Validation of five global radiation models with measured daily data in China

Two sunshine based and three air temperature based global radiation models are calibrated using daily data in Jan. 1 1994–Dec. 31 1998 at 48 stations all over China. The Nash–Sutcliffe equation (NSE) is used as the model evaluation criterion. The sunshine based models are suitable for daily global radiation estimation. The averaged NSE value of the Angström model is 0.83, and the maximum value is 0.91. The maximum NSE value of the Bahel model is 0.92 with an averaged value of 0.84. The models that use air temperature as the input variable are not suitable for daily global radiation estimation in China. The averaged NSE values of the three air temperature based models (Bristow–Campbell model, Allen model and Hargreaves model) are not larger than 0.47. A logarithmic relationship between the daily global radiation/daily extra-terrestrial solar radiation (R_G/R_A) and the temperature difference between the maximum and minimum daily air temperature (T_M−T_m) is found in the present study. A new daily global radiation model that is a function of R_A, sunshine hours and T_M−T_m is designed, which gives an averaged NSE value of 0.85 and a maximum value of 0.92.     

Sensitivity analysis of performance of crop growth simulation models to daily solar radiation estimation methods in Iran

Solar radiation is the single most important environmental factor driving canopy photosynthesis and transpiration. This weather characteristic is measured only in a limited number of weather stations. Hence, in many situations it has to be estimated from other weather characteristics such as sunshine duration and temperature using empirical relations. In this study, the Ångstrom and Hargreaves formulas have been used for solar radiation estimation, based on monthly and annual weather data for three weather stations in Esfahan province, Iran. Deviations of estimated solar radiation from measured values (both absolute and relative) varied with month of the year and with estimation method. Estimated and measured radiation values were used in a crop growth simulation model to explore sensitivity of simulated production with respect to radiation estimation method. Maximum deviation for winter barley and silage maize was around 9%.     

Estimation of global solar radiation on horizontal surfaces in Jeddah, Saudi Arabia

The measured data of global solar radiation on a horizontal surface, as well as the number of sunshine hours, mean daily ambient temperature, maximum and minimum ambient temperatures, relative humidity and amount of cloud cover, for Jeddah (latitude 21° 42′37″N, longitude 39° 11′12″E), Saudi Arabia for the period 1996–2006 are analyzed. The data are divided into two sets. The sub-data set 1 (1996–2004) are employed to develop empirical correlations between the monthly average of daily global solar radiation fraction (H/H₀) and various meteorological parameters. The nonlinear Angström type model developed by Sen and the trigonometric function model proposed by Bulut and Büyükalaca are also evaluated. New empirical constants for these two models have been obtained for Jeddah. The sub-data set 2 (2005, 2006) are then used to evaluate the derived correlations. Comparisons between measured and calculated values of H have been performed. It is indicated that, the Sen and Bulut and Büyükalaca models satisfactorily describe the horizontal global solar radiation for Jeddah. All the proposed correlations are found to be able to predict the annual average of daily global solar radiation with excellent accuracy. Therefore, the long term performance of solar energy devices can be estimated.     

Models for obtaining solar radiation from other meteorological data

The application of solar energy requires a knowledge of long-term solar radiation and daylight data. Because of the limited availability of measured data, various formulae have been derived to compute the solar irradiance using other, more commonly available, weather data. In this article two such models are presented, MRM (meteorological radiation model) and CRM (cloud-cover radiation model). MRM requires hourly data for sunshine duration, dry- and wet-bulb temperature; while CRM requires only cloud amount. Both models can generate hour-by-hour data for horizontal global, diffuse, and beam irradiance. A brief comparison of the two models is presented. Results showed that MRM has the advantage over CRM, on account of its consistency with the measured data. Both models are now available via the Internet in the form of electronic spreadsheets.     

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%.     

