A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data

Wind farm performance monitoring has traditionally relied on deterministic models, such as power curves or machine learning approaches, which often fail to account for farm-wide behavior and the uncertainty quantification necessary for the reliable detection of underperformance. To overcome these li...

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Bibliografische gegevens

Hoofdauteurs:	Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2025-07-01
Reeks:	Energies
Onderwerpen:	wind farm SCADA possible power kernels uncertainty
Online toegang:	https://www.mdpi.com/1996-1073/18/14/3764
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