Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6764488 | Renewable Energy | 2018 | 26 Pages |
Abstract
We propose in this study that including a prior automatic filtering, by means of Gaussian Processes modelling, improves the network performance significantly, and saves substantial time and resources. The aim of this paper is to present a complete method based on Gaussian Processes data pre-filtering and ANN modeling of wind turbine power curves. Results show that this procedure improves the standard ANN modeling and also improves on the widely used IEC-61400 standard (International Electro technical Commission) and other parametric and non-parametric methods. Overall, there is a significant improvement (25%) in root mean square error of predicted power using our proposed model compared to standard methods currently applied.
Related Topics
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Renewable Energy, Sustainability and the Environment
Authors
Bartolomé Manobel, Frank Sehnke, Juan A. Lazzús, Ignacio Salfate, Martin Felder, Sonia Montecinos,