Estimation and prediction of global solar radiation over Greece

A regression analysis of the relative monthly values of global solar radiation ( ) the corresponding values of sunshine (n/N), for the period 1961-75, was performed to determine the constants a and b of the Ångström formula, for Athens. The constants a and b were also determined by a graphical relationship between the average annual relative sunshine (n/N) and these constants, for the same station. The latter method was then used to determine the constants a and b for 33 other stations widely distributed throughout Greece, after making a relative correction to these constants. In this way, monthly and annual values of global solar radiation were estimated for 34 stations over Greece from sunshine measurements. The geographical distribution of the annual totals of global solar radiation over Greece was mapped and some types and sub-types were identified.Further, a stepwise multiple regression analysis of the annual total amounts of global solar radiation and the three factors (latitude, longitude and altitude) was carried out; the validity of the assumption of the linear relationship between the annual totals of global solar radiation and the three factors was examined.     

Solar radiation and sunshine hour maps in Castilla and León region (Spain)

From global solar radiation and sunshine hour data of Castilla and León region (Spain), six different Angstrom-type correlations have been performed using the least square technique and in each of them the parameters a and b have been calculated. In two of these correlations we have taken into account the optic effects of atmosphere and not burning the sunshine recorder chart. The results have been compared using statistical tests based on MBE, RMSE and CC and from this calculation we have obtained the best correlation for Castilla and León locations. Finally from experimental and calculated data the monthly mean solar global radiation and sunshine isoline maps have been plotted for each month of the year and for the year as a whole.     

Assessment of solar and wind energy resources in Ethiopia. II. Wind energy

Using wind data from 21 meteorological stations with hourly or 3-hourly readings and 60 stations with monthly means, together with data from previous studies of neighbouring countries, a series of analyses were undertaken to illustrate the general availability of wind energy across Ethiopia. In order to calculate the wind energy density, firstly these 21 stations, along with 12 stations from neighbouring countries with hourly readings, were used to calculate the Weibull parameters, c and k. The Weibull distribution is shown to be a good approximation for the observed values in a majority of cases. Isopleths of the k values were then plotted, and from this the remaining 60 stations with monthly readings were then assigned k values. The wind energy density for each station was then calculated. Although the quantity of wind data is somewhat lacking, the results show that there is a potential for wind energy utilisation in some regions of Ethiopia.     

ESTIMATION OF SOLAR RADIATION ENERGY OF ETHIOPIA FROM SUNSHINE DATA

Measurements of global solar radiation on a horizontal surface, for nine meteorological stations in Ethiopia, are compared with their corresponding values computed based on Ångström relations, Regression coefficients are obtained and correlation equations are determined to predict the global solar radiation. The result shows that Ångström relations are valid for Ethiopian locations, and the correlation equations can be used to predict the monthly mean daily global solar radiation in the locations considered in this study.

This study also proves that the results made by ENEC et al, using the generalised Frere's coefficients, is unsatisfactory for the prediction of monthly mean daily global solar radiation. On the other hand, the work of Dogniaux and Lemoine, using the regression coefficients a and b as a function of latitude and atmospheric turbidity and grouping large range latitudes to extend the application, can give better estimation. However, for more accurate estimation, several additional meteorological stations have to be evaluated and their regression coefficients have to be determined before grouping in to one relationship to express the variations of a and b under any conditions of equipment and location.     

Estimation of solar radiation over Jordan—predicted tables

As measured solar radiation data for all parts of Jordan are not available, they have to be estimated using correlation relations and models. This paper presents, for the first time, values of solar radiation over Jordan as estimated from these relations. Measurements of global solar irradiance on a horizontal surface and sunshine duration at nine meteorological stations in Jordan are correlated and used for prediction of the regression coefficients of an Angstrom type correlation relation at these stations and others which only have records of sunshine duration. Regional regression coefficients are obtained and used for prediction of global solar irradiance. The agreement with measurements is better than 5% and 1% on monthly and yearly basis respectively. Estimation of diffuse solar irradiance by Page's and also Liu and Jordan's correlations, as well as the direct beam component are also performed and the results are examined and presented. The abundance of solar energy in Jordan is evident from the daily average global solar irradiance which ranges between 5 and 7 kWh/m². A correlation of Angstrom type of the form: H/Ho = 0.448+0.203 S/So is found suitable for Jordan with correlation coefficient r = 0.93.     

