Monthly Average Global Solar Radiation Research Articles

NEW MODELS FOR ESTIMATION OF DIFFUSE SOLAR RADIATION USING METEOROLOGICAL PARAMETERS FOR BENIN, NIGERIA

In this comprehensive study, an extensive 22-year dataset (2001-2022) for Benin (Latitude 6.32 oN, Longitude 5.10 oE and 77.80 m above sea level) were obtained from the National Aeronautic Space Administration (NASA) website. The datasets comprises of the monthly average daily global solar radiation, diffuse solar radiation, relative humidity, atmospheric pressure, wind speed, and mean temperature, was utilized to develop 19 new models for estimating diffuse solar radiation. These models were categorized into five distinct groups: modified Page, Liu and Jordan models; clearness index and one-variable models; two-variable models; three-variable models, and a four-variable model. These models were statistically evaluated using a set of five validation indices—Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t-test, and the coefficient of determination (R²). The study identified the most effective models in each category. Equation 28b from the modified Page, Liu and Jordan category, Equation 28f from the clearness index and one-variable models, Equation 28j from the two-variable models, and Equation 28o from the three-variable models category were found to be the best-performing models. A comparative assessment of these performed models revealed that the quadratic regression model (Equation 28b) stood out as the most suitable for accurately estimating diffuse solar radiation in Benin. This implies that the developed model equation 28b can be used to estimate the diffuse solar radiation for Benin and locations with similar climatic conditions

Sunshine and Temperature Based Models for Estimating Global Solar Radiation in Maiduguri, Nigeria

Nine existing sunshine based models and three existing temperature based models were evaluated and compared to ascertain the most suitable models for estimating global solar radiation in Maiduguri; the most suitable sunshine based and most suitable temperature based models were also compared. The measured monthly average daily global solar radiation, sunshine hours, maximum and minimum temperature meteorological parameters during the period of thirty one years (1980 – 2010) was utilized and the evaluated models were tested statistically using validation indicators of coefficient of determination, Mean Bias Error, Root Mean Square Error, Mean Percentage Error, t – test, Nash – Sutcliffe Equation and Index of Agreement. The results indicated that the linear exponential sunshine based model and the logarithmic temperature based model were found more accurate for global solar radiation estimation in Maiduguri as compared to other evaluated models. Furthermore, the logarithmic temperature based model was found more accurate for estimating global solar radiation as compared to the linear exponential sunshine based model, and this was testified from the figure showing the comparison between the recommended sunshine based and temperature based models in which the recommended temperature based model depicts the best fitting with the measured global solar radiation data.

Empirical Model for Estimating Measured Monthly Average Global Solar Radiation in Lawra using TMY Data

In this study, simple and multiple regression models were developed to estimate the monthly average daily global solar radiation in Lawra, Ghana using ground measurement of global horizontal irradiance (Nov 2020–May 2022) and typical meteorological year (TMY) data (Jan 2017–Dec 2019). Various predictor variables such as sunshine ratio, minimum relative humidity and maximum relative humidity ratio, minimum and maximum temperature ratio, etc. were correlated from the TMY data. Many model equations were developed with the variables ranging from one to eight. The best model from each category was chosen and compared using statistical indices to determine the overall best model. We used the JMP statistical software’s ‘All Possible Models’ functionality to select the best model from each category. The selected models where then compared using the adjusted R-squared, mean absolute percentage error, and the root mean square error statistical indices. The best model equation correlated with eight independent variables with adjusted R-squared of 0.99. The equation can be used to estimate monthly global solar radiation in Lawra and in locations with similar climatic conditions where ground measurement of radiation data is unavailable but have access to the National Solar Radiation Database’s (NSRDB) TMY data.

A generalized approach for the determination of optimum tilt angle for solar photovoltaic modules with selected locations in Ethiopia as illustration examples

