Enhancing Wind Turbine Power Curve Monitoring with eXplainable Artificial Intelligence Techniques
Author:
Affiliation:
1. University of Perugia,Department of Engineering,Perugia,Italy
2. University of Sannio,Department of Engineering,Benevento,Italy
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10198869/10198877/10199016.pdf?arnumber=10199016
Reference27 articles.
1. Comparison of modeling methods for wind power prediction: a critical study
2. Yaw-adjusted wind power curve modeling: A local regression approach;nasery;Renewable Energy,2022
3. Wind Power in Power Systems
4. Data-driven multivariate power curve modeling of offshore wind turbines
5. Wind Turbine Power Curve Modelling using Gaussian Mixture Copula, ANN Regressive and BANN
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1. Wind Power Applications of eXplainable Artificial Intelligence Techniques;2023 AEIT International Annual Conference (AEIT);2023-10-05
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