A model for calculating hourly global solar radiation from satellite data in the tropics

A model for calculating global solar radiation from geostationary satellite data is presented. The model is designed to calculate the monthly average hourly global radiation in the tropics with high aerosol load. This model represents a physical relation between the earth-atmospheric albedo derived from GMS5 satellite data and the absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation by water vapour which is important for the tropics, was calculated from ambient temperature and relative humidity. The relationship between the visibility and solar radiation depletion due to aerosols was developed for a high aerosol load environment. This relationship was used to calculate solar radiation depletion by aerosols in the model. The total column ozone from TOMS/EP satellite was employed for the determination of solar radiation absorbed by ozone. Solar radiation from four pyranometer stations was used to formulate the relationship between the satellite band earth-atmospheric albedo and broadband earth-atmospheric albedo required by the model. To test its performance, the model was used to compute the monthly average hourly global radiation at 25 solar radiation monitoring stations in tropical areas in Thailand. It was found that the values of monthly average of hourly global radiations calculated from the model were in good agreement with those obtained from the measurements, with the root mean square difference of 10%. After the validation the model was employed to generate hourly solar radiation maps of Thailand. These maps reveal the diurnal and season variation of solar radiation over the country.     

A method for estimating direct normal solar irradiation from satellite data for a tropical environment

In order to investigate a potential use of concentrating solar power technologies and select an optimum site for these technologies, it is necessary to obtain information on the geographical distribution of direct normal solar irradiation over an area of interest. In this work, we have developed a method for estimating direct normal irradiation from satellite data for a tropical environment. The method starts with the estimation of global irradiation on a horizontal surface from MTSAT-1R satellite data and other ground-based ancillary data. Then a satellite-based diffuse fraction model was developed and used to estimate the diffuse component of the satellite-derived global irradiation. Based on this estimated global and diffuse irradiation and the solar radiation incident angle, the direct normal irradiation was finally calculated. To evaluate its performance, the method was used to estimate the monthly average hourly direct normal irradiation at seven pyrheliometer stations in Thailand. It was found that values of monthly average hourly direct normal irradiation from the measurements and those estimated from the proposed method are in reasonable agreement, with a root mean square difference of 16% and a mean bias of −1.6%, with respect to mean measured values. After the validation, this method was used to estimate the monthly average hourly direct normal irradiation over Thailand by using MTSAT-1R satellite data for the period from June 2005 to December 2008. Results from the calculation were displayed as hourly and yearly irradiation maps. These maps reveal that the direct normal irradiation in Thailand was strongly affected by the tropical monsoons and local topography of the country.     

Estimation of solar radiation over Cambodia from long-term satellite data

In this work, monthly average daily global solar irradiation over Cambodia was estimated from a long-term satellite data. A 14-year period (1995–2008) of visible channel data from GMS5, GOES9 and MTSAT-1R satellites were used to provide earth-atmospheric reflectivity. A satellite-based solar radiation model developed for a tropical environment was used to estimate surface solar radiation. The model relates the satellite-derived earth-atmospheric reflectivity to absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation due to water vapour was calculated from precipitable water derived from ambient relative humidity and temperature. Ozone data from the TOMS and OMI satellite data were employed to compute the solar radiation absorption by ozone. The depletion of radiation due to aerosols was estimated from the visibility data. Five new solar radiation measuring stations were established at Cambodian cities, namely Siem Reap (13.87°N, 103.85°E), Kompong Thom (12.68°N, 104.88°E), Phnom Penh (11.55°N, 104.83°E), Sihanouke Ville (10.67°N, 103.63°E) and Kampot (10.70°N, 104.28°E). Global solar radiation measured at these stations was used to validate the model. The validation was also carried out by using solar radiation measured at four Thai meteorological stations. These stations are situated near the Cambodian border. Monthly average daily global irradiation from these stations was compared with that calculated from the model. The measured and calculated irradiation is in good agreement, with the root mean square difference of 6.3%, with respect to the mean values. After the validation, the model was used to calculate monthly average daily global solar irradiation over Cambodia. Based on this satellite-derived irradiation, solar radiation maps for Cambodia were generated. These maps show that solar radiation climate of this country is strongly influenced by the monsoons. A solar radiation database was also generated for solar energy applications in Cambodia.     