A procedure to obtain global radiation maps from sunshine durations at isolated stations in a region with complex orography

In this paper the procedure followed to obtain preliminary maps of monthly average daily global radiation is discussed. The information on which these maps are based is monthly average daily percent sunshine durations at stations covering the considered territory with very irregular density. The possibility of correlations between monthly average percent sunshine and meteorological parameters, other than cloudiness, is examined but found to be absent. A local fit procedure (octant-search), followed by smoothing, is used to construct percent sunshine maps, over the entire territory, coherent with the values relative to the single stations. Finally we have considered the possibility of important variations in the elevation and the influence of this parameter on the global radiation. Hence, among the various relationships relating monthly average daily global radiation to average percent sunshine duration, we have chosen one in which the daily clear sky global radiation (which depends on elevation above sea level) appears instead of the daily extra-terrestrial radiation. The clear sky global radiation has been calculated with a model deduced from Hottel's transmission model which includes elevation dependence. When more data become available, an analogous procedure could be used to obtain definitive maps, employing more reliable values for parameters relating global radiation to percent sunshine tested with experimental data. This method has been applied to the territory of Ethiopia, in order to obtain preliminary maps of global radiation.     

Uses of sunshine duration to estimate the global solar radiation over eight meteorological stations in Egypt

The climatological Ångstrom regression coefficients have been determined by three methods and used to predict the global solar radiation over eight meteorological stations. Each of the three methods depends on the correlation between two ratios. The first ratio is between the long period of monthly average sunshine duration and the corresponding maximum of daily sunshine duration (day length) N, and the second ratio is between the measured monthly average daily global solar radiation and the corresponding monthly mean daily extraterrestrial solar radiation on the horizontal surface ₀. A comparison between the measured data and the estimated values has been done. The t-statistics is used as a statistical indicator to choose the coefficients of the best method that gives a percentage of error less than 10%.     

Comprehensive study of solar conditions in Mozambique: the effect of trade winds on solar components

A new algorithm to simulate all solar components and optimum slopes, β_opt, based on new models for direct normal beam and diffuse radiation and an analytical model to predict β_opt, developed at the University of Botswana is applied for complete study of solar conditions in Mozambique. The components of solar radiation depend to a large extent on the number of h of sunshine. However, it is obvious that cloud-cover is determined mainly by the prevailing trade winds, which carry moisture and rain clouds. This is of especial concern in coastal areas. In the current work, hourly, I, daily, H and monthly mean, components of solar radiation and the optimum slopes of a north–south aligned collector are simulated and analyzed for 21 synoptic stations in Mozambique. Monthly mean daily direct normal, solar radiation maps are plotted for December and June and discussed. It is found that, to a great extent, isoinsolation curves are determined by the prevailing trade winds, mountain chains and coastal conditions. Plotted maps of annual mean daily direct normal and global solar radiation also show tremendous dependence on the prevailing winds. Several special locations in Mozambique with quite high or very low solar radiation components are pointed out and the reasons explained.     

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.     

Mesoscale mapping of available solar energy at the earth's surface by use of satellites

Ground measurements of solar radiation are too sparse to determine important mesoscale differences that can be of major significance in solar power station location and for other purposes. A method is presented for use of cloud images in the visual spectrum from the SMS/GOES geostationary satellites to determine the hourly distribution of sunshine on the mesoscale. Cloud coverage and density as a function of time of day and season are evaluated through the use of digital data processing techniques. Low density cirrus clouds are less detrimental to solar energy collection than other types; and clouds in the morning and evening are less detrimental than those during midday hours of maximum insolation.Seasonal geographic distributions of cloud cover/sunshine are converted to joules of solar radiation received at the earth's surface through relationships developed from long-term measurements of these two parameters at six widely distributed stations. The technique can be used to generate maps showing the geographic distribution of total solar radiation on the mesoscale which is received at the earth's surface.     

