Correlation Feature Selection and Mutual Information Theory Based Quantitative Research on Meteorological Impact Factors of Module Temperature for Solar Photovoltaic Systems

Correlation Feature Selection and Mutual Information Theory Based Quantitative Research on Meteorological Impact Factors of Module Temperature for Solar Photovoltaic Systems

The module temperature is the most important parameter influencing the output power of solar photovoltaic (PV) systems, aside from solar irradiance. In this paper, we focus on the interdisciplinary research that combines the correlation analysis, mutual information (MI) and heat transfer theory, whi...

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Bibliographic Details
Main Authors: Yujing Sun, Fei Wang, Bo Wang, Qifang Chen, N.A. Engerer, Zengqiang Mi
Format: Article
Language:English
Published: MDPI AG 2016-12-01
Series:Energies
Subjects:
photovoltaic (PV) module temperature
meteorological impact factor (MIF)
quantitative influence analysis
correlation-based feature selection (CFS)
mutual information (MI) theory
Online Access:http://www.mdpi.com/1996-1073/10/1/7

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http://www.mdpi.com/1996-1073/10/1/7

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