Towards practical oscillation detection in wind farms: Comparative study of AI models, novel metrics, and edge implementations
- DOI
- 10.1049/enc2.70043
- Published
- 2026-06
- Container
- Energy Conversion and Economics
- Publisher
- Institution of Engineering and Technology (IET)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1049/enc2.70043,
title = {Towards practical oscillation detection in wind farms: Comparative study of AI models, novel metrics, and edge implementations},
author = {Shyam Yathirajam and Arash Peighambari and Valeria Romero and Christopher Rubin and Nikil Balaji and Hamed Nademi and Sreedevi Gutta and Justin Morris and Ali Ahmadinia},
year = {2026},
journal = {Energy Conversion and Economics},
doi = {10.1049/enc2.70043},
url = {https://doi.org/10.1049/enc2.70043}
}RIS
TY - JOUR TI - Towards practical oscillation detection in wind farms: Comparative study of AI models, novel metrics, and edge implementations AU - Shyam Yathirajam AU - Arash Peighambari AU - Valeria Romero AU - Christopher Rubin AU - Nikil Balaji AU - Hamed Nademi AU - Sreedevi Gutta AU - Justin Morris AU - Ali Ahmadinia PY - 2026 JO - Energy Conversion and Economics DO - 10.1049/enc2.70043 UR - https://doi.org/10.1049/enc2.70043 ER -
APA
Yathirajam, S., Peighambari, A., Romero, V., Rubin, C., Balaji, N., Nademi, H., Gutta, S., Morris, J., & Ahmadinia, A. (2026). Towards practical oscillation detection in wind farms: Comparative study of AI models, novel metrics, and edge implementations. Energy Conversion and Economics. https://doi.org/10.1049/enc2.70043
Source records
- crossref · retrieved 2026-09-24T17:14:18.438Z