Estimation of Monthly Mean Global Solar Radiation Over Semi-arid Region, Kadapa Using Meteorological Parameters (original) (raw)
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Journal of Renewable and Sustainable Energy, 2017
Solar radiation information at the site of solar energy systems is required for proper planning and execution of energy projects. In this work, global and diffuse solar radiations were measured for a period of two years (September, 2013 to August, 2015) in the Humid Subtropical Climatic Region of India in the city of Aligarh (27.89 N, 78.08 E). Secondary standard pyranometers were used to observe solar radiation at the ground level. The measured data for Aligarh were compared with the available data for the neighboring Capital city, New Delhi (28.61 N, 77.21 E). It was observed that Aligarh has a better availability of solar energy and solar energy utilization potential. Annual average global and diffuse solar radiations were observed to be 22.12 and 7.92 MJ/m 2-day, respectively, for Aligarh. Using measured solar radiation data for Aligarh, six empirical models were established to assess monthly mean diffuse solar radiation (by correlating the diffuse fraction with the sky-clearness index). Models were analyzed in terms of several statistical indicators and exhibited reasonable agreement with correlation coefficients in the range of 0.7610 to 0.8188. Models were subsequently ranked based on the Global Performance Indicator. The Global Performance Indicator (GPI) of the developed models was in the range of À1.86 to 5.84, and the highest GPI was achieved for the cubic model.
Renewable and Sustainable Energy Reviews, 2017
In the present work, long-term solar radiation assessment was performed for three years (September 2013 to August 2016) in Humid-Subtropical Climatic Region of India for the city of Aligarh (27.88°N, 78.08°E). Annual average global, beam and diffuse solar radiation values for Aligarh were observed as 21.01 MJ/m 2-day, 13.40 MJ/m 2-day and 7.61 MJ/m 2-day. Annual average sky-clearness index, diffuse fraction and diffusion coefficient were found to be 0.66, 0.37 and 0.24 respectively. Ground based global solar radiation measurements were compared with the available satellite data of the closest coordinate location (27.50°N, 78.50°N). Strong association was found between the ground measurements and satellite data. Further, empirical models for estimation of monthly mean diffuse solar radiation were developed using ground-based measured data. Diffuse solar radiation was modelled in terms of single and two input variables (namely sky-clearness index and relative sunshine period). A total of 42 new models in six different categories were developed. Proposed models were also compared with well-established models from literature. Models were assessed for performance in terms of ten most frequently used statistical indicators. Subsequently, proposed models were ranked in order of suitability of estimation within their respective category as well as among the group of all the developed models using Global Performance Index (GPI). Overall GPI of developed models was found in the range of −1.2677 to 5.5596 with the highest value representing the best model. It was inferred that two input variable models perform much better in comparison to single variable input models. Among the two variable models, diffuse fraction model in terms of sky-clearness index and relative sunshine period (each in order one) was found to be the most accurate. Excellent agreement was affirmed between estimated and measured values from two variable models. The use of single variable models was also suggested within reasonable accuracy.
Renewable Energy, 2019
The primary objective of the present work is to introduce a new method, i.e., Theory of Experimentation for prediction of monthly average global solar radiation. Meteorological data for 15 years is accessed considering six input predictors (i.e., latitude, longitude, altitude, relative humidity, temperature, and sunshine hours). Global solar radiation model is developed using various input parameters, and the accuracy of the developed models is assessed using statistical errors. The established model forms are also compared with the models available in the literature. Also, Global Performance Indicator is employed to sort the models for the development of the ranking system. A five-variable global solar radiation model (M-06) is found the best amongst all the proposed models (on training dataset) where the determination coefficient is 0.9424, and the mean percentage error is À0.1524%; whereas, for validation dataset, a two-variable regression model was seen to be the best. The study reveals that the effectiveness of the developed Global solar radiation model does not increase with an increase in the input variables; however, altitude, relative humidity, and sunshine hours are the dominating parameter. The proposed method exhibits a high potential of use in the prediction of monthly average global solar radiation.