Solar Irradiance Polygon Concept and Application for Jordan

Abstract

Solar global irradiation using the Angstrom linear model is widely discussed in the literature. Most of these studies discuss the linear relationship between sunshine duration and global solar irradiation, which is a rigged concept and cannot provide information about the annual variations. This study presents the variation of global solar irradiation through solar irradiation polygon (SIP), which reflects the monthly and seasonal variation of solar irradiation throughout the year. The variation of solar radiation is referred to the state of the atmosphere in the lower layer that is affected by the synoptic weather situation. The model parameters a_s and b_s are calculated month to month throughout the year for seven stations in Jordan. On the other hand, the classical model parameters are calculated for the whole year for the same stations.     

Correlating beam radiation with sunshine duration

For seven locations in north and central India, monthly averaged data of daily beam irradiation on a horizontal surface, I, have been correlated with bright sunshine duration, s, using the relation (I/I₀) = b₀(s/S′) where I₀ is the monthly mean value of extraterrestrial irradiation over a day, S′ is the corresponding duration over which Campbell-Stokes type sunshine recorders remain sensitive. It is found that b₀ is a constant that is period and region dependent. Monthly estimates of beam radiation using the relation above show that for the seven stations rms errors are within 3–6%. Tests made for other stations in India also gave good estimates. For the computation of I, global radiation is not required unlike most estimation techniques and therefore the method should find a wide application.It may be observed that b₀ values turn out to be roughly equal to exp(-md T ) where m is the relative airmass, d is the Raleigh optical thickness and T is the Linke turbidity factor.     

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.     

Ranking the overall performance of eight sunshine-based global solar radiation models with a nonparametric statistical procedure

By using a nonparametric statistical procedure, the ranking of the overall performance of eight sunshine-based global radiation models is conducted in this paper with measured data of global solar radiation and bright sunshine hours at seven meteorological stations in Yunnan Province, China. It is found that, in this region, the Page model performs best, followed by the monthly independent Rietveld model, monthly specific Dogniaux–Lemoine model, monthly specific Rietveld model, Bahel et al. model, monthly independent Dogniaux–Lemoine model, Glover–McCulloch model and the Gopinathan model.     

Effect of sunshine and solar declination on the computation of monthly mean daily diffuse solar radiation

Several years of measured data for 17 European locations have been used to develop models for estimating monthly mean daily values of diffuse radiation (Hd) from combinations of the following: clearness index, sunshine fraction, and solar declination. Two models giving the highest correlation coefficients and the lowest standard errors of estimation are tested with data for 10 European locations not used in their development. From consideration of the MBE and RMSE values, a model which estimates Hd values from clearness index, relative sunshine duration and solar declination is found to be the most accurate. Comparison with Hd values predicted with the European Community solar radiation model (ECM) confirms this conclusion.     

Estimating monthly mean valuesof daily total solar radiation for Australia

Monthly mean values of daily total solar radiation were obtained for the widest possible network acrossAustralia. Bureau of Meteorology sources yielded 11 stations with long term records of both measured daily total solar radiation and sunshine hour values. Monthly modified Angstrom equations were developed from these data and used to estimate radiation values for a further 90 stations in the Bureau of Meteorology network that had sunshine hour data. Measured daily total solar radiation data were obtained from a variety of sources mostly outside the Bureau of Meteorology network for an additional 33 stations. Finally, estimates of solar radiation from detailed cloud cover data were used for a further 12 stations, selected because they filled in significant gaps in coverage. These various sources yielded a total of 146 sets of monthly mean values of daily total solar radiation. For each month optimal surfaces, which were functions of position only, were fitted to this network of values using Laplacian smoothing splines with generalized cross validation. Residuals from the fitted surfaces at the data points were acceptably low. Fitted surfaces which included, in addition to position variables, a cloudiness index based on a transform of mean monthly precipitation further reduced these residuals. The latter fitted surfaces permit estimation of monthly mean values of total daily solar radiation at any point on the continent with a root mean square predictive error of no more than 1.25 MJ m⁻² day⁻¹ (5.2 per cent of the network mean) in summer and 0.74 MJ m⁻² day⁻¹ (5.5 per cent of the network mean) in winter.     