The amount of total solar energy that strikes the photovoltaic module's surface directly affects how much power is generated. On the other hand, solar energy is influenced by the solar module's location, tilt angle, and orientation. The models presented in this study can be used to determine the seasonal and annual optimal tilt angles of photovoltaic modules at any location in Ethiopia as a function of the location's latitude and elevation without the need for solar radiation data. Both isotropic and anisotropic diffuse solar radiation models were used to determine the monthly, seasonal, and annual optimal tilt angles. The monthly average daily global horizontal solar radiation for a total of 44 study sites, 32 for training and 12 for testing, were retrieved from the National Aeronautical and Space Administration database. The optimal tilt angle and regression models were determined by developing and applying algorithms in the programming languages MATLAB and R. The proposed model estimates the optimal tilt angle with the fewest statistical validation errors. By using the proposed monthly optimal tilt angles, solar radiation gains of 6.76% - 8.48% (for isotropic models) and 10.16% - 26.97% (anisotropic models) were obtained for Bahir Dar city. The solar radiation gains for the cities of Adigrat, Butajira, and Gode were found to be 7.18–9.02% (isotropic) and 10.90%–28.06% (anisotropic), 5.43%–7.05% (isotropic) and 8.48%–25.99% (anisotropic), and 4.33%–5.79% (isotropic) and 6.96%–23.03% (anisotropic), respectively. The results of this study were further confirmed by comparing them to previously published papers and online PVGIS and NREL's PVWatt software tools.

Performance Evaluation and Statistical Analysis of Solar Energy Modeling: A Review and Case Study

The main target of this research is a quantitative review of literature on global solar radiation (GSR) models available for different stations around the world. The statistical analysis of 400 existing sunshine-based GSR models on a horizontal surface is compared using 40-year meteorological data in the selected locations in Egypt. The measured data is divided into two sets. The first sub-data set from 1980 to 2019 was used to develop empirical correlation models between the monthly average daily global solar radiation fraction (H/H0) and the monthly average of desired meteorological parameters. The second sub-data set from 2015–2019 was used to validate and evaluate the derived models and correlations. The developed models were compared with each other and with the experimental data of the second subset based on the statistical error indicators such as RMSE, MBE, MABE, MPE, and correlation coefficient (R). The statistical test of the correlation, coefficient (R), for all models gives very good results (above 0.92). The smallest values of t-Test occur around the models (M 272, M 261, M 251, and M 238). The accuracy of each model is tested using ten different statistical indicator tests. The Global Performance Indicator (GPI) is used to rank the selected GSR models. According to the results, the Rietveld model (Model 272) has shown the best capability to predict the GSR on horizontal surfaces, followed by the Katiyar et al. model (Model 251) and the Aras et al. model (Model 261).

Development of Optimal Tilt Angle Models of a Photovoltaic Module for Maximum Power Production: Ethiopia

The power generated from the photovoltaic module is directly related to the magnitude of total incident solar radiation on the surface of the solar module. The total incident solar radiation depends on the location, tilt angle, and orientation of the solar module. In this paper, generic models were developed that determine the seasonal and annual optimal tilt angle of the Photovoltaic module at any location in Ethiopia without using meteorological data. Both isotropic and anisotropic diffuse solar radiation models were used to estimate monthly, seasonal, and annual optimal tilt angles. The monthly average daily global horizontal solar radiation for a total of 44 cities -32 for training and 12 for testing were obtained from the National Aeronautical and Space Administration database, and algorithms were developed and implemented using MATLAB and R programming software to obtain optimum tilt angle and regression models. The study showed that the developed model accurately estimates the optimal tilt angle with the minimum statistical validation errors. It is also found that 5.11% to 6.275% (isotropic) and 5.72% to 6.346% (anisotropic models) solar radiation energy is lost when using the yearly average fixed optimal tilt angle as compared with the monthly optimal tilt angle. The result of this study was also validated by comparing it with the previously published works, PVGIS and PVWatt online software. The graphical abstract is included in the supplementary file.

Best Combinations of Inputs for ANN-Based Solar Radiation Forecasting in Morocco

In this paper, for forecasting, with the high possible accuracy, the solar radiation intensity, an approach for identifying the optimum set of input data from large sets of input parameters is elaborated, assessed, and proposed. This approach belongs to techniques of Input Variable Selection (IVS) and was established using artificial neural networks (ANNs) as an effective means for numerically approximating the computed objective function: Monthly Average Global Solar Radiation (MAGSR). Based on the approach suggested, we could determine the best combinations of inputs that can reveal great possible correlation and approximation with the output considered parameter. Recorded data from 35 stations of different climatic zones were used for both training and testing purposes. Several new linear formulas between the MAGSR and other climatological and meteorological parameters were developed and evaluated. Based on these relationships, we can forecast other climatological and meteorological parameters like temperature, wind speed, and humidity. The statistical analysis was done, and the best performance of the proposed approach has been well checked and duly validated.

