LSTM-Based Estimation of Harmonic Source Equivalent Parameters in Power Systems

This paper proposes a deep learning-based method to estimate equivalent parameters of harmonic sources, thus improving the reliability of harmonic contribution assessment. Harmonic contribution assessment is a technique for quantitatively estimating how much individual harmonic sources contribute to...

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Autors principals:	Jong-Il Park, Dohan Kim, Chang-Hyun Park
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Access
Matèries:	Deep learning harmonic contribution assessment harmonic equivalent model long short-term memory recursive least square
Accés en línia:	https://ieeexplore.ieee.org/document/11339442/
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