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Wind energy forecasting with neural networks: a literature review

Author
Manero, J.; Bejar, J.; Cortes, U.
Type of activity
Journal article
Journal
Computación y sistemas
Date of publication
2018
Volume
22
Number
4
First page
1085
Last page
1098
DOI
10.13053/CyS-22-4-3081
Repository
http://hdl.handle.net/2117/129113 Open in new window
URL
http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/3081 Open in new window
Abstract
Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecasting based on the statistical properties of the wind time series and in the integration of meteorological information, these methods are being used commercially around the world. But one family of new ...
Citation
Manero, J.; Béjar, J.; Cortés, U. Wind energy forecasting with neural networks: a literature review. "Computación y sistemas", 2018, vol. 22, núm. 4, p. 1085-1098.
Keywords
Deep learning, Literature review, Machine learning, Neural networks, Short-term prediction, Wind power forecast, Wind speed forecast
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group