Novel Assessment and Classification of Monthly Average Daily Global Solar Radiation Models Through a Figure of Merit Called Irradiation Time Equivalence: Analysis of 70 Regression Models Based on Air Temperature and Sunshine Hours Predictors

Abstract Irradiation time equivalence pioneers the classification of models that predict monthly average daily global solar radiation on a horizontal surface based on their double cross-validation performances. By exploiting indigenous irradiation data, novel irradiation-based models can be created and used to classify prediction models, thereby facilitating a deeper understanding of model performance beyond routine summary statistics. The concept was demonstrated by formulating novel 1-hour and 2-hour irradiation-based models to predict monthly average daily global horizontal irradiation. Double cross-validations of the two irradiation-based models and 70 existing regression models were performed using a pair of 5-year subsets. The 70 models used the measured meteorological predictors of air temperature and sunshine hours, either alone or combined. The irradiation time equivalence of a model evaluated under double cross-validation has been defined as the minimum number of hours of measured irradiation needed to predict the monthly average daily irradiation in an average year, with a root mean square error less than or equal to that of the model. Despite their intracompetitiveness, all 44 temperature-based models had an irradiation time equivalence of 1 h, while the remaining 26 models that contained the sunshine-hours predictor were classified with a higher-performance rank of 2 h. An irradiation time equivalence scale extending to 13 h was also developed to cater to the classification of higher-performance models. This fresh perspective on model performance directs future investigations toward determining whether prediction models exhibit global classification constancy.

ESTIMATION OF GLOBAL SOLAR RADIATION USING SUNSHINE HOURS IN SOKOTO NIGERIA

Inadequate installations of materials such as solar water heater, solar still, solar dryer, and solar cooker etc. Which required solar radiation and maximally, in the area location of is a major problem and this hinders the abundant utilization of solar energy as it can be harnessed directly without any requirement of external energy such as electricity. It is the lack of the information that limits the number of installations in the study area. Therefore, it is compulsory to study and analyzed the solar radiation of our environment to get better view of monitoring the performance of solar energy conversion system in Sokoto State, so that companies and government should know what period or seasons can therefore utilize the abundant solar energy. A new model was developed for estimation the monthly average daily global solar radiation. In this research a modified angstrom model for estimation of global solar radiation in Sokoto, Nigeria using sunshine duration based on meteorological data were used. However, solar radiation estimates are too local since they rely on weather stations or have a resolution that is too satellites. In this work, a model was developed for estimation of global solar radiation on horizontal surface for Sokoto at latitude of m13 13.00E and longitude of 5.250N. Global solar radiation and maximum temperature data for Sokoto were used to fit the Angstrom model, Regression coefficient a, b, and c. 1.12, 0.65, and 0.32 respectively were obtained from the models base on sunshine duration respectively. In order to evaluate the results, three statistical methods have been used namely: mean bias, root mean square, and percentage errors of values -6.47, 6.47 and 41.20% respectively. It was found from statistical model’s performance indicators that the model provides reasonably high degree of precision in the estimation of average global solar radiation on horizontal surfaces.

Estimating Global Solar Radiation from Empirical Models: An Application

Solar radiation data are required for many applications and many areas of research. In order to achieve this, several empirical models have been suggested to predict the global solar radiation in Turkey and other countries. The different meteorological data as the global solar radiation, the sunshine duration, the temperature, the atmospheric pressure, the wind speed and the relative humidity were measured by Eskisehir Osmangazi University during the period between 01 January 2011 and 31 December 2014. These data were used to develop the empirical models in order to estimate the monthly average daily global solar radiation on the horizontal surface over Eskisehir City of Turkey. The developed empirical models were analyzed with the widely used nine statistical methods, namely; the relative percentage error (E), the mean percentage error (MPE), the mean absolute percentage error (MAPE), the sum of squares of relative errors (SSRE), the relative standard error (RSE), the mean bias error (MBE), the root mean square error (RMSE), the t-statistic method (t-stat) and coefficient of determination (R2). It is expected that the new model will be beneficial to everyone who is the solar engineers, architects, agriculturists, and hydrologists involved or interested in the design and study of solar energy applications such as solar furnaces, wood drying, stoves, concentrating collectors, interior illumination and thermal load analyzing of buildings, and photovoltaics, agricultural and meteorological forecasting.

