Monthly Average Daily Solar Radiation Research Articles

Correlations for estimating solar radiation using sunshine hours and temperature measurement in Osogbo, Osun State, Nigeria

In this study, the global solar radiation on horizontal surface in Osogbo, Osun state, Nigeria was analyzed using 11-year data (1997–2007). Correlations using linear and quadratic expressions were developed to relate the global solar radiation on horizontal surface based on relative sunshine hours and temperature measurements for evaluating the monthly average daily global solar radiation. The calculated monthly clearness index values indicate that the prevailing weather condition in Osogbo is heavily overcast. All the developed quadratic correlations gave better correlation coefficients (0.834, 0.872 and 0.823 respectively) than the linear models. However, the Hargreaves and Samani related based quadratic model gave the best among the three developed quadratic expressions and is therefore suggested for estimating the monthly global radiation in this site and its surroundings.

Mapping Global Solar Radiation from Long-Term Satellite Data in the Tropics Using an Improved Model

This paper presents an improved model and its application for mapping global solar radiation from satellite data in the tropics. The model provides a more complete description of the absorption and scattering of solar radiation in the earth-atmosphere system as compared to the earlier models. The study is conducted in the tropical environment of Thailand. Digital data from the visible channel of GMS4, GMS5, GOES9, and MTSAT-1R satellites collected during a 15-year period (1995–2009) are used as a main input to the model. Satellite gray levels are converted into earth-atmospheric reflectivity and used to estimate the cloud effect. The absorption of solar radiation due to water vapour is computed from precipitable water derived from ambient temperature and relative humidity. The total ozone column data from TOMS/EP and OMI/AURA satellites are used to compute solar radiation absorption by ozone. The depletion of solar radiation due to aerosol is estimated from visibility data. In order to test its performance, the model is employed to calculate monthly average daily global solar radiation at 36 solar monitoring stations across the country. It is found that solar radiation calculated from the model and that obtained from the measurement are in good agreement, with a root mean square difference of 5.3% and a mean bias difference of 0.3%. The model is used to calculate the monthly average daily global solar radiation over the entire country, and results are displayed as monthly and yearly maps. These maps reveal that the geographical distribution of solar radiation in Thailand is strongly influenced by the tropical monsoons and local geographical features.

A Suitable Model to Estimate Global Solar Radiation in Black Sea Shoreline Countries

The new model for monthly average data is developed to predict monthly average global radiation with acceptable accuracy. The measured monthly average daily global solar radiation and sunshine duration for Istanbul-Samsun-Trabzon (Turkey), Varna (Bulgaria), and Odessa (Ukraine) were used to establish a second order polynomial equation for a suitable correlation model in Black Sea shoreline countries. Estimated data produced by the model were compared with the measured data. A good agreement between the estimated and the measured values of global solar radiation in Black Sea shoreline countries has been found. The new quadratic model seems to be used to estimate monthly average daily global solar radiation for the Black Sea region where the measured data is scarce.

Calculating the diffuse solar radiation in regions without solar radiation measurements

Correlations for calculating diffuse solar radiation can be classified into models with global solar radiation (H-based method) and without it (Non-H method). The objective of the present study is to compare the performance of H-based and Non-H methods for calculating the diffuse solar radiation in regions without solar radiation measurements. The comparison is carried out at eight meteorological stations in China focusing on the monthly average daily diffuse solar radiation. Based on statistical error tests, the results show that the Non-H method that includes other readily available meteorological elements gives better estimates. Therefore, it can be concluded that the Non-H method is more appropriate than the H-based one for calculating the diffuse solar radiation in regions without solar radiation measurements.

Estimating global solar radiation using common meteorological data in Akure, Nigeria

Abstract In this study, the global solar radiation on horizontal surface in Akure, Nigeria (Latitude 7.25° N and Longitude 5.2° E) using 22-year data (July 1983–June 2005) was analysed. Simple empirical correlations for evaluating the monthly average daily global solar radiation were developed. The calculated monthly clearness index values indicates that prevailing weather condition in Akure is partly overcast but can become heavily overcast during the months of July–September. The Angstrom–Page correlation predicted the monthly average daily global solar radiation better than the other correlations developed in this study. However, in the absence of the sunshine hour data, it was found that temperature only based correlations (especially the average temperature based correlation) and precipitation based correlation can be used to predict the global solar radiation within reasonable level of accuracy in Akure. The correlations presented in this study could be applied to locations with comparable weather condition to Akure.