Equations for estimating global solar radiation in data sparse regions

The knowledge of the amount of solar radiation in an area/region is very essential in the field of Solar Energy Physics. In this work two equations are put forward for estimating global solar radiation from common climate variables in data sparse regions. The first is the Hargreaves equation, R_s=0.16R_aT_d^0.5 where R_a is the extraterrestrial solar radiation and T_d is the temperature difference (maximum minus minimum), while the second is the Angstrom equation, R_s=R_a(0.28+0.39n/N) where n and N are the measured sunshine hours and the maximum daylight duration respectively. The global solar radiation estimated by the two equations for three sites, Owerri (5°28′N, 7°2′E), Umudike (5°29′N, 7°33′E) and Ilorin (8°32′N, 4°46′E), located in different climate zones of in Nigeria, West Africa, are in agreement with those of earlier workers and that from Photovoltaic Geographic Information System (PVGIS) project. The implication of this in solar photovoltaic applications has been stressed.     

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.     

An analysis of thermal and solar zone radiation models using an Angstrom–Prescott equation and artificial neural networks

The correlation between the clearness index and sunshine duration is useful in the estimation of the solar radiation for areas where measured solar radiation data are unavailable. Regression techniques and artificial neural networks were used to investigate the correlations between daily global solar radiation (GSR) and sunshine duration for different climates in China. Measurements made during the 30-year period (1971–2000) from 41 measuring stations covering 9 thermal and 7 solar climate zones and sub-zones across China were gathered and analysed. The performance of the regression and the ANN models in the thermal and solar zones was analysed and compared. The coefficient of determination (R²), Nash–Sutcliffe efficiency coefficient (NSEC), mean bias error (MBE) and root-mean-square error (RMSE) were determined. It was found that the regression models in both the thermal and the solar climate zones showed a strong correlation between the clearness index and sunshine duration (R²=0.79–88). There appeared to be an increasing trend of larger MBE and RMSE from colder climates in the north to warmer climates in the south. In terms of the thermal and solar climate zone models, there was very little to choose between the two models.     

The empirical relationship between global radiation and global ultraviolet (0.290–0.385) μm solar radiation components

Measurements of the monthly average daily global and global ultraviolet solar radiation over a period of three years (1985, 1986, 1987) in Kuwait are reported. Over the three years the computed yearly daily means for the above solar radiation components were 5.592 kW h/m² and 0.260 kW h/m². The effect of atmospheric dust on the measured solar radiation components is investigated. Employing the least-square linear regression analysis an estimated empirical function relating global radiation to ultraviolet radiation was proposed for the past three years' measurements.     

Relationship between the total solar radiation on tilted surfaces and the sunshine hours in Hong Kong

Solar energy technologies can play an important role in meeting the ultimate goal of replacing fossil fuels to generate inexhaustible, clean and safe energy. The availability of more comprehensive solar radiation data is invaluable for the design and evaluation of solar-based conversion systems. In many places of the world, particularly the developing countries, the basic solar radiation data for the surfaces of interests are not readily obtainable. This paper presents an approach to estimate the annual global solar radiation on various inclined planes facing different orientations based on measured sunshine hours. Solar radiation and sunshine hours data recorded in 2004 were used for the model development. The performance of the proposed model was assessed against data measured in 2005. It is shown that the solar radiations estimated by the proposed method are in good agreements with the measured data and the peak difference was found less than 5.2%. The predictive ability and the simplicity nature of the model provide a reliable and convenient alternative for estimating inclined solar radiation.     

Estimating global solar radiation using artificial neural network and air temperature data in a semi-arid environment

Global solar radiation (GSR) data are desirable for many areas of research and applications in various engineering fields. However, GSR is not as readily available as air temperature data. Artificial neural networks (ANNs) are effective tools to model nonlinear systems and require fewer inputs. The objective of this study was to test an artificial neural network (ANN) for estimating the global solar radiation (GSR) as a function of air temperature data in a semi-arid environment. The ANNs (multilayer perceptron type) were trained to estimate GSR as a function of the maximum and minimum air temperature and extraterrestrial radiation. The data used in the network training were obtained from a historical series (1994–2001) of daily climatic data collected in weather station of Ahwaz located in Khuzestan plain in the southwest of Iran. The empirical Hargreaves and Samani equation (HS) is also considered for the comparison. The HS equation calibrated by applying the same data used for neural network training. Two historical series (2002–2003) were utilized to test the network and for comparison between the ANN and calibrated HS method. The study demonstrated that modelling of daily GSR through the use of the ANN technique gave better estimates than the HS equation. RMSE and R² for the comparison between observed and estimated GSR for the tested data using the proposed ANN model are 2.534 MJ m^?2 day^?1 and 0.889 respectively.     

