Smart baseline models for solar irradiation forecasting
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- 作者：R. Urraca ; ruben.urraca@unirioja.es" class="auth_mail" title="E-mail the corresponding author ; J. Antonanzas ; M. Alia-Martinez ; F.J. Martinez-de-Pison ; F. Antonanzas-Torres
- 关键词：Solar forecasting ; Intra-daily solar irradiance ; Random forests ; Soft computing ; Persistence models
- 刊名：Energy Conversion and Management
- 出版年：2016
- 出版时间：15 January 2016
- 年：2016
- 卷：108
- 期：Complete
- 页码：539-548
- 全文大小：461 K
文摘
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Smart baseline forecasting models fed with easy-to-obtain data.
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Significant improvements over the naive persistence models.
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Fixed models, trained with samples from all periods of the year.
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Moving models, constantly updated based on the features of the test sample.
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Machine learning algorithms and automation of the calibration process using GAs.