The Calculation of Diffuse Radiation on a Horizontal Surface for Solar Energy Applications

To analyze the systems working with solar energy, it is required that values of the solar radiation belonging to the region have been known. The global solar radiation on a horizontal surface has been measured by the Turkish State Meteorological Service over all of the country, while the diffuse solar radiation has not been measured. In this study, empirical correlations are developed to establish a relationship between the monthly average daily diffuse fraction (Hd/H) and monthly average daily diffuse coefficient (Hd/Ho) with the monthly average daily clearness index (KT = H/Ho) for the province of Erzurum, Turkey. The six new models for estimating the monthly average daily diffuse solar radiation on a horizontal surface for Erzurum are validated, and the new models are then compared with the 10 models available in the literature. In order to indicate the performance of the models, the statistical test methods of relative percentage error, mean bias error, mean absolute bias error, mean relative error, root mean square error, and correlation coefficient are used. The results indicated that the correlations developed in the study predict diffuse solar radiation reasonably well for future projections.

Further investigation of empirically derived models with multiple predictors in estimating monthly average daily diffuse solar radiation over China

Two models based on Li et al. (2011) are developed for general application in estimating the monthly average daily diffuse solar radiation in China. The validation of these models is performed by comparing with four existing empirical models against the measured data. It is found that the proposed models have better performance than these existing models. This study further argues that ambient temperature and relative humidity incorporated into empirical models can generally improve its estimates. Hence, the two models can be recommended for general application in estimating the monthly average daily diffuse solar radiation in China.

Sunshine-based estimation of global solar radiation on horizontal surface at Lake Van region (Turkey)

In this study several sunshine-based regression models have been evaluated to estimate monthly average daily global solar radiation on horizontal surface of Lake Van region in the Eastern Anatolia region in Turkey by using data obtained from seven different meteorological stations. These models are derived from Angström–Prescott linear regression model and its derivatives such as quadratic, cubic, logarithmic and exponential. The performance of this regression models were evaluated by comparing the calculated clearness index and the measured clearness index. Several statistical tests were used to control the validation and goodness of the regression models in terms of the coefficient of determination, mean percent error, mean absolute percent error, mean biased error, mean absolute biased error, root mean square error and t-statistic. The results of all the regression models are within acceptable limits according to the statistical tests. However, the best performances are obtained by cubic regression model for Bitlis, Gevaş, Hakkari, Muş stations and by quadratic regression model for Malazgirt, Tatvan and Van stations to predict global solar radiation. The spatial distributions of the monthly average daily global solar radiation around the Lake Van region were obtained with interpolation of calculated solar radiation data that acquired from best fit models of the stations. The annual average solar energy potential for Lake Van region is obtained between 750kWh/m2 and 2485kWh/m2 with annual average of 1610kWh/m2.

Comparison of Some Existing Models for Estimating Monthly Average Daily Global Solar Radiation for Isparta

Global gunes radyasyonunun miktari ve zamansal dagilimi duzlemsel kollektorler, fotovoltaik sistemler vediger gunes enerjisi toplayicilari gibi gunes enerjisi sistemlerinin tasarimi icin birincil etkendir. Enerji-verimlibinalarin tasarimlari ve gunes enerjisi uygulamalari icin mimarlar ve muhendisler tarafindan bu parametrelerinbilinmesi gereklidir. Ancak bircok durumda, dogrudan olcum mevcut degildir. Bu nedenle global radyasyonutahmin etmek icin olculen bazi meteorolojik verileri kullanan numeriksel hesaplamalar etkili bir alternatifyoldur. Bu calismada, Isparta’da yatay duzleme gelen aylik ortalama gunluk global gunes radyasyonunbelirlenmesi icin literaturde bulunan bazi modeller incelenmistir. Incelemesi yapilan modeller bagil hatayuzdesi (e), belirlilik katsayisi (R2), ortalama yuzde hata (MPE), ortalama mutlak hata yuzdesi (MAPE),bagil hata karesi (SSRE), bagil standart toplam hata (RSE), ortalama sapma hatasi (MBE), karekok hatasi(RMSE) ve t-istatistik (t-stat) kullanan istatistiksel hata testlerine bagli olarak karsilastirilmistir. Istatistikselhata testlerin sonucuna gore, e (%1.77), R2 (%95.86), MPE (%0.127), MAPE (%8.95), SSRE (%5.22), RSE(%0.007), MBE (%0.092), RMSE (%1.39) ve t-stat (%0.812), Isparta’nin yatay duzlemi gelen global gunesradyasyonunun tahmin edilmesinde en iyi yaklasim Model 18c ile elde edilmektedir.