Prediction of monthly mean daily diffuse solar radiation using artificial neural networks and comparison with other empirical models

An artificial neural network (ANN) model for estimating monthly mean daily diffuse solar radiation is presented in this paper. Solar radiation data from 9 stations having different climatic conditions all over China during 1995–2004 are used for training and testing the ANN. Solar radiation data from eight typical cities are used for training the neural networks and data from the remaining one location are used for testing the estimated values. Estimated values are compared with measured values in terms of mean percentage error (MPE), mean bias error (MBE) and root mean square error (RMSE). The results of the ANN model have been compared with other empirical regression models. The solar radiation estimations by ANN are in good agreement with the actual values and are superior to those of other available models. In addition, ANN model is tested to predict the same components for Zhengzhou station over the same period. Results indicate that ANN model predicts the actual values for Zhengzhou with a good accuracy of 94.81%. Data for Zhengzhou are not included as a part of ANN training set. Hence, these results demonstrate the generalization capability of this approach and its ability to produce accurate estimates in China.     

Estimation of solar radiation parameters for Izmir,Turkey

In this study, the solar radiation parameters (global and diffuse solar radiation) are correlated with respect to ambient temperatures in the fifth‐order polynomial form for Izmir in Turkey. Experimental data were measured in the Solar‐Meteorological Station of Solar Energy Institute in Ege University over a 5‐yr period, 1994–1998. The ratios of the total daily diffuse to global radiation intensities for each month range from 0.38 to 0.45 averaged for the same period, with an average value of 0.41. It can be concluded that the present models predict the solar radiation parameters reasonably well with the correlation coefficients over 0.95 for the projections. Copyright © 2002 John Wiley & Sons, Ltd.     

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.     

Review of research on autonomous wind farms and solar parks and their feasibility for commercial loads in hot regions

In the wake of rising cost of oil and fears of its exhaustion coupled with increased pollution, the governments world-wide are deliberating and making huge strides to promote renewable energy sources such as solar–photovoltaic (solar–PV) and wind energy. Integration of diesel systems with hybrid wind–PV systems is pursued widely to reduce dependence on fossil-fuel produced energy and to reduce the release of carbon gases that cause global climate change. Literature indicates that commercial/residential buildings in the Kingdom of Saudi Arabia (KSA) consume an estimated 10–40% of the total electric energy generated. The study reviews research work carried out world-wide on wind farms and solar parks. The work also analyzes wind speed and solar radiation data of East-Coast (Dhahran), KSA, to assess the technical and economic potential of wind farm and solar PV park (hybrid wind–PV–diesel power systems) to meet the load requirements of a typical commercial building (with annual electrical energy demand of 620,000 kWh). The monthly average wind speeds range from 3.3 to 5.6 m/s. The monthly average daily solar global radiation ranges from 3.61 to 7.96 kWh/m². The hybrid systems simulated consist of different combinations of 100 kW wind machines, PV panels, supplemented by diesel generators. NREL (and HOMER Energy's) HOMER software has been used to perform the techno-economic study. The simulation results indicate that for a hybrid system comprising of 100 kW wind capacity (37 m hub-height) and 40 kW of PV capacity together with 175 kW diesel system, the renewable energy fraction (with 0% annual capacity shortage) is 36% (24% wind + 12% PV). The cost of generating energy (COE, $/kWh) from this hybrid wind–PV–diesel system has been found to be 0.154 $/kWh (assuming diesel fuel price of 0.1$/L). The study exhibits that for a given hybrid configuration, the number of operational hours of diesel generators decreases with increase in wind farm and PV capacity. Attention has also been focused on wind/PV penetration, un-met load, excess electricity generation, percentage fuel savings and reduction in carbon emissions (relative to diesel-only situation) of different hybrid systems, cost break-down of wind–PV–diesel systems, COE of different hybrid systems, etc.     

