Clear-sky Solar Radiation Model Research Articles

Spectral integration of clear-sky atmospheric transmittance: Review and worldwide performance

Broadband atmospheric transmittance is a key component in many broadband clear-sky solar radiation models, whose performance is inevitably bound to the goodness of their atmospheric transmittance parameterizations. A key element in the development of these parameterizations, that has been traditionally overlooked, is the spectral integration to the broadband range. The related scientific literature reveals that two different spectral integration approaches have been proposed, but they have been vaguely evaluated despite the central role of broadband transmittance. This work discusses such approaches, proposes new ones that mitigate current issues and conducts an unprecedented worldwide evaluation study that analyzes the direct normal irradiance evaluation error that is directly attributable to the choice of spectral integration approach. The study makes use of more than 7 million atmospheric transmittance spectra and a 1-year hourly simulation across a 2-degree spatial grid worldwide. The results show that the independent integration scheme, which is the one virtually used always, results in deviations as high as ±40 W/m2 in dry and clean, and in humid and turbid environmental conditions. Overall, while the error stays within ±20 W/m2 for 90% of the cases worldwide using the independent scheme, it is reduced to only ±1.5 W/m2 using one of the alternative integration schemes here proposed. Hence, as a matter of conclusion, it is recommended that any broadband clear-sky solar irradiance model intended for global applications considers a higher-performance spectral integration scheme for atmospheric transmittance, such as the ones proposed here.

Aerosol transmittance for clear-sky solar irradiance models: Review and validation of an accurate universal parameterization

Accurate modeling of solar radiation under cloudless situations is important to facilitate the development and exploitation of the renewable solar resource worldwide. However, many existing clear-sky solar radiation models perform inconsistently under varying aerosol conditions. This work presents a worldwide review of some of the most widely known clear-sky solar radiation models and shows that most of these inconsistencies are related to deficiencies in the simulation of the extinction by aerosols. As a remedy, a fast yet highly accurate analytical parameterization of the aerosol transmittance is introduced here. A performance evaluation using worldwide ground observations of aerosol Ångström's parameters has shown that, conversely to the existing parameterizations, the new one performs consistently under all possible aerosol conditions with virtually no bias and no dispersion. At seven arid locations, in particular, it is found that, when the new aerosol parameterization is used, the direct normal irradiance (DNI) predictions of the reviewed clear-sky irradiance models are comparable to those made with the high-performance RRTMG physical model. This fact proves that the deficiencies in the simulation of aerosol extinction produce most of the DNI biases of clear-sky solar irradiance models in arid regions. Thus, the performance differences found in such models in previous benchmarking studies can vanish by using a better parameterization of the aerosol transmittance such as the one proposed here.

Relationship between Environmental Covariates and Ceylon Tea Cultivation in Sri Lanka

How the current distribution of tea cultivation is influenced by specific environmental conditions in Sri Lanka is yet to be explored. Therefore, this study aims to assess the differences between tea and non-tea growing areas with respect to climatic and topographic covariates, and to determine the major covariates that control tea distributions. Climatic data of temperature and rainfall were extracted from WorldClim-Global Climate Data; the elevation, slopes, and aspects were obtained from Global Multi-resolution Terrain Elevation Data; and the solar radiation data was computed using a clear-sky solar radiation model. Random points were created on rasterised environmental layers for tea-growing and non-tea growing areas, stratified into low, mid, and high regions, using ArcGIS version 10.4.1 (Environmental Systems Research Institute: ESRI Redlands, CA, USA).Correlations were derived between covariates and tea and non-tea growing areas. According to the logistic regression analysis, there was no significant influence of the south-west, west, and north-west aspect compared to the north aspect when all other covariates were held constant. The odds ratio indicated that an area with a one-unit higher solar radiation was 1.453 times more likely to be a tea growing area. Similarly, a per unit increase in slope increases the likelihood of an area being suitable for tea cultivation by 1.039 times. When the annual mean temperature increased, the suitability of tea cultivation decreased, but an increased rainfall had increased the suitability of an area for tea cultivation. Areas with a north facing slope had the highest suitability for tea cultivation. This research demonstrated that tea growing could be expanded into a variety of locations as long as these variables are either found or managed in order to obtain the critical levels. In addition, it is proposed that the results of this study could be utilised in the assessment of the climate or/and land suitability for tea.

Machine learning regressors for solar radiation estimation from satellite data

In this paper we evaluate the performance of several Machine Learning regression techniques in a problem of global solar radiation estimation from geostationary satellite data. Different types of neural networks, Support Vector Regression and Gaussian Processes have been selected as regression techniques to be evaluated, due to their good performance in similar problems in the past. The study area is located in the surroundings of the radiometric station of Toledo, Spain. In order to train the regression techniques considered, one complete year of hourly global solar radiation data is used as the target of the experiments, and different input variables are considered: a cloud index, a clear-sky solar radiation model and several reflectivity values from Meteosat visible images. To assess the results obtained by the Machine Learning algorithms, we have selected as a reference three different physical-based methods, a model based on the Heliosat-2 method (Heliosat-2), the Copernicus Atmosphere Monitoring Service (CAMS) and the SolarGIS model (Soevaluate the performance of Machine Learning regressors when the physical models are included as input variables, in a class of post-processing of these physical approaches. The results obtained show the capacity of Machine Learning regressors to obtain reliable global solar radiation estimation by using satellite measurements.