General formula for the estimation of global solar radiation on earth’s surface around the globe

The data such as global solar radiation, air temperature, relative humidity, wind and moisture, was collected from 875 stations around the globe. Of which data from 210 stations fairly spread on the earth surface was used to develop the formula for estimating the monthly average daily global radiation on a horizontal surface. In this study, using air temperature, relative humidity, wind, moisture and few derived parameters as independent variables, the most accurate equations have been obtained. The results show that the general formula developed could be used for the estimation of solar radiation with the local site parameters. Thus developed models have been validated with remaining 665 data sites. Finally two candidate models have been proposed. These models are capable of covering 50% of the land area on earth surface between latitude ±30°, enabling estimation accuracy to 93% of sites, with an estimation error (RMSE) limiting to 15%. Thus it is envisaged that, the proposed equations (models) can be used to estimate the monthly average daily global solar radiation in area where the radiation data is missing or not available. This helps in assessing the solar energy potential over necessitated area.

A model for determining the global solar radiation for Makurdi, Nigeria

An empirical model for determining the monthly average daily global solar radiation on a horizontal surface for Makurdi, Nigeria (Latitude 7°7′N and Longitude 8°6′E) was developed using the Angstrom–Page equation. The solar radiation (W/m 2), hours of bright sunshine and cloudiness were measured hourly from 0600 H to 1800 H daily for 18 months. The constants ‘a’ and ‘b’ of the Angstrom linear type equation were determined by plotting the clearness index (H/H o) against the possible sunshine hours (n s/N) to obtain the line of best fit. The constant ‘a’ was obtained from the intercept of the line on the y-axis while the constant ‘b’ was obtained from the slope of the line. The developed model for determining the global horizontal solar radiation at the location was H = H o [0.17 + 0.68(n/N)] with a coefficient of correlation of 0.78. The mean bias error and root mean square error that were used to test the performance of the constants were 0.17% and 1.22% respectively. The measured solar radiation was compared with the solar radiation predicted by the model and no significant difference was found between them using F-LSD at P ≤ 0.05.

Solar constant values for estimating solar radiation

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

A Systematic Study on the Monthly Mean Global Solar Radiation between Latitudes 65S and 65N

In this work, the monthly average daily global solar radiation reaching the earth on a horizontal surface was analyzed and compared. We used data of 115 surface stations, in a wide region of latitudes between 65S and 65N and having various climate types. The aim of this work is to investigate the climate types effects on the solar energy budgets and characterize the basic geographical and climatological parameters.

Techno-Economic Potential of Retrofitting Diesel Power Systems with Hybrid Wind-Photovoltaic-Diesel Systems for Off-Grid Electrification of Remote Villages of Saudi Arabia