Generation of operational maps of global solar irradiation on horizontal plan and of direct normal irradiation from Meteosat imagery by using SOLARMET

The physical model SOLARMET, elaborated in ENEA (Italian National Agency for New Technologies, Energy and Environment), provides hourly average global solar irradiance on a horizontal surface (GHi) and hourly average direct normal solar irradiance (DNi) for Italy based on primary satellite images in the visible band.

In the present study, the hourly estimates of surface radiation generated by SOLARMET have been summed up to produce monthly average daily irradiation maps. Hourly and monthly maps were done for the years 1996 and 2002. The parameters of this model were obtained by comparing the Meteosat satellite data with ground data gathered in 2002. Differences, relative to 1996, between SOLARMET estimates and observations obtained over two radiation networks of Italian ground sites are presented: the Meteorological Service of the Italian Air Force and National Agro-Meteorological Network; In total 51 ground stations. The comparison between SOLARMET and the previous Italian method carried out in ENEA shows an improvement due to SOLARMET. Such comparison between the values derived using SOLARMET and previous ENEA methodologies and with data from ground-based stations was possible only for monthly averages of daily global radiation due to an almost total lack of direct radiation ground data in Italy.

The operational monthly solar radiation maps, showing solar energy potentials, permit the selection of construction sites to solar energy project developers. In Italy, these data are necessary for installing solar thermal concentration power plants in support of the R&S program recently funded to demonstrate the possibility of these technologies.     

A technique for mapping global illuminance from satellite data

A technique for mapping global illuminance from satellite data was developed. A five-year (1998–2002) climatology of global solar illuminance obtained from this technique is presented for Thailand using hourly GMS-5 satellite data. The technique is based on a radiation budget model which traces solar radiation as it is scattered, absorbed and reflected back to space. The model produces an earth-atmospheric albedo in the satellite spectral window as well as global illuminance at the earth’s surface. The model is tuned using surface illuminance measurements at four stations in Thailand: Chiang Mai (18.78°N, 98.98°E), Ubon Ratchatani (15.25°N, 104.87°E), Songkhla (7.20°N, 100.60 °E) and Nakhon Pathom (13.82°N, 100.04°E). In the mapping process, a satellite earth-atmospheric albedo at any locations yields a cloud-atmospheric albedo in the satellite band, which is then transformed into a cloud-atmospheric albedo in the photopic band. Having obtained the photopic cloud-atmospheric albedo, the model calculates surface illuminance. The model gives a root mean square difference of 8.1% and a mean bias difference of −2.6% when tested against an independent data set. Monthly average maps are presented covering Thailand for local times of 10:30, 12:30 and 14:30.     

Satellite-derived solar resource maps for Myanmar

Solar resource maps for use in solar energy applications have been produced for Myanmar. A satellite-based solar radiation model, originally developed for the tropics, was improved and applied for the region. A 13-year period (1998–2010) of imagery data from GMS 5, GOES 9 and MTSAT-1R satellites was used as the main input in the model. The absorption and scattering of solar radiation by various atmospheric constituents was also taken into account. The absorption of solar radiation due to water vapour was estimated from precipitable water database obtained from the National Center for Environmental Protection (NCEP), USA. The total column ozone obtained from TOMS/EP and OMI/AURA satellites were used to calculate solar radiation absorption by ozone. The visibility data observed at meteorological stations in Myanmar and neighbouring countries were employed to estimate solar radiation depletion due to aerosols. In order to validate the model, five pyranometer stations were established in different regions of Myanmar and a two-year period of data from these stations were used for the model validation. Additionally, global solar radiation measured at 10 stations in a neighbouring country was also employed for the validation. It was found that monthly average global radiation obtained from the measurements and that estimated from the model was in good agreement, with a root mean square difference of 9.6% at monthly scale. After the validation, the model was used to estimate monthly average global radiation over Myanmar and the results were presented as solar resource maps. The maps revealed that geographical distribution of solar radiation was strongly influenced by the topography of the country and the tropical monsoons.     