Validating nine clear sky radiation models in Australia

There have been many validation studies of clear sky solar radiation models, however, to date, no such analysis has been completed for Australia. Clear sky models are essential for estimating the generation potential of various solar energy technologies, the basic calibration of radiation measuring equipment, quality control of solar radiation datasets, engineering design (e.g. heating and cooling of buildings) and in agricultural and biological sciences (e.g. forestry). All of these areas are of considerable interest to the Australian economy and will benefit from an assessment of clear sky radiation models. With the recent provision of one-minute interval radiation data by the Australian Bureau of Meteorology for 20 sites across Australia, such a study can now be undertaken at a level not previously possible. Using up to ten years of data from each of 14 of these sites, clear sky periods are extracted through an automated detection algorithm. With these clear sky periods identified, nine of the most prominent beam and global clear sky radiation models are assessed using the relative Mean Bias Error, relative Root Mean Square Error and Coefficient of Determination as metrics. Further testing assessed model performance as a function of solar zenith angle and apparent solar time. Results show that for global clear sky simulations, the Solis, Esra and REST2 approaches perform best, while the Iqbal, Esra and REST2 methods are the most proficient clear sky beam models.

Comparison of solar radiation models and their validation under Algerian climate – The case of direct irradiance

The accurate prediction of direct solar irradiance is essential in many solar energy applications, particularly those relying on concentrating solar technologies. The present paper is aimed at a detailed assessment of a large range of clear-sky solar radiation models under Algerian climate to select the more accurate one for estimating the performance of solar power projects where meteorological and radiometric measurement stations are not available. To this end, seventeen models have been reviewed and their performance compared to measured irradiance of Ghardaia (Southern Algeria). The validation methodology presented herein is very helpful for ranking the models. A new statistical accuracy indicator has been originally introduced to find out the most accurate ones.A thorough analysis of selected models has shown that the more complex models, that seem at first sight more sophisticated, are not necessary the most accurate; while simpler models depending on a limited number of parameters are more suitable. In other words, the suitability and accuracy of a model do not necessarily improve with an increase in the number of its parameters. This important finding is in good agreement with the previous published studies. This fact is important to take into account, in the case where measured data are not available, for the selection of the most suitable locations for the installation of the future concentrating solar power plants in Algeria or even in other countries.

A clear sky irradiation assessment using the European Solar Radiation Atlas model and Shuttle Radar Topography Mission database: A case study for Romanian territory

The objectives of this paper are to develop a software application that allows to establish the clear-sky solar radiation on horizontal surface considering the shading effect of complex topography of terrain and to employ it in order to assess the amount of clear-sky irradiation over Romanian territory. In order to achieve the first objective, a clear sky solar radiation model developed in accordance with the latest mathematical equations published in European Solar Radiation Atlas has been adopted and implemented together with a digital elevation model developed based on the Shuttle Radar Topography Mission database. In order to achieve the second objective, based on a digital elevation model of the Romanian territory, the monthly average daily clear-sky irradiation over whole territory has been established. The estimates have been validated using the solar radiation values from other two well known databases, the relative errors shown that the irradiance values have a good accuracy. The software application has been involved in order to build and analyze the maps of monthly average of daily irradiation, in the assumption of the clear-sky conditions and in horizontal surface, over whole Romanian territory.

Accuracy analysis for fifty-four clear-sky solar radiation models using routine hourly global irradiance measurements in Romania

Fifty-four broadband clear-sky models for computation of global solar irradiance on horizontal surfaces are tested by using measured data from Romania (South-Eastern Europe). The input data to the models consist of surface meteorological data, column integrated data and data derived from satellite measurements. The testing procedure is performed in twenty-one steps for two different sites in Romania. The models accuracy is reported for various sets of input data. No model ranked “the best” for all sets of input data. However, some of the models were ranked among the best for most of the testing steps, and thus performed significantly better than others. These “better” models are, on an equal footing, ESRA3, Ineichen, METSTAT and REST2 (version 8.1). The next “better” models are, on an equal footing, Bird, CEM and Paulescu and Schlett. Details about the accuracy of each model are found in the Electronic Supplementary Content for all testing steps.

A CLEAR SKY IRRADIATION ASSESSMENT USING THE ESRA MODEL AND SRTM DATABASE

This paper describes a model and an algorithm used to develop a solar radiation database for Romanian territory. In order to obtain this database, two main steps were performed. In the first part, a clear sky solar radiation model was presented, in accordance with the latest models published in European Solar Radiation Atlas. After this, a digital elevation model has been developed, based on the Shuttle Radar Topography Mission database, which, together with the previously mentioned model, allows the computation of the solar radiation s potential over the Romanian territory. The obtained results have been validated using the solar radiation values from two another well known database. The comparative results show that the irradiance values have a good accuracy and, therefore, it can be used as a practical tool for the estimation of the solar radiation s potential over the analyzed territory.