Recent climatic anomalies such as hot summers, cold winters, hurricanes, and cyclones are all reflections of global warming due to burning of fossil fuels. To combat unprecedented global warming and to mitigate future energy challenges, there is worldwide interest in utilization of renewable sources of energy such as solar-photovoltaic (solar-PV) and wind energy. Other driving forces paving avenue for renewable energy include rapid escalation in oil prices, growing concerns regarding depletion of oil/gas reserves, etc. Retrofitting of diesel systems with hybrid wind-PV-diesel systems is being widely disseminated to reduce diesel fuel consumption and to minimize atmospheric degradation. One of the potential market for deployment of hybrid systems is in remote locations which are driven by diesel generators. The Kingdom of Saudi Arabia (KSA) has a number of remote villages scattered all over the Kingdom. The aim of this study is to analyze wind speed and solar radiation data of Rafha, KSA, and to assess the technical and economic potential of hybrid wind-PV-diesel power systems to meet the load requirements of a typical remote village Rawdhat Bin Habbas (RBH) with annual electrical energy demand of 15,943 MWh. Rafha is located near RBH. The monthly average wind speeds range from 2.99 m/s to 4.84 m/s at 10 m height. The monthly average daily global solar radiation ranges from 3.04 to 7.3 kWh/sq.m. The hybrid systems simulated consist of different combinations of 600 kW wind machines, PV panels, supplemented by diesel generators. National Renewable Energy Laboratory's (NREL) Hybrid Optimization Model for Electric Renewables (HOMER) software has been used to perform the techno-economic study. The simulation results indicate that for a hybrid system comprising of 1.2 MW wind farm capacity (two 600 kW units, 50 m hub-height) and 1.2 MW of PV capacity together with 4.5 MW diesel system (three 1.5 MW units), the renewable energy fraction with 0% annual capacity shortage is 24% (10% wind + 14% PV). The cost of generating energy (COE) from this hybrid wind-PV-diesel system has been found to be 0.118 $/kWh (“assuming diesel fuel price of 0.1$/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, unmet load, excess electricity generation, percentage of fuel savings and reduction in carbon emissions (relative to diesel-only situation) of different hybrid systems, cost breakdown of wind-PV-diesel systems, COE of different hybrid systems, etc.

Correlations for estimation of daily global solar radiation with hours of bright sunshine in Turkey

In this study, seven different empirical equations are employed to estimate the monthly average daily global solar radiation on a horizontal surface for provinces in the different regions of Turkey, using only the relative duration of sunshine. Daily global solar radiation and sunshine measurement data collected for the provinces of Turkey are obtained from the Turkish State Meteorological Service. The regression constants of the new models developed in this study are found for the provinces of Turkey, as well as that of some models given in the literature. In order to indicate the performance of the models, the statistical test methods of the mean bias error (MBE), mean absolute bias error (MABE), mean relative error (MRE), root mean square error (RMSE) and correlation coefficient (r) are used.

Diffuse solar radiation estimation models for Turkey’s big cities

A reasonably accurate knowledge of the availability of the solar resource at any place is required by solar engineers, architects, agriculturists, and hydrologists in many applications of solar energy such as solar furnaces, concentrating collectors, and interior illumination of buildings. For this purpose, in the past, various empirical models (or correlations) have been developed in order to estimate the solar radiation around the world. This study deals with diffuse solar radiation estimation models along with statistical test methods used to statistically evaluate their performance. Models used to predict monthly average daily values of diffuse solar radiation are classified in four groups as follows: (i) From the diffuse fraction or cloudness index, function of the clearness index, (ii) From the diffuse fraction or cloudness index, function of the relative sunshine duration or sunshine fraction, (iii) From the diffuse coefficient, function of the clearness index, and (iv) From the diffuse coefficient, function of the relative sunshine duration or sunshine fraction. Empirical correlations are also developed to establish a relationship between the monthly average daily diffuse fraction or cloudness index ( K d) and monthly average daily diffuse coefficient ( K dd) with the monthly average daily clearness index ( K T) and monthly average daily sunshine fraction ( S/ S o) for the three big cities by population in Turkey (Istanbul, Ankara and Izmir). Although the global solar radiation on a horizontal surface and sunshine duration has been measured by the Turkish State Meteorological Service (STMS) over all country since 1964, the diffuse solar radiation has not been measured. The eight new models for estimating the monthly average daily diffuse solar radiation on a horizontal surface in three big cites are validated, and thus, the most accurate model is selected for guiding future projects. The new models are then compared with the 32 models available in the literature in terms of the widely used statistical indicators, namely; the relative percentage error ( E), coefficient of determination ( R 2), the mean percentage error (MPE), the mean absolute percentage error (MAPE), the sum of the squares of relative errors (SSRE), the relative standard error (RSE), the mean bias error (MBE), the root mean square error (RMSE), and the t-statistic ( t-stat) method combining the last two errors. It may be concluded that the new models predict the values of cloudness index ( K d) and diffuse coefficient ( K dd) as a function of clearness index ( K T) and sunshine fraction ( S/ S o) for three big cities in Turkey better than other available models, while all the models tested appear to be location independent models for diffuse radiation predictions, at least for three big cities in Turkey. It is also expected that the models reviewed and developed will be beneficial to everyone involved or interested in the design and study of solar energy.

