Monthly mean solar radiation statistics for Australia

Tables of monthly mean solar radiation parameters are computed from detailed cloud cover information. The parameters include direct and global daily total energy inputs to horizontal, inclined and “sun-tracking” surfaces. Comparison with measured global radiation at 12 stations reveals virtually no systematic error in the computation scheme, and an error of 2MJ m⁻² day⁻¹ in the worst case month of any station.     

Some aspects of solar radiation climatology of Iraq

Study of the climatology of global solar radiation is considered very useful for assessing the potential efficiency of systems designed for solar energy utilization. This paper explores some aspects of solar radiation climatology in Iraq. Analysis of the monthly averages global solar radiation and the general atmospheric transparency for the period 1971–1985 for three different climatological zones (Mosul, Baghdad, Nasiriyah) are discussed. The frequency distribution of daily clearness index for each station is determined using histograms of frequencies. The percentage number of days with solar radiation and sunshine duration values below a certain value is analyzed and discussed. The period of successive days having radiation less than 5 MJ/m² · day⁻¹ and 10 MJ/m² · day⁻¹ is examined and presented graphically.     

Study of hourly solar radiation data in Istanbul

This paper presents a study of the solar radiation data measured in Istanbul (41.1°N, 29.0°E) during 1992 and 1993. The monthly and annual average values of total solar radiation and clearness index are analysed. The monthly averages of daily total radiation are 1.23 kW h m⁻² day⁻¹ for January and 6.55 kW h m⁻² day⁻¹ for July. The annual average value of daily total radiation is 3.81 kW h m⁻² day⁻¹. The monthly averages of clearness index for January and July are 0.28 and 0.50, respectively. The annual average value of clearness index is 0.38. In the second part of the study, the seasonal relative frequency of hourly total radiation and clearness index is studied. 46% of the annual data corresponds to a value greater than 300 W m⁻². The annual average frequency of clear hours is 24%. The analysis points to the conclusion that solar radiation will be efficient and useful between April and September for heating purposes. A polynomial relationship is developed between hourly clearness index and hourly fractional sunshine duration. Some statistical tests are used to check this relationship for four different ranges of optical air mass.     

The solar radiation climate of Thailand

Geographical, seasonal, and diurnal variations of global solar radiation in Thailand are surveyed. Seasonal effects are shown by separate studies for eight 1.5 month periods of the year defined by standard solar declination values. Detailed maps are given of the geographical distribution of solar radiation prepared from data on cloudiness at 44 stations, duration of sunshine at 18 stations, and linear regressions relating radiation to sunshine at Chiang Mai and Bangkok. The highest mean values are above 19.5 MJ m⁻² d⁻¹ and are widespread in spring. The lowest values are below 15.0 MJ m⁻² d⁻¹ in restricted localities with heavy rainfall in autumn.Rough estimates of diffuse solar radiation and atmospheric turbidity are made from the radiation-sunshine regression parameters. Diffuse radiation averages 8.4 MJ m⁻² d⁻¹. Turbidity at Chiang Mai is high in spring and low in summer and autumn; at Bangkok it is high throughout the year.The diurnal variation of global solar radiation determined from hourly measurements at Chiang Mai and Bangkok is analysed. The mean midday radiation fluxes range from 0.80 kW m⁻² in spring to 0.60 kW m⁻² in autumn. On the average the radiation received in the afternoon is slightly less than that received in the morning.     