PV-GIS: a web-based solar radiation database for the calculation of PV potential in Europe

Solar radiation is a key factor determining electricity produced by photovoltaic (PV) systems. This paper presents a solar radiation database of Europe developed in the geographical information system, and three interactive web applications providing an access to it. The database includes monthly and yearly average values of the global irradiation on horizontal and inclined surfaces, as well as climatic parameters needed for an assessment of the potential PV electricity generation (Linke atmospheric turbidity, the ratio of diffuse to global irradiation, an optimum inclination angle of modules to maximize energy yield). In the first web application, a user may browse radiation maps and query irradiation incident on a PV module for different inclination angles. The second application simulates daily profiles of irradiance for a chosen month and module inclination and orientation. The third web application estimates electricity generation for a chosen PV configuration. It also calculates optimal inclination and orientation of a PV module for a given location. The database and the applications are accessible at http://re.jrc.cec.ev.int/pvgis/pv/imaps/imaps.htm.     

A model for calculating global illuminance from satellite data

A model for calculating global illuminance on horizontal surfaces from meteorological satellite data was developed. The data used for developing the model are global illuminance measured at four solar monitoring stations situated in different parts of Thailand and 8-bit digital data from visible channel of GMS-5 satellite covering the whole country for the period of 1–2 years. Values of normalized global illuminance defined as a ratio of global illuminance to clear sky global illuminance were calculated. These values were used to correlate with those of cloud index derived from the satellite data. From the correlation, a model relating the normalized global illuminance to cloud index was established. The performance of this model was investigated using an independent illuminance data set. It was found that the global illuminance calculated from the model agreed well with that obtained from the measurement, with a root mean square difference of 5.38 klux or 7.0% of the mean values.     

Solar radiation estimations over India using Meteosat satellite images

India is endowed with good solar energy resource due to its geographic position in the equatorial Sun Belt of the earth, but its atmosphere can have eventual large presence of aerosols with the subsequent negative feedback to the solar radiation available. Therefore, solar resource assessment studies over India are of high interest for potential solar energy applications. In this work daily estimations of global horizontal and direct normal irradiation are presented for six locations in India covering the years from 2000 till 2007. These computations have been performed with IrSOLaV/CIEMAT method for computing solar radiation components from Meteosat images with a spatial resolution of less than 5 × 5 km. A brief assessment exercise of the model output have been made with ground measurements available from the World Radiation Data Centre database, which consists only of daily sums of global horizontal irradiation. The daily global horizontal irradiation estimated by the model has shown a general positive bias with the ground measurements in the range of 5%, being the root mean square deviation around 12%, excepting for Trivandrum location where there are evidences of higher uncertainty in the ground measurements. In addition, the dynamical behavior of daily global irradiation is quite well reproduced by the model as a consequence of adding to the input the daily turbidity values estimated from MODIS Terra satellite information. Estimations of direct normal irradiation are also exposed but no assessment was made due to the lack of ground measurements. The importance and need of accurate daily aerosol data with high spatial resolution for solar radiation estimations is pointed out in this work.     

Atmospheric aerosol influence on the Brazilian solar energy assessment: Experiments with different horizontal visibility bases in radiative transfer model

The radiative transfer model BRASIL-SR is used by Brazilian Institute for Space Research for the assessment of the solar irradiation in Brazil. The model parameterizes the influence of aerosols in the solar radiation transmittance using climate averages of horizontal visibility, which does not represent the actual atmospheric condition in Brazil, especially during dry season. In clear sky conditions, aerosols are a major source of bias in solar radiation models. Their concentration have large spatial and temporal variability particularly in the Brazilian Midwestern region from April until October, due to forest fires, and in Southeastern region due to pollution from megacities. In this study, meteorological data from METAR comprising the years of 2006, 2007 and 2008 were analyzed to evaluate the seasonal variability of the horizontal visibility in Brazil to better represent the influence of aerosols on the model estimations of surface solar irradiation. New horizontal visibility values was generated to each month simulated, to provide input data to the BRASIL-SR model and site specific ground data were used to validate the model estimates. The global, direct beam and diffuse solar irradiation estimates obtained by making use of the new horizontal visibility data presented an overall lower BIAS and RMSE deviations.     

