| Article ID | Journal | Published Year | Pages | File Type | 
|---|---|---|---|---|
| 1549540 | Solar Energy | 2016 | 11 Pages | 
Abstract
												In this study, a statistical characterization of annual solar irradiation series is presented which can be used as input in risk assessment for securing competitive financing for solar power projects. To perform this task, an analysis of annual Direct Normal solar Irradiation (DNI) and Global Horizontal solar Irradiation (GHI) probability density functions has been carried out, showing that annual DNI and GHI distributions are described by Weibull and normal functions, respectively. Normal fitting of annual GHI distributions yields uncertainties in mean parameter below 1%, and uncertainties in standard deviation parameter of â¼12%. Weibull fitting of annual DNI distributions yields uncertainties in scale parameter of â¼1%, and uncertainties in shape parameter of â¼15%. For each location analyzed in this study, the estimated regression coefficients (and their uncertainties) of annual solar irradiation distributions fitting are used to obtain percentile values and their respective associated uncertainties. The greatest uncertainties are associated with the lower percentiles, being 1st percentile uncertainty â¼1.6% and â¼4% for GHI and DNI respectively. Finally, according to the results obtained in this work, a minimum of 11 years of GHI and 15 years of DNI are recommended for their statistical characterization.
											Related Topics
												
													Physical Sciences and Engineering
													Energy
													Renewable Energy, Sustainability and the Environment
												
											Authors
												Carlos M. Fernández Peruchena, Lourdes RamÃrez, Manuel A. Silva-Pérez, Vicente Lara, Diego Bermejo, MartÃn Gastón, Sara Moreno-Tejera, Jesús Pulgar, Juan Liria, Sergio MacÃas, RocÃo Gonzalez, Ana Bernardos, Nuria Castillo, Beatriz Bolinaga, 
											