An assessment of the solar radiation climate of the Cyprus environment

The solar radiation climate of Athalassa, Cyprus, is reported upon in detail. The database utilized in this analysis consisted of daily global and diffuse radiation on a horizontal surface, and global radiation on tilted surfaces, together with the calculated daily values of horizontal beam radiation. In addition, the data reported here include maximum and minimum temperature, relative humidity and percentage of possible sunshine. Monthly average hourly global and diffuse radiation for the time interval 5 a.m.–7 p.m. are reported and analyzed. The annual means of the daily global, diffuse and beam solar radiation on a horizontal surface are about 17.26, 5.75 and 12.35 MJ m⁻², respectively. The average monthly fraction of daily horizontal global radiation that is beam radiation varies from 0.61 in February to 0.77 in September. The average monthly clearness index varies from 0.636 in July to 0.491 in December, whereas the ratio of diffuse to global radiation varies from 0.494 in February to 0.257 in July. The solar radiation climate of the Cyprus environs has also been compared to those reported for two neighbouring countries. We conclude, based upon the above analysis, that Athalassa and its environs are characterized on average, by relatively high daily irradiation rates, both global and beam, and a relatively high percentage of clear days.     

Estimation of monthly Angström–Prescott equation coefficients from measured daily data in Toledo, Spain

In this study, daily global radiation for Toledo (39°53′05″N, 4°02′58″W, Spain) were utilized to determine monthly-specific equations for estimating global solar radiation from sunshine hours and to obtain improved fits to monthly Angström–Prescott's coefficients.Models were compared using the root mean square error (RMSE), the mean bias error (MBE) and the t-statistic. According to our results, all the models fitted the data adequately and can be used to estimate the specific monthly global solar radiation.Average RMSE and MBE for comparison between observed and estimated global radiation were 1.260 and −0.002 MJ m⁻² day⁻¹, respectively. The t-statistic was used as the best indicator, this indicator depends on both, and is more effective for determining the model performance. The agreement between the estimated and the measured data were remarkable and the method was recommended for use in Toledo (Spain).     

Global solar radiation in Northeastern Saudi Arabia

This paper presents the actual global solar radiation on a horizontal surface along with the prevailing meteorological conditions encountered during the measurement period from 1 January–31 December, for one complete year, in the Arabian Gulf Coast near the city of Dhahran. High resolution, real time solar radiation and meteorological data were collected, and processed. Hourly, daily, and monthly statistics of solar radiation was made from the one-minute averaged recorded values. The highest measured daily, and monthly mean solar radiation were found to be 351 and 328 W/m⁻², respectively. The highest one-minute averaged solar radiation values up to 1183 W/m⁻² were observed in the summer season, from May–September. The highest hourly solar radiation value was recorded as 1053 W/m⁻² in the middle of June. Beside the global solar radiation measurements, the main observed meteorological parameters were temperature, pressure, wind speed, precipitation, and relative humidity. On the other hand, the estimation of daily and monthly mean global solar radiation was performed based upon two empirical formulas which relate the solar radiation to the sunshine duration, relative humidity, maximum temperature, the latitude of the monitoring location, sunset hour and declination angles. The agreement between the measured and estimated solar radiation values was found to be satisfactory. Nevertheless, the empirical formula under-estimates the solar radiation values during summer, and over-estimates during winter.     

Survey of the incident solar radiation in Brazil by use of meteosat satellite data

Meteosat-2 satellite data in the visible band were used to calculate monthly averages from daily mean incident solar radiation over Brazil, using the IGMK physical model for the period 1985–1986. Satellite estimates are compared with ground data from 22 national stations. The global root mean square error between model and ground results for all data points was 13%, and the mean bias error was 1.23 MJ m⁻². About 68% of the individual errors were below 10% and clustered around 8%. Global radiation estimated by the model ranged from 9.0 to 27 MJ m⁻² with the diffuse to global ratio falling into the 0.2–0.5 interval. Enhanced inverted zonal trends were found for both satellite predictions and the ground station results.     