Satellite-derived solar resource maps for Brazil under SWERA project

The SWERA project is an international project financed by GEF/UNEP which aims at providing a consistent and easily accessible database to foster the insertion of renewable energies on the energy matrix of selected pilot countries. In Brazil, the project is now at the stage of formatting information, validating of solar and wind resource assessment models, and ancillary GIS data integration. Solar energy resource maps in Brazil were generated using the satellite radiation model BRASIL-SR and the NREL’s CSR (climatological solar radiation) model. This paper describes the methodology used to produce the solar maps using the BRASIL-SR radiation model and discusses the seasonal and yearly means of daily solar irradiation maps obtained for 1995–2002 period.     

Developing an improved global solar radiation map for Zimbabwe through correlating long-term ground- and satellite-based monthly clearness index values

Reliable knowledge of the spatio-temporal distribution of solar radiation is required for the informed design and deployment planning of solar energy delivery systems. In this paper an improved global solar radiation map for Zimbabwe is developed by merging ground-measured radiation data from a sparsely distributed station network, with less accurate satellite-measured data which have an almost continuous spatial coverage. Monthly clearness index values derived from ground-measured global radiation are correlated with those derived from satellite data to obtain a model for calibrating satellite-measured data at a specified grid interval. Two multiplicative factors are to then used to further correct the generated data; CF_m to cater for the in-exactness of the regression fit and the other, IBCF to cater for the interpolation error. Contour maps of global solar radiation are then constructed using interpolation by the geo-statistical method of ordinary kriging. The accuracy of the maps in predicting observed (ground-measured) values was tested by evaluating error statistics; relative bias error (rBE), relative mean bias error (rMBE) and normalized root mean square error (NRMSE) in a “leave-one-out” cross-validation analysis. Results indicate that the maximum normalized root mean square error was 0.028 (about 3%), a significant improvement when compared to an earlier map, the H–G map with a normalized root mean square error (NRMSE) of 0.097.     

Solar constant values for estimating solar radiation

There are many solar constant values given and adopted by researchers, leading to confusion in estimating solar radiation. In this study, some solar constant values collected from literature for estimating solar radiation with the Ångström-Prescott correlation are tested in China using the measured data between 1971 and 2000. According to the ranking method based on the t-statistic, a strategy to select the best solar constant value for estimating the monthly average daily global solar radiation with the Ångström-Prescott correlation is proposed.     

A comparison of estimated and measured values of solar radiation in Elazi , Turkey

In this study, variation of global solar radiation reaching the Elazi region at hourly and monthly average daily periods was examined measuring daily global solar radiation between April 1994 and March 1995 by a Kipp–Zonen pyranometer. Taking the measured values as reference, the statistical performance of the three equations used in estimating the monthly average global solar radiation was investigated. Secondly, it was shown that ‘bright sunshine hours/daylength’ and its standard derivation could be used to estimate the monthly daily ‘solar radiation/extraterrestrial radiation’ by applying the maximum likelihood quadratic fit method to the data taken from the state Meteorological Office in Elazi between 1983–1994.     

A revised empirical model to estimate solar radiation using automated surface weather observations

The transition from manual to automated weather observations at US National Weather Service Offices has compromised the ability to use these data as a means for estimating global horizontal and direct solar radiation. The creation of long term model-derived solar radiation climatologies continues to rely on the in situ cloud data that these observations provide, since homogeneous and readily available satellite data does not span the transition. An existing semi-physical solar radiation model is revised to allow for the estimation of hourly solar radiation based on these observations. Model evaluation reveals that errors in solar radiation estimates are comparable to other contemporary solar radiation models that estimate global horizontal solar radiation on both daily (10–15% mean absolute error) and hourly (15–19% mean absolute error) timescales. Hourly mean absolute errors are similar for different sky conditions, while daily percent errors are similar between seasons. Model updates also allow for accurate estimates of solar radiation in various climate regimes; regional patterns in model bias are not evident.     