Empirical Modelling of Global Solar Radiation in Hatay (Turkey) Province

There are many models used in global solar radiation prediction. However, these prediction models vary according to the climate and geographic characteristics of the region involved. When the prediction model determined for a region is used in a different region, the prediction model may not work. In order to gain absolute and stable results from these models, the studies should be either custom-made or tested. In this study, 7 different models were examined, comparison charts were created and statistical interpretations were made in order to determine the monthly average global solar radiation coming to the horizontal plane taking into account the climatic characteristics of Hatay province, located in the eastern 39.92º latitude and northern longitude 36.16º, covering an area of 5403 km, and has a humid climate with a value of 41.3, based on De Martonne-Gottmann’s drought index and 50.6 based on Erinç's rainfall efficiency index. Under the scope of this study, the most ideal global solar radiation prediction model was selected by making a statistical evaluation according to the parameters of determination coefficient (R²), mean percentage error (MPE), mean deviation error (MBE), root mean square error (RMSE). A general assessment of the graphics and statistical parameters of the predictions obtained by using the models and the measured data has indicated Model 4 as the most successful model by an RMSE value of 0.17306, and the least successful model was Model 3 by an RMSE value of 2.11851. When the models are interpreted according to the determination coefficient, it has been observed that other models are generally successful. However, this situation does not coincide with the comparison charts of the predicted and measured data. For this reason, it was seen that the determination coefficient was not sufficient in the statistical evaluation of the prediction models. In the interpretation of the models, it was observed that the interpretation of root mean square error, mean percentage error and mean deviation error values together gave more accurate results. In conclusion, it has been suggested that Model 4 should be preferred for the global solar radiation forecast of Hatay province.

Off-grid solar photovoltaic/hydrogen fuel cell system for renewable energy generation: An investigation based on techno-economic feasibility assessment for the application of end-user load demand in North-East India

In this paper, an optimal off-grid solar photovoltaic (PV)/hydrogen fuel cell (FC) (HFC) based energy system is proposed for renewable energy generation to supply electricity to the end-user load demand in north-east (NE) Indian states. The energy system is modeled and simulated in the HOMER software. The monthly average global horizontal solar radiation (GHSR) and ambient temperature of the NE states are found to be 3.95–4.79 kWh/m2 and 12.9–25.3 °C, respectively. The synthesized typical AC electrical load profile of 10 kWp is assumed to have a scaled daily annual mean value equal to 138 kWh/d and an average base demand value equal to 5.75 kW. With the considered connected load, the available GHSR and ambient temperature, the optimal sizes of renewable energy components for the considered eight geographical locations (latitude: 23° 30′-27° 3′ North, longitude: 88° 37' – 94° 7′ East) are determined based on the minimum levelized cost of energy (COE) and lowest net present cost (NPC). The optimal system architecture range obtained is 110–120 kW PV array, 10–15 kW FC, 30–60 kW electrolyzer, 40–60 kg hydrogen tank capacity and 15 kW converter. Based on optimization results, the levelized COE and NPC range obtained are 0.509–0.689 $/kWh and $ 3,27,557–4,43,004, respectively, which confirm the cost-effectiveness of the proposed optimal energy system. Besides, with a renewable fraction of 100%, the electricity generated by the PV/HFC system satisfied the load demand and produced excess electricity with capacity factor found to be 16.4–31.2% in all the NE Indian states. Moreover, the optimized electrical profile, PV profile, inverter profile, and hydrogen production from an FC are compared and analyzed in terms of monthly average and annualized values for all the NE states. Also, the range of net hydrogen produced by the electrolyzer over the year obtained is 1538–1856 kg/yr.

Correlating clearness index with cloud cover and other meteorological parameters for forecasting the global solar radiation over Morocco

In this study, new correlations between clearness index and cloud cover without and/or with other meteorological parameters were proposed for estimating the monthly average daily global solar radiation (MADGSR) on a horizontal surface. By using a long-term of continuously observed meteorological data at fourteen cities over Morocco, seventeen new correlation models were established, evaluated and compared with the other seven cloud-based models selected from the literature. The statistical analysis was done based on the coefficient of determination (R²), mean bias error (MBE), mean square error (MSE), root mean square error (RMSE), standard deviation (σ) and performance score (φ). Results revealed that the new proposed model, which combines the clearness index with the cloud cover and all other meteorological parameters, has a good prediction level of the MADGSR for the considered Moroccan cities. The accuracy of the newly developed model may recommend it to be employed in the future design and assessment of the performance of different solar energy applications in Morocco and in other locations with similar climatic conditions.

