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A review on artificial intelligence (AI) for stability assessment: preprint / Shutang You, [and twelve others].
- Format:
- Book
- Government document
- Author/Creator:
- You, Shutang, author.
- Series:
- Conference paper (National Renewable Energy Laboratory (U.S.)) ; 5D00-77845.
- NREL/CP ; 5D00-77845
- Language:
- English
- Subjects (All):
- Electric power system stability--Simulation methods.
- Electric power system stability.
- Artificial intelligence--United States--Evaluation.
- Artificial intelligence.
- Electric power systems--United States--Reliability.
- Electric power systems.
- Physical Description:
- 1 online resource (6 pages) : color illustrations.
- Other Title:
- Review on artificial intelligence for stability assessment
- Place of Publication:
- Golden, CO : National Renewable Energy Laboratory, 2020.
- Summary:
- Artificial intelligence provides a convenient route for power grid stability assessment. Compared with simulation-based approaches, artificial intelligence can potentially save time on model development and numerical computation in stability assessment. This paper first reviewed existing literature on using artificial intelligence for power grid stability assessment. Then a machine-leaning-based tool is presented and developed to assess power grid transient stability, frequency stability, and small-signal stability. Test results verified the accuracy and effectiveness of the artificial intelligence tool for power grid stability assessment.
- Notes:
- In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).
- "November 2020."
- "NREL/CP-5D00-77845."
- "Presented at the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm), November 11-13, 2020"--Cover.
- Includes bibliographical references (page 6).
- Description based on online resource, PDF version; title from title page (NREL, viewed January 3, 2025).
- OCLC:
- 1407175839
- Publisher Number:
- 0000-0002-0599-7730 orcid
- 0000-0002-5559-0971 orcid
- 1726026 OSTI ID
- Access Restriction:
- Publicly released
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