Measurement of solar energy radiation in Abu Dhabi,UAE

This paper presents data on measurement of actual solar radiation in Abu Dhabi (24.43°N, 54.45°E). Global solar radiation and surface temperatures were measured and analyzed for one complete year. High resolution, real-time solar radiation and other meteorological data were collected and processed. Daily and monthly average solar radiation values were calculated from the one-minute average recorded values. The highest daily and monthly mean solar radiation values were 369 and 290 W/m², respectively. The highest one-minute average daily solar radiation was 1041 W/m². Yearly average daily energy input was 18.48 MJ/m²/day. Besides the global solar radiation, the daily and monthly average clearness indexes along with temperature variations are discussed. When possible, global solar energy radiation and some meteorological data are compared with corresponding data in other Arab state capitals. The data collected indicate that Abu Dhabi has a strong potential for solar energy capture.     

An application of the multilayer perceptron: Solar radiation maps in Spain

In this work an application of a methodology to obtain solar radiation maps is presented. This methodology is based on a neural network system [Lippmann, R.P., 1987. An introduction to computing with neural nets. IEEE ASSP Magazine, 4–22] called Multi-Layer Perceptron (MLP) [Haykin, S., 1994. Neural Networks. A Comprehensive Foundation. Macmillan Publishing Company; Hornik, K., Stinchcombe, M., White, H., 1989. Multilayer feedforward networks are universal approximators. Neural Networks, 2(5), 359–366]. To obtain a solar radiation map it is necessary to know the solar radiation of many points spread wide across the zone of the map where it is going to be drawn. For most of the locations all over the world the records of these data (solar radiation in whatever scale, daily or hourly values) are non-existent. Only very few locations have the privilege of having good meteorological stations where records of solar radiation have being registered. But even in those locations with historical records of solar data, the quality of these solar series is not as good as it should be for most purposes. In addition, to draw solar radiation maps the number of points on the maps (real sites) that it is necessary to work with makes this problem difficult to solve. Nevertheless, with the application of the methodology proposed in this paper, this problem has been solved and solar radiation maps have been obtained for a small region of Spain: Jaén province, a southern province of Spain between parallels 38°25′ N and 37°25′ N, and meridians 4°10′ W and 2°10′ W, and for a larger region: Andalucía, the most southern region of Spain situated between parallels 38°40′ N and 36°00′ N, and meridians 7°30′ W and 1°40′ W.     

Statistical analysis of solar measurements in Algeria using beta distributions

A method of smoothing solar data by beta probability distributions is implemented in this paper. In the first step, this method has been used to process daily sunshine duration data recorded at thirty-three meteorological stations in Algeria for eleven year periods or more. In the second step, it has been applied to hourly global solar irradiation flux measured in Algiers during the 1987/89 period. For each location and each month of the year, beta probability density functions fitting the monthly frequency distributions of the daily sunshine duration measurements are obtained. Both the parameters characterising the resulting beta distributions are then mapped, enabling us to build the frequency distributions of sunshine duration for every site in Algeria. In the case of solar radiation for Algiers, the recorded data have been processed following two different ways. The first one consists in sorting the hourly global solar irradiation data into eight typical classes of the daily clearness index. The second one is based on the repartition of these data per month. The results of the first classification show that for each class of daily clearness index, the hourly data under consideration are modelled by only one beta distribution. When using the second classification, linear combinations of two beta distributions are found to fit the monthly frequency distributions of the hourly solar radiation data.     

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.     

Comparison of methods for generating typical meteorological year using meteorological data from a tropical environment

This paper presents the comparison of methods for generating typical meteorological year (TMY) data set using a 10-year period of meteorological data from four stations in a tropical environment of Thailand. These methods are the Sadia National Laboratory method, the Danish method and the Festa and Ratto method. In investigating their performance, these methods were employed to generate TMYs for each station. For all parameters of the TMYs and the stations, statistical test indicates that there is no significant difference between the 10-year average values of these parameters and the corresponding average values from TMY generated from each method. The TMY obtained from each method was also used as input data to simulate two solar water heating systems and two photovoltaic systems with different sizes at the four stations by using the TRNSYS simulation program. Solar fractions and electrical output calculated using TMYs are in good agreement with those computed employing the 10-year period hourly meteorological data. It is concluded that the performance of the three methods has no significant difference for all stations under this investigation. Due to its simplicity, the method of Sandia National Laboratories is recommended for the generation of TMY for this tropical environment. The TMYs developed in this work can be used for solar energy and energy conservation applications at the four locations in Thailand.