Assessment of Solar Energy Potential of East Gojjam Zone Ethiopia Using Angestrom-Prescott Model

Only a small number of Ethiopia’s rural population has access to electricity. These rural areas can be electrified using different electrification approaches. One of the prime challenges in the decision making process is to obtain reliable information about the energy potential of the region under consideration. In this paper, an assessment of the solar energy potential of East Gojjam Zone in Ethiopia is presented. In the study area, there are only four meteorological measurement stations, namely: Debre Markos, Debrewerk, Mota, and Yetnora. The data for the hours of sunshine for these sites is collected from the National Meteorological Agency, Bahir Dar Branch Office. The data is prepared and used to calculate the mean global horizontal solar radiation using Angestrom-Prescott (AP) Model. An AP model for the four study sites was developed. The model regression coefficients, a and b, are estimated for each study site for respective latitudes, average hours of sunshine and day length. According to the models, the annual mean daily global horizontal radiation for Debre Markos, Debrewerk, Mota, and Yetnora is 5.88, 6.52, 6.28, and 6.31 kWh/m2/day, respectively, and 6.30kWh/m2/day for East Gojjam Zone, which is actually a very good solar energy potential. According to the monthly average global horizontal solar radiation profiles, the study sites receive the highest solar radiation in April and lowest solar radiation in July and August. The radiation in Debre Markos varies between 3.97 and 5.88kWh/m2/day, but Debrewerk receives more uniform solar radiation throughout the year. By considering intermittency and average solar energy potential of the four sites, Debrewerq and Debre Markos are the best and the worst sites, respectively, for large solar energy projects.

Estimation of Global Solar Radiation and Optimal Tilt Angles of Solar Panels for Pune, India

Solar panels can achieve the highest yield when they are oriented in the right way as the influence of the tilt angles can lead to a high impact on the performance. This paper demonstrates the effect of the tilt angle on the final yield and maximum utilization of solar energy. The annual optimal tilt angle of the solar panels for Pune was found out using the Liu and Jordan model. The optimal tilts yielding an increase of 7% was found out to be 0° on the months starting from April and lasting till September and 40° starting from October and holding at 40° till March. By changing the tilt angle every month, there was an increase in the yield by more than 8%. For better yield and maximum utilization of solar energy, optimizing the tilt angles of solar panels monthly or even twice a year is effective based on the study. Most of the panels are fixed at an angle equal to the latitude of the place and oriented towards the Southern sky in the northern hemisphere. Measurements of the monthly average global solar radiation, monthly average temperatures, and monthly average relative humidity were compared. Further ahead regression correlation for a linear model was carried and the regression coefficients a and b were found out to be 0.2804 and 0.3618 respectively.

Estimating Daily Global Solar Radiation with No Meteorological Data in Poland

The aim of the study was to calibrate coefficients and evaluate performance of simple, day-of-the-year, global solar radiation (H) models nominated from the literature. Day-of-the-year models enable estimation of global solar radiation when no meteorological data is available. The study used 16-year-long data series of daily H, taken at 15 actinometric stations located in various parts of Poland. The goodness-of-fit of the models to the actual long-term monthly average daily global solar radiation data expressed by determination coefficient (R2) ranges from 0.94 to 0.97. Depending on statistical indicators analysis (root mean square error—RMSE, mean absolute bias error—MABE, mean average percentage error—MAPE) the best model was selected. The averaged values of H computed by the recommended model deviate from those measured by 4.16% to 8.71%. Locally calibrated, day-of-the-year model provides satisfactory accuracy and—where meteorological data is unavailable—can be used to estimate mean monthly daily global solar radiation in Poland and similar climate conditions.

Empirical Models for Estimating Tropospheric Radio Refractivity Over Osogbo, Nigeria

Background:Estimation of tropospheric radio refractivity is significant in the planning and design of terrestrial communication links.Methods:In this study, the monthly average daily atmospheric pressure, relative humidity and temperature data obtained from the National Aeronautics and Space Administration (NASA) during the period of twenty two years (July 1983 - June 2005) for Osogbo (Latitude 7.470N, Longitude 4.290E, and 302.0 m above sea level) were used to estimate the monthly tropospheric radio refractivity. The monthly average daily global solar radiation with other meteorological parameters was used to developed one, two, three and four variable correlation(s) tropospheric radio refractivity models for the location. The accuracy of the proposed models are validated using statistical indicator of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Nash - Sutcliffe Equation (NSE) and Index of Agreement (IA).Results:In each case one empirical model was recommended based on their exceptional performances after ranking, except for the two variation correlations with two empirical models. The recommended models were further subjected to ranking from which the three variable correlations model that relates the radio refractivity with the absolute temperature, relative humidity and global solar radiation was found more suitable for estimating tropospheric radio refractivity for Osogbo with R2= 100.0%, MBE = -0.2913 N-units, RMSE = 0.3869 N-units, MPE = 0.0811%, NSE = 99.9999% and IA = 100.00%.Conclusion:The newly developed recommended models (Equations 16c, 17d, 17f, 18d and 19) can be used for estimating daily and monthly values of tropospheric radio refractivity with higher accuracy and has good compliance to highly varying climatic conditions for Osogbo and regions of similar climatic information.

