Analysis of daily solar power prediction with data-driven approaches

• Published in: Applied energy Vol. 126; pp. 29 - 37
• Main Authors: Long, Huan, Zhang, Zijun, Su, Yan
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.08.2014; Elsevier
• Subjects: Applied sciences; Artificial Neural Network (ANN); Data mining; Energy; Exact sciences and technology; meteorological parameters; neural networks; prediction; regression analysis; solar energy; Solar power prediction; Support Vector Machine (SVM); support vector machines; Time-series model; Solar power prediction; Data mining; Time-series model; Support Vector Machine (SVM); Artificial Neural Network (ANN); Solar energy; Time series; Models; Electric power production; Neural network; Modeling

•We develop daily solar power prediction models with data-driven approaches.•We introduce a parameter selection procedure for reducing dimensions of prediction models.•We report a comparative analysis of data mining algorithms in daily solar power prediction.•Data mining algorithms can perform bette...