Assessment of diffuse solar energy under general sky condition using artificial neural network

In this paper, artificial neural network (ANN) models are developed for estimating monthly mean hourly and daily diffuse solar radiation. Solar radiation data from 10 Indian stations, having different climatic conditions, all over India have been used for training and testing the ANN model. The coefficient of determination (R²) for all the stations are higher than 0.85, indicating strong correlation between diffuse solar radiation and selected input parameters. The feedforward back-propagation algorithm is used in this analysis. Results of ANN models have been compared with the measured data on the basis of percentage root-mean-square error (RMSE) and mean bias error (MBE). It is found that maximum value of RMSE in ANN model is 8.8% (Vishakhapatnam, September) in the prediction of hourly diffuse solar radiation. However, for other stations same error is less than 5.1%. The computation of monthly mean daily diffuse solar radiation is also carried out and the results so obtained have been compared with those of other empirical models. The ANN model shows the maximum RMSE of 4.5% for daily diffuse radiation, while for other empirical models the same error is 37.4%. This shows that ANN model is more accurate and versatile as compared to other models to predict hourly and daily diffuse solar radiation.     

Modelling of solar energy potential in Nigeria using an artificial neural network model

In this study, an artificial neural network (ANN) based model for prediction of solar energy potential in Nigeria (lat. 4–14°N, log. 2–15°E) was developed. Standard multilayered, feed-forward, back-propagation neural networks with different architecture were designed using neural toolbox for MATLAB. Geographical and meteorological data of 195 cities in Nigeria for period of 10 years (1983–1993) from the NASA geo-satellite database were used for the training and testing the network. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine duration, mean temperature, and relative humidity) were used as inputs to the network, while the solar radiation intensity was used as the output of the network. The results show that the correlation coefficients between the ANN predictions and actual mean monthly global solar radiation intensities for training and testing datasets were higher than 90%, thus suggesting a high reliability of the model for evaluation of solar radiation in locations where solar radiation data are not available. The predicted solar radiation values from the model were given in form of monthly maps. The monthly mean solar radiation potential in northern and southern regions ranged from 7.01–5.62 to 5.43–3.54 kW h/m² day, respectively. A graphical user interface (GUI) was developed for the application of the model. The model can be used easily for estimation of solar radiation for preliminary design of solar applications.     

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.     

Technical note On the development of spatialtemporal solar radiation maps: a Brazilian case study

This work summarizes recently published information on the solar resource of Brazil. We describe the spatial distribution of solar radiation and its relationship with climatic and geographical conditions. In order to harmonize the information in terms of type of instruments, time recording period and data processing methods, a careful selection of records from the data base was made. Density of recording stations is reasonable in the south, southeast and northeast regions of the country, while in the west center and north regions the density of stations is rather poor. The procedure to elaborate the maps of daily solar radiation, monthly and annual average is described. Consideration of the measuring period of the monthly averages, used to elaborate the contour maps, shows that they meet the requirement that 90% of averages are inside the strip of ±7.5%, centralized on the average of very long period measurements. We present one map with the localization of the recording stations and one annual and 12 monthly contour maps, describing daily solar radiation levels over the whole territory. Spacing among the contour lines is (±2 MJm² day). Annual average of solar radiation lies within the interval of ((18±2) MJm² day), except in the northeast region where values higher than (20 MJm² day) are found. Two regions with levels of (16 MJm² day) are also observed. The highest monthly average values (24 MJm² day) are observed in the state of Rio Grande do Sul, southern end of the country, in the summer season (December and January). The lowest values in the country (8 MJm² day) are observed in June and July (winter in the southern hemisphere), on the extreme south coastline of the same state, Rio Grande do Sul, below 32° south latitude.