest to provide good data for machine learning

  • Increases prediction accuracy of machine learning algorithm

  • Clips out unnecessary parts of the signal



Applications and Industries




  • Power grid operators

  • Electric utilities



Contact



To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.


Attachments/Links
Contact Information
Contracting Office Address
  • Oak Ridge National Laboratory PO Box 2008
  • Oak Ridge , TN 37831
  • USA
Primary Point of Contact
Secondary Point of Contact


History
  • Sep 11, 2024 10:23 am EDTSpecial Notice (Original)
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