Statistical Modeling of Spatio-Temporal Variability in Monthly Average Daily Solar Radiation over Turkey.

Though one of the most significant driving forces behind ecological processessuch as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from othermeteorological data through (geo)statistical models. In this study, spatial and temporalpatterns of monthly average daily solar radiation on a horizontal surface at the ground levelwere quantified using 130 climate stations for the entire Turkey and its conventionally-accepted seven geographical regions through multiple linear regression (MLR) models as afunction of latitude, longitude, altitude, aspect, distance to sea; minimum, maximum andmean air temperature and relative humidity, soil temperature, cloudiness, precipitation, panevapotranspiration, day length, maximum possible sunshine duration, monthly average dailyextraterrestrial solar radiation, and time (month), and universal kriging method. Theresulting 20 regional best-fit MLR models (three MLR models for each region) based onparameterization datasets had R²adj values of 91.5% for the Central Anatolia region to 98.0%for the Southeast Anatolia region. Validation of the best-fit MLR models for each region led to R₂ values of 87.7% for the Mediterranean region to 98.5% for the Southeast Anatoliaregion. The best-fit anisotropic semi-variogram models for universal kriging as a result ofone-leave-out cross-validation gave rise to R² values of 10.9% in July to 52.4% inNovember. Surface maps of monthly average daily solar radiation were generated overTurkey, with a grid resolution of 500 m x 500 m.

Estimating and Statistically Analyzing the Global Solar Radiation Potential over Big Cities in Turkey

This study develops empirical models in order to estimate the monthly average daily global solar radiation on a horizontal surface (H). The seven big cities considered in the model have 33.4% of Turkey's population and are as follows: Izmir in the Aegean Sea, Samsun in the Black Sea, Ankara in the Central Anatolia, Van in the East Anatolia, Istanbul in the Marmara, Antalya in the Mediterranen Sea, and Urfa in the Southeast Anatolia Region of Turkey. The developed models were analyzed using the seven statistical analyzing methods such as the mean percentage error (MPE), mean absulate percentage error (MAPE), sum of squares of relative error (SSRE), relative standard error (RSE), mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R). It may be concluded that the present models estimate the values of H, reasonably well for the cities studied and possibly elsewhere with similar climatic conditions.

Global Solar Radiation Potential, Part 1: Model Development

Solar engineers, architects, agriculturists, and hydrologists dealing with many applications of solar energy require a reasonably accurate knowledge about the availability of solar resources at any place. For this purpose, in the past, several empirical correlations have been developed in order to predict the solar radiation around the world. The present study, consisting of two parts, analyzes global solar radiation over the Central Anatolia Region (CAR) of Turkey along with its twelve provinces. Part 1 of this study includes the solar radiation models developed, while their statistical analysis is presented in Part 2. In the analysis, the data of the monthly average daily global solar radiation and sunshine duration measured by the Turkish State Meteorological Service in the period from January 1990 to December 1996 are used. Empirical models to estimate the monthly global solar radiation on a horizontal surface for each province are developed. The results obtained have indicated that the models developed here predict solar radiation reasonably well for future projections.

Estimating the horizontal diffuse solar radiation over the Central Anatolia Region of Turkey

Abstract The main objective of the present study is to develop new hybrid models to predict the monthly average daily diffuse solar radiation on a horizontal surface over Turkey’s Central Anatolia Region (CAR), which covers the 12 provinces (Afyon, Ankara, Cankiri, Corum, Eskisehir, Kayseri, Kirsehir, Konya, Nevsehir, Nigde, Sivas and Yozgat), as an example. The models proposed by many investigators to estimate the diffuse solar radiation were reviewed. Although the global solar radiation and sunshine duration have been measured by the Turkish State Meteorological Service (DMI) over all the country since 1964, the diffuse solar radiation has not been measured. The twelve new hybrid models for estimating the monthly average daily diffuse solar radiation on a horizontal surface in the CAR were validated, and thus, the most accurate model was selected for guiding future projects.