Urban Climate, 2019
The primary aim of the present work is to develop a single Global Solar Radiation model applicable to the diversified locations across India. For the development of the global solar radiation models, meteorological data of 15-years are analyzed which were obtained from the Indian Meteorological Department. The performance of the global solar radiation models is tested using different statistical tests and also compared against those available in the literature. Global Performance Indicator is used to rank the established models. For the prediction of monthly average daily global solar radiation for the larger area, the first order Angström-Prescott equation was not found suitable and it was recommended that it should be replaced by higher order relation. Also, the relative humidity, latitude, and altitude were found to be the dominating parameter. The developed model M-03 is found to be applicable for all part of India with a maximum error of −11.8935% whereas the coefficient of determination was found in the range of 0.8454 to 0.9853. Also, the confidence interval (95%) was found to lie between 0.7763 MJ/m 2 to 2.7386 MJ/m 2 .
Journal of Nepal Physical Society, 2020
The accurate knowledge of solar energy potential is essential for agricultural scientists, energy engineers, architects and hydrologists for relevant applications in concerned fields. It is cleanest and freely available renewable energy measured using CMP6 Pyranometer. However, it is quite challenging to acquire accurate solar radiation data in different locations of Nepal because of the high cost of instruments and maintenances. In these circumstances, it is essential to select an appropriate empirical model to predict global solar radiation for the use of future at low land, Nepalgunj (28.102°N, 81.668°E and alt. 165 masl) for the year 2011-2012. In this paper, six different empirical models have been used based on regression technique, provided the meteorological data. The empirical constants (a = 0.61, b = 0.05, c = -0.0012 and d = -0.017) are obtained to predict Global solar radiation. The values of statistical tools such as mean percentage error, mean bias error, root mean squ...
This study aims to evaluate performance of 30 models (15 selected from literature and 15 newly developed) to estimate diffuse horizontal irradiance (H d) using high-quality measurements for nine stations having different climatic conditions. The models (divided into three categories) are based on extraterrestrial global horizontal irradiance (H o) and measured global horizontal irradiance (H g) using sunshine duration ratio, clearness-index, temperature, relative humidity, and periodicity factor as input parameters. The performance of models was evaluated using statistical parameters; the performance of H g based models (Category-II and Category-III) is better than H o based models (Category-I). The performance of newly developed models in three categories is better than best models selected from the literature, due to higher number of input parameters and higher powers used. The best models in Category-I, Category-II and Category-III have rMBE (rRMSE) ranges from − 0.3 to 0.6% (14 to 20%), − 0.6 to 0.1% (10 to 17%) and − 0.3 to 0.0% (10 to 17%) respectively. The performance of models varies in different zones, and different stations within same zone, due to variations of climatic conditions. The best models have rMBE within ±1% and rRMSE < 20%, and can be used for initial resource assessment of commercial solar PV projects for potential locations.
Applied Solar Energy, 2016
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.
Assessment of Empirical Models for Estimating Mean Monthly Global Solar Radiation in Katsina
2019
Solar energy occupies the most significant position among the various renewable energy sources in the world today. Global solar radiation data in various locations across the country is not accessible due to unavailability of the required equipment to measure it. This work sought to estimate the mean monthly global solar radiation in Katsina using different empirical models. Daily data of meteorological parameters obtained from the Nigeria meteorological agency (NiMet) was converted into monthly data and fitted using MATLAB curve fitting toolbox to determine the regression coefficients required to model it. Temperature-based models, sunshine-based models and hybrid parameters-based models were developed, tested and validated using statistical error indicators of mean absolute error, MAE, root mean square error, RMSE, mean percentage error, MPE, coefficient of correlation, R and coefficient of determination, R 2 . The prediction results show that the model with the best performance i...
Analysis Based Estimation of Complete Solar Radiation at Destination Allahabad Uttar Pradesh, India
Consumption after conversion process of Solar Energy at Allahabad, Uttar Pradesh, India longitude 81.846 (81° 50' east), latitude 25.436 (25° 26' north) depends the variation of Direct, Global and Diffuse component of solar radiation throughout the year. The analysis based estimation of diffuse solar radiation quantitatively wise is very high during the rainy season (last days of June, July and August). From the estimated values it is found that, solar energy can be utilized very efficiently throughout the year with the exception of rainy season. In the paper discusses the monthly averages of sun shine hour and monthly variation of entire solar radiation are estimated.