The Analysis of Measurement and Model of Solar Radiation in Hohhot

The data of four sets of the sun radiation testing system in Hohhot was processed by the method of standard deviation to get the highest relative accuracy as a model with data. By comparing the measuring value with the calculating value of clear-sky solar radiation model established, it is found the model is only fit for the sunny day, moreover the lager percentage of sunshine is, the model is more appropriate. This model can meet the practical needs of general engineering and also can be used in the analysis of building energy efficiency

A topographic geostatistical approach for mapping monthly mean values of daily global solar radiation: A case study in southern Spain

Local topography influences total incoming solar radiation at ground surface in mountainous areas, and so it becomes a key factor for the spatial distribution of plants. However, radiometric stations are often clustered only around farmland or populated areas, usually throughout valleys and flat regions. In this work, we use residual kriging methods to account for cloud- and terrain-related effects, especially when availability of measurements in mountains is scarce. Terrain-related effects have been considered through the terrain elevation and a topographic clear-sky solar radiation model that, additionally, also allow us to consider local clouds effects. Mesoscale-level phenomena were considered through the distance to the coast and the geographical longitude, that partially explain the atmospheric circulation in the studied region. The study has been conducted in the region of Andalusia, in southern Spain, using a target grid support of 1km of grid-spacing and based on a 10-year length experimental dataset of 63 stations. Two different residual kriging approaches were evaluated and compared against ordinary kriging estimates. Overall, all kriging methods showed good skills in predicting the spatial regionalization of the monthly averages of daily solar radiation. The use of the distance to the coast and the geographical longitude enhanced the performance of residual kriging methods. Elevation proved to be important during summer months, while clear-sky solar radiation estimates were helpful especially during winter months. Overall, the RMSE value for ordinary kriging at the validation sites was about 3%. The residual kriging methods were able to outperform ordinary kriging around a 5% in winter and up to a 18% in summer, in relative terms.

Monthly average clear-sky broadband irradiance database for worldwide solar heat gain and building cooling load calculations

This paper establishes the formulation of a new clear-sky solar radiation model appropriate for algorithms calculating cooling loads in buildings. The aim is to replace the ASHRAE clear-sky model of 1967, whose limitations are well known and are reviewed. The new model is derived in two steps. The first step consists of obtaining a reference irradiance dataset from the REST2 model, which uses a high-performance, validated, two-band clear-sky algorithm. REST2 requires detailed inputs about atmospheric conditions such as aerosols, water vapor, ozone, and ground albedo. The development of global atmospheric datasets used as inputs to REST2 is reviewed. For the most part, these datasets are derived from space observations to guarantee universality and accuracy. In the case of aerosols, point-source terrestrial measurements were also used as ground truthing of the satellite data. The second step of the model consists of fits derived from a REST2-based reference irradiance dataset. These fits enable the derivation of compact, but relatively accurate expressions, for beam and diffuse clear-sky irradiance. The fitted expressions require the tabulation of only two pseudo-optical depths for each month of the year. The resulting model, and its tabulated data, are expected to be incorporated in the 2009 edition of the ASHRAE Handbook of Fundamentals.

We-P11:101 The prevalence of metabolic syndrome amongst patients presenting for elective surgery, and its association with post-operative complications

The accurate prediction of direct solar irradiance is essential in many solar energy applications, particularly those relying on concentrating solar technologies. The present paper is aimed at a detailed assessment of a large range of clear-sky solar radiation models under Algerian climate to select the more accurate one for estimating the performance of solar power projects where meteorological and radiometric measurement stations are not available. To this end, seventeen models have been reviewed and their performance compared to measured irradiance of Ghardaia (Southern Algeria). The validation methodology presented herein is very helpful for ranking the models. A new statistical accuracy indicator has been originally introduced to find out the most accurate ones.A thorough analysis of selected models has shown that the more complex models, that seem at first sight more sophisticated, are not necessary the most accurate; while simpler models depending on a limited number of parameters are more suitable. In other words, the suitability and accuracy of a model do not necessarily improve with an increase in the number of its parameters. This important finding is in good agreement with the previous published studies. This fact is important to take into account, in the case where measured data are not available, for the selection of the most suitable locations for the installation of the future concentrating solar power plants in Algeria or even in other countries.

A simple hourly clear-sky solar radiation model based on meteorological parameters

An hourly solar radiation model, based on observed meteorological data, was developed and tested. As a means of comparison, the Watt and Bird models and the Solmet regression models were also tested. Several conclusions were drawn about the parameterization of solar radiation-depleting parameters. It was determined that a reasonable estimate of lower layer aerosol extinction can be determined using humidity, visibility, and mixing height. The parameterization of water vapor absorption obtained by atmospheric rather than laboratory observations was found to give better model results.