Empirical models for the estimation of global solar radiation with sunshine hours on horizontal surface for Jharkhand (India)

The main objective of this study is to develop a linear regression model for estimating radiation for some selected cities of Jharkhand region. Taking sunshine hours as the prime concern, the three main places which come under this region, namely—Jamshedpur (longitude 86°11′ E, latitude 22°48′ N), Ranchi (longitude 85°20′ E, latitude 23°21′ N) and Bokaro (longitude 86°09′ E, latitude 23°40′ N) a set of regression constants were obtained in order to develop the linear regression model. The new developed models estimated the value of regression constant “a” which is ranging between 0.204 to 0.211 and value of regression constant “b” ranging from 0.489 to 0.514. Results are compared with measured data and some well known models with the help of statistical test for city Ranchi. Finally, the proposed model was preferred for estimation of solar radiation in Ranchi, with smallest statistical errors among all models and close agreement with measured data.     

Climatic influences on solar modelling in China

Correlation between clearness index and sunshine duration is useful to the estimation of the solar radiation for areas where measured solar radiation data are not available. Regression techniques were used to investigate the correlations between daily global solar radiation and sunshine duration for different climates in China. Measurements made during the 30-year period (1971–2000) from 40 measuring stations covering major thermal and solar climatic zones across China have been gathered and analysed. The correlations were developed for each individual station as well as for each of the major climates. It was found that the Angstrom–Prescott equation tended to give a good estimation of global solar radiation based on the corresponding measured sunshine hours. A simple two-parameter linear regression equation was proposed for each of the major thermal and solar climatic zones.     

Luminescent solar concentrator employing rare earth complex with zero self-absorption loss

Luminescent solar concentrator (LSC) employing Eu(TTA)₃(TPPO)₂ (europium tris(2-thenoyl trifluoro acetonate)-di(triphenylphosphine oxide)) was fabricated in our work firstly, and then its current–voltage (I–V) performance under AM1.5G radiation with different radiation area were measured and compared with that of LSC employing dye. As there is no overlap between absorption spectrum and fluorescence spectrum of Eu(TTA)₃(TPPO)₂, it is found that the power conversion efficiency of LSC employing Eu(TTA)₃(TPPO)₂ decreases ten times slower than that of LSC employing dye reported with the increment of radiation area under AM1.5G. To accurately characterize the zero self-absorption loss of LSC employing rare earth complex more, external quantum efficiency (EQE) was also measured and simulated theoretically. When experiment data is compared with theoretical simulation, the measured EQE data at 380 nm is found to well coincide with theoretical result by taking host absorption loss into consideration. And the conclusion could be drawn that rare earth complex obviously shows zero self-absorption loss in use of LSC system and is proposed as a potential candidate for increasing the LSC efficiency.     

Estimation of monthly averaged direct normal solar radiation using elevation angle for any location

Light concentrators used in solar photovoltaic and solar thermal applications, and concentrates light by a factor of 10 or more, use only direct normal solar radiation, I_N. A new method, called elevation angle constant (EAC) method, is developed to determine the resource potential of I_N for different locations. This method is applicable to estimate the I_N at any location in the world. The EAC method is based on empirical relations. The method calculates the elevation angle constant (ε) for a given location and time. It uses readily available daily global and diffuse global radiation data to estimate the I_N. This is different from existing methods which invariably uses hourly global and diffuse radiation. The values of I_N are estimated for 12 locations across the world. The values of I_N obtained using the EAC method have been compared with values obtained using the model-based approach (Appendix-1). The comparison is also done with the measured values for some stations. Ninety percent of the estimated values of I_N using the EAC method for the stations like Angola, Egypt, Kuala Lumpur, Singapore, Brussels, Stuttgart, Ottawa, Birmingham, Los Angeles, Wellington, Perth and New Delhi are within ±5% of the values estimated by the model-based approach (Appendix-1).     

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.