Quantifying rooftop photovoltaic solar energy potential: A machine learning approach

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• 作者：Dan Assouline ; ^{dan.assouline@epfl.ch} ; Nahid Mohajeri ; Jean-Louis Scartezzini
• 关键词：Machine learning ; Support vector regression ; Solar photovoltaics ; Large-scale solar potential ; Geographic information systems
• 刊名：Solar Energy
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：141
• 期：Complete
• 页码：278-296
• 全文大小：9636 K
• 卷排序：141

文摘

Rooftop photovoltaic solar energy potential has been quantified in Switzerland. Geographic Information Systems (GIS) tools were used for data processing. Support Vector Regression was used to predict solar and urban characteristics. Annual potential PV production in Switzerland is estimated at 17.86 TW h.