Preliminary survey on site-adaptation techniques for satellite-derived and reanalysis solar radiation datasets

Abstract

At any site, the bankability of a projected solar power plant largely depends on the accuracy and general quality of the solar radiation data generated during the solar resource assessment phase. The term “site adaptation” has recently started to be used in the framework of solar energy projects to refer to the improvement that can be achieved in satellite-derived solar irradiance and model data when short-term local ground measurements are used to correct systematic errors and bias in the original dataset. This contribution presents a preliminary survey of different possible techniques that can improve long-term satellite-derived and model-derived solar radiation data through the use of short-term on-site ground measurements. The possible approaches that are reported here may be applied in different ways, depending on the origin and characteristics of the uncertainties in the modeled data. This work, which is the first step of a forthcoming in-depth assessment of methodologies for site adaptation, has been done within the framework of the International Energy Agency Solar Heating and Cooling Programme Task 46 “Solar Resource Assessment and Forecasting”

Merging Satellite Retrievals and Reanalyses to Produce Global Long-Term and Consistent Surface Incident Solar Radiation Datasets

“…Another commonly used approach is regression [61][62][63]. However, the regression method suffers from the regression dilution effect, which means that the regression slope tends to be biased toward zero, which causes an underestimated scaling factor [64].…”

“…Previous studies [33,62] have developed bias correction methods for R s , which are primarily dependent on the cloudiness to clear-sky ratio. Zhao et al [68] provides a bias correction method using the error ratio.…”

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

“…The former methods are mainly used for intra-hour forecasting, while the latter features forecast horizons of tens of minutes to up to 6 h [18][19][20][21][22][23][24].…”

Evaluation of Himawari-8 surface downwelling solar radiation by ground-based measurements

“…Many additional factors can introduce a bias in the results of a validation exercise and make satellite-based estimates more uncertain (Polo et al, 2016). Among others, it is worth mentioning the important role played by aerosols in reducing the surface solar irradiance; thus this is an important parameter to be accounted in the algorithms, especially in polluted regions or deserts under clear-sky conditions (e.g., Qu et al, 2017).…”

“…It is worth mentioning the negative effect of the complex morphology in mountainous regions which cannot be easily accounted for due to the limited satellite spatial resolution and the local fast-changing weather conditions (Dürr et al, 2010;Urraca et al, 2017;Federico et al, 2017). Further, the negative impact of the high solar zenith angle (SZA) and satellite-viewing zenith angle on the quality of the estimates must be also mentioned: the former can cause low clouds to be overshadowed by higher clouds while the latter leads to parallax effect in the clouds position (Polo et al, 2016;Qu et al, 2017). Finally, uncertainties in the surface albedo, especially over bright surfaces (e.g., snow or desert), can make cloud identification hard (e.g., Tanskanen et al, 2007).…”