Empirical Models for Estimating Tropospheric Radio Refractivity Over Osogbo, Nigeria

Background:Estimation of tropospheric radio refractivity is significant in the planning and design of terrestrial communication links.Methods:In this study, the monthly average daily atmospheric pressure, relative humidity and temperature data obtained from the National Aeronautics and Space Administration (NASA) during the period of twenty two years (July 1983 - June 2005) for Osogbo (Latitude 7.470N, Longitude 4.290E, and 302.0 m above sea level) were used to estimate the monthly tropospheric radio refractivity. The monthly average daily global solar radiation with other meteorological parameters was used to developed one, two, three and four variable correlation(s) tropospheric radio refractivity models for the location. The accuracy of the proposed models are validated using statistical indicator of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Nash - Sutcliffe Equation (NSE) and Index of Agreement (IA).Results:In each case one empirical model was recommended based on their exceptional performances after ranking, except for the two variation correlations with two empirical models. The recommended models were further subjected to ranking from which the three variable correlations model that relates the radio refractivity with the absolute temperature, relative humidity and global solar radiation was found more suitable for estimating tropospheric radio refractivity for Osogbo with R2= 100.0%, MBE = -0.2913 N-units, RMSE = 0.3869 N-units, MPE = 0.0811%, NSE = 99.9999% and IA = 100.00%.Conclusion:The newly developed recommended models (Equations 16c, 17d, 17f, 18d and 19) can be used for estimating daily and monthly values of tropospheric radio refractivity with higher accuracy and has good compliance to highly varying climatic conditions for Osogbo and regions of similar climatic information.

Developing of the new models in solar radiation estimation with curve fitting based on moving least-squares approximation

Recently, serious progress has been made in solar energy applications in developed and developing countries. Solar radiation on a horizontal surface is the basic parameter required for the design of solar energy systems and for evaluating the system performance. Therefore, solar radiation the exact determination of the amount of land in different latitudes on the earth's surface is of great importance in many solar energy applications. In this study, Angstorm coefficients were determined by Moving Least Squares Approximation (MLSA). Three different models were obtained by using the moving least squares method. In this study, new empirical models were developed for determining the monthly average daily global solar radiation on a horizontal surface for Antalya. The developed models were compared with the models in the literature by using different error analysis methods. The statistical compatibility of the investigated models was tested and the model closest to the measurements was determined. Although, this study concluded that the suggested methods are applicable to estimate the monthly average daily diffuse radiation on a horizontal surface for selected region, it has been observed that the performance of these models varies according to years and the error analysis test used. If the results are generally evaluated the developed linear model showed the best performance to estimate the global solar radiation on a horizontal surface for Antalya. Also, among the models used in the literature, the Togrul model showed the best performance for selected region.

Prediction and performance assessment of global solar radiation in Indian cities: A comparison of satellite and surface measured data

The design and performance assessment of solar photovoltaic/thermal system requires the knowledge of global solar radiation. Generalised models to assess the monthly average global solar radiation of twelve locations in India were established using sunshine hours available for 14 years (2000–2014) obtained from the World Radiation Data Centre (WRDC), Russia. Statistical analysis is carried out to assess the accurate model to estimate the global solar radiation which includes mean bias error, root mean square error, mean absolute percentage error, the coefficient of determination and uncertainty at 95%. Also, the assessment of the global radiation values obtained from satellite data by the National Renewable Energy Laboratory (NREL) is performed. Further, Global Performance Indicator (GPI) is introduced to find the ranking of models from the overall performance of the investigated models by scaling statistical indicators. The comparison of the NREL estimated data and WRDC data shows that the satellite data overestimates the surface measured data between 10 and 15% for seven locations, whereas, for the remaining four stations, it is between 7 and 9.5%.