Techniques for the precise estimation of hourly values of global, diffuse and direct solar radiation

The method usually used to compute solar radiation, when no measured data are available, is the well-known regression technique relating mean daily totals of global and diffuse solar radiation with the mean duration of sunshine. Using this method and taking into account the first order multiple reflections between the ground and the atmosphere, regression parameters were obtained from the monthly mean values of daily totals of global solar radiation and sunshine at a network of 16 stations in India. Daily values of global and diffuse solar radiation were then computed for 121 stations, where sunshine data are available for periods of 6–28 yr, using interpolated values of the regression parameters. Where no sunshine data were available, global and diffuse solar radiation were computed from cloud observations, using the inverse relationship between sunshine and cloudiness. Further, using the empirical relationship between daily totals and the corresponding hourly values of global and diffuse solar radiation, two sets of curves were prepared valid for the whole country, using which mean hourly values of global and diffuse radiation could be deduced from the corresponding daily totals, with a high degree of accuracy. The paper discusses the validity of the techniques used for computing daily and hourly values of global and diffuse solar radiation from sunshine and cloud amounts at an extended network of 145 stations in India and stresses the fact that such techniques are successful, only if accurate data on both radiation and sunshine are available at a widely distributed network of stations for a minimum period from at least 5 to 6 yr, using carefully calibrated and well-maintained instruments of the required quality. Theoretical models have also been used to compute clear sky noon values of global, diffuse and direct solar radiation from the solar constant, allowing for attenuation by atmospheric constituents such as ozone, water vapour, dust and aerosols. Using a simple model, calculations of global and diffuse solar radiation on clear days were made for 145 stations from values of the solar constant and measured values of ozone, water vapour and atmospheric turbidity. A method of extending the technique to overcast skies and partly clouded skies is discussed. The values of the mean annual transmission factor for global solar radiation under cloud-free conditions using the two methods show excellent agreement and establishes the soundness of the regression technique on one hand and the reliability of the theoretical model used for computing clear sky radiation, on the other.     

Computation of solar radiation from observations of cloud cover

Techniques of computation of global and diffuse solar radiation from the daily duration of bright sunshine and cloud cover are well-known. However, since radiation computations from cloud cover data provide rather imprecise results, this method is resorted to only when sunshine data are not available. To obtain a better idea of the inverse relationship between the long-term averages of sunshine duration and total cloud cover, an analysis of the monthly mean values of the fraction of the sky C, covered by clouds of all types and the duration of bright sunshine, n, was carried out. The relationship between C and (1−n/N′), where N′ is the maximum possible hours of sunshine, was found to be non-linear. The shape of the regression line connecting the two parameters also shows that ground observations of cloud cover always tend to be overestimates. The differences between such estimates and cloud cover values derived from sunshine duration tend to become zero when skies are either clear or overcast and are a maximum for cloud cover values in the range 0.4–0.7. A cubic regression equation was derived relating C and (1−n/N′) and using this relationship, it has been possible to compute sunshine duration from cloud cover data to an accuracy of about 4–7 per cent and from the cloud derived sunshine data, to compute monthly mean values of global solar radiation to an accuracy of about 6–10 per cent and diffuse solar radiation within an accuracy of about 10–15 per cent.     

Estimation of monthly mean daily diffuse radiation in China

In this study, several equations are employed to estimate monthly mean daily diffuse solar radiation for eight typical meteorological stations in China. Estimated values are compared with measured values in terms of statistical error tests such as mean percentage error (MPE), mean bias error (MBE), root mean square error (RMSE). All the models fit the data adequately and can be used to estimate monthly mean daily diffuse solar radiation from global solar radiation and sunshine hours. This study finds that the quadratic model performed better than the other models:     

Modeling of solar radiation using remote sensing and artificial neural network in Turkey

Artificial neural networks (ANNs) were used to estimate solar radiation in Turkey (26–45°E, 36–42°N) using geographical and satellite-estimated data. In order to train the Generalized regression neural network (GRNN) geographical and satellite-estimated data for the period from January 2002 to December 2002 from 19 stations spread over Turkey were used in training (ten stations) and testing (nine stations) data. Latitude, longitude, altitude, surface emissivity for ?_4, surface emissivity for ?_5, and land surface temperature are used in the input layer of the network. Solar radiation is the output. Root Mean Square Error (RMSE) and correlation coefficient (R²) between the estimated and measured values for monthly mean daily sum with ANN values have been found as 0.1630 MJ/m² and 95.34% (training stations), 0.3200 MJ/m² and 93.41% (testing stations), respectively. Since these results are good enough it was concluded that the developed GRNN tool can be used to predict the solar radiation in Turkey.     

