Difference between revisions of "Predicting electricity generation capacity in solar and wind power plants based on meteorological data using machine learning algorithms"

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{{StudentProjectTemplate
 
{{StudentProjectTemplate
|Summary=Machine learning and artificial intelligence algorithms will be used to analyze meteorological data in order to predict the electricity generation capacity of solar and wind power plants, and the optimum size of their required batteries. (This project is a collaboration between Halmstad University and Sam Houston State University (USA)).
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|Summary=ML algorithms will be used to analyze meteorological data to predict the electricity generation capacity of solar and wind power plants. This project is a collaboration between Halmstad and Sam Houston University (USA)).
 
|Supervisor=Reza Khoshkangini, Ramin Sahba, Amin Sahba
 
|Supervisor=Reza Khoshkangini, Ramin Sahba, Amin Sahba
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|Level=Flexible
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|Status=Open
 
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Latest revision as of 13:58, 6 October 2021

Title Predicting electricity generation capacity in solar and wind power plants based on meteorological data using machine learning algorithms
Summary ML algorithms will be used to analyze meteorological data to predict the electricity generation capacity of solar and wind power plants. This project is a collaboration between Halmstad and Sam Houston University (USA)).
Keywords
TimeFrame
References
Prerequisites
Author
Supervisor Reza Khoshkangini, Ramin Sahba, Amin Sahba
Level Flexible
Status Open