2015
DOI: 10.18777/ieashc-task46-2015-0001
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Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications

Abstract: ForewordThe first version of this handbook was developed in response to a growing need by the solar energy industry for a single document addressing the key aspects of solar resource characterization. The solar energy industry has developed rapidly throughout the last few years, and there have been significant enhancements in the body of knowledge in the areas of solar resource assessment and forecasting. Thus, this second version of the handbook was developed from the need to update and enhance the initial ve… Show more

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Cited by 152 publications
(140 citation statements)
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References 213 publications
(229 reference statements)
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“…Post-processing methods like Model Output Statistics (MOS) are frequently applied to reduce these biases or to refine the output of NWP models, as detailed local weather features are generally not resolved by NWP predictions [3]. In addition, spatial averaging can contribute to reduce forecast errors, particularly in situations with variable clouds, that are difficult to predict ( [4,17]). To our best knowledge, these post-processing techniques have been only tested in a continental context ( [3][4][5]) and it appears interesting to assess in this survey the performances of these techniques in the case of an insular environment.…”
Section: Introductionmentioning
confidence: 99%
“…Post-processing methods like Model Output Statistics (MOS) are frequently applied to reduce these biases or to refine the output of NWP models, as detailed local weather features are generally not resolved by NWP predictions [3]. In addition, spatial averaging can contribute to reduce forecast errors, particularly in situations with variable clouds, that are difficult to predict ( [4,17]). To our best knowledge, these post-processing techniques have been only tested in a continental context ( [3][4][5]) and it appears interesting to assess in this survey the performances of these techniques in the case of an insular environment.…”
Section: Introductionmentioning
confidence: 99%
“…The mean bias difference (MBD), the root mean square difference (RMSD), and mean absolute difference (MAD) in absolute (Wm -2 ) and relative (%) values (rMBD, rRMSD and rMAD) were calculated according to Equations 1 to 6 [3,7,24]. In addition to these, the R 2 correlation coefficient was also calculated using Equation 7 [7,24]. …”
Section: Validation Metricsmentioning
confidence: 99%
“…When no on-site measurements are available, other techniques should be applied, such as empirical models based on meteorological variables like temperature or sunshine duration [3,4] or models based on reanalysis and retrospective weather prediction models [5,6]. Satellite-based models have become a very powerful tool for estimating the solar resource at high and uniform spatial resolution (typically a few kilometres) and temporal resolution (hourly or better) over large geographical areas [3,7]. Satellite-based estimates have been validated in the scientific literature [8][9][10][11][12].…”
Section: Introductionmentioning
confidence: 99%
“…Sunlight is the fuel for all solar energy generation technologies, and knowledge of the quality and future reliability of this fuel is essential to accurate analyses of system performance and the financial viability of a project 1,2 . In particular, a precise knowledge of the incoming Direct Normal solar Irradiance (DNI) is required for an accurate design and operation of Concentrating Solar Thermal Power (CSTP) plants 3,4 .…”
Section: Introductionmentioning
confidence: 99%