The relationship between global solar radiation and sunshine duration in Vietnam

Two approaches of the well-known modified Angstrom formula were developed from long term records of measured monthly mean daily global solar radiation and sunshine hour values obtained from 12 meteorological stations across Vietnam. These formulae were then used to estimate solar radiation for stations where only sunshine records were available. Three other commonly used correlations between solar irradiation and sunshine duration were also used and their results compared with those of two developed models. The procedure of measurement in Vietnamese weather stations was also indicated.     

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.     

Parameterization of a simple model to estimate monthly global solar radiation based on meteorological variables, and evaluation of existing solar radiation models for Tabouk, Saudi Arabia

Using 9 years of solar radiation data, we established a simple model to calculate the monthly mean global solar radiation on a horizontal surface in Tabouk (28.38° N, 36.6° E, Saudi Arabia). The model correlates the global solar radiation with five meteorological parameters. These parameters are the perceptible water vapor, air temperature, relative humidity, atmospheric pressure, and the mean monthly daily fraction of possible sunshine hours. The estimated global radiation from the model was compared with the measured values using the mean bias error (MBE), coefficient of correlation (R), root mean square error (RMSE), and mean percentage error (MPE). The t statistics were also applied as another indication of suitability. The model has a high coefficient of correlation (R = 0.99), MBE = −14 × 10⁻⁴ kW h/m², RMSE = 0.10 kW h/m², and MPE = −0.03%. It is believed that the model developed in this work is applicable for estimating, with great accuracy. The monthly mean daily global radiation at any site having similar conditions to those found in Tabouk.Furthermore, 29 regression models available in the literature were used to estimate the global solar radiation data for Tabouk. The selected models were different in terms of the variables they use and in the number of the variables they contained. The models were compared on the basis of the statistical errors considered above. Apart from Abdall’s model, which showed a reasonable estimate (MPE = −2.04%, MBE = −0.22 kW h/m², and RMSE = 0.59 kW h/m²), all the models under or overestimate the measured solar radiation values. Comparisons between these models and the produced model, from this study, were also considered. According to the statistical results, the model of Abdall showed the prediction closest to those estimated using the developed model.     

Predicting total solar irradiation values using artificial neural networks

This study explores the possibility of developing an artificial neural networks model that could be used to predict monthly average daily total solar irradiation on a horizontal surface for locations in Uganda based on geographical and meteorological data: latitude, longitude, altitude, sunshine duration, relative humidity and maximum temperature. Results have shown good agreement between the predicted and measured values of total solar irradiation. A correlation coefficient of 0.997 was obtained with mean bias error of 0.018 MJ/m² and root mean square error of 0.131 MJ/m². Overall, the artificial neural networks model predicted with an accuracy of 0.1% of the mean absolute percentage error.     

Calculation of monthly mean solar radiation for horizontal and inclined surfaces

The use of daily rather than hourly time intervals in the calculation of the monthly mean values of solar radiation for both horizontal and inclined surfaces has for long been a desirable objective due to a reduction in the required computational effort and more general availability of daily data. This paper presents a method for such calculations, with bright sunshine hours and surface albedo being the only required input data. The incorporation of the effects of multiple reflection between the ground and atmosphere results in relationships used to calculate the diffuse and total solar radiation for a horizontal surface which are largely independent of season and location.The present paper shows that, despite the use of a daily time interval, the solar radiation incident on both horizontal and south-facing surfaces may be calculated with an accuracy generlly associated with instrumental measurements. This result is achieved without the necessity of arbitrarily varying the empirical coefficients to account for variations in climatological conditions at the stations being studied.     

Compilation and evaluation of solar and wind energy resources in Sudan

A number of years worth of data concerning the solar radiation on a horizontal surface, sunshine duration and wind speed in Sudan have been compiled, evaluated and presented in this article.Measurements of global solar radiation on a horizontal surface at 16 stations for several years are compared with predictions made by several independent methods. In the first method the Angstrom formula was used to correlate relative global solar irradiance to the corresponding relative duration of bright sunshine.Regression coefficients are obtained and used for prediction of global solar irradiance. The predicted values were consistent with measured values (± 8.01% variation).In the second method, by Barbaro et al. [Solar Energy, 1978, 20, 431] sunshine duration and minimum air mass were used to drive an empirical correlation for the global radiation. The predicted values compared well with measured values (± 12% variation).The diffuse solar irradiance is estimated. The results of two formulas have close agreement. A radiation map of Sudan was prepared from the estimated radiation values. The annual daily mean global radiation ranges from 3.05 to 7.62 kW h m⁻² per day.Routine wind data from 70 stations were analyzed. Monthly averaged wind speed and average powers were determined for each station. The derived annual average speeds range from 1.53 to 5.07 m s⁻¹. Maximum extractable average wind powers were found to vary between 1.35 and 49.5 W m⁻². A wind map of Sudan was also prepared.Sudan possessed a relatively high abundance of sunshine and moderate wind speed. It is concluded that Sudan is blessed with abundant solar and wind energy.     

Assessment of solar and wind energy resources in Ethiopia. I. Solar energy

This paper describes how data from a variety of sources are merged to present new countrywide maps of the solar energy distribution over Ethiopia. The spatial coverage of stations with radiation data was found to be unsatisfactory for the purpose of a countrywide solar energy assessment exercise. Therefore, radiation had to be predicted from sunshine hours by employing empirical models. Using data from seven stations in Ethiopia, linear and quadratic correlation relationships between monthly mean daily solar radiation and sunshine hours per day have been developed. These regional models show a distinct improvement over previously employed countrywide models. To produce a national solar-energy distribution profile, a spatial extension of the radiation/sunshine relationships had to be carried out. To do this, the intercepts (a) and slopes (b) of each of the seven linear regression equations and another six from previous studies, completed in neighbouring Sudan, Kenya and Yemen, were used to interpolate the corresponding values to areas between them. Subsequent to these procedures, 142 stations providing only sunshine data were assigned their “appropriate” a and b values to estimate the amount of solar radiation received, which was then used to produce annual and monthly solar radiation distribution maps for Ethiopia. The results show that in all regions solar energy is an abundant resource.     

Use of artificial neural networks for mapping of solar potential in Turkey

Turkey has sufficient solar radiation intensities and radiation durations for solar thermal applications since Turkey lies in a sunny belt, between 36° and 42° N latitudes. The yearly average solar-radiation is 3.6 kWh/m²day, and the total yearly radiation period is ∼2610 h. The main focus of this study is to determine the solar-energy potential in Turkey using artificial neural-networks (ANNs). Scaled conjugate gradient (SCG), Pola-Ribiere conjugate gradient (CGP), and Levenberg-Marquardt (LM) learning algorithms and a logistic sigmoid transfer function were used in the network. In order to train the neural network, meteorological data for the last 3 years (2000–2002) from 17 stations (namely cities) spread over Turkey were used as training (11 stations) and testing (6 stations) data. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration, and mean temperature) are used as inputs to the network. Solar radiation is in the output layer. The maximum mean absolute percentage error was found to be less than 6.7% and R² values to be about 99.8937% for the testing stations. However, the respective values were found to be 2.41 and 99.99658% for the training stations. The trained and tested ANN models show greater accuracies for evaluating solar resource posibilities in regions where a network of monitoring stations has not been established in Turkey. The predicted solar-potential values from the ANN were given in the form of monthly maps. These maps are of prime importance for different working disciplines, like those of scientists, architects, meteorologists, and solar engineers in Turkey. The predictions from ANN models could enable scientists to locate and design solar-energy systems in Turkey and determine the appropriate solar technology.