Global solar radiation estimation from commonly available meteorological data for Bangladesh

Sarkar, Md. Nazmul Islam; Sifat, Anwarul Islam

doi:10.1186/s40807-016-0027-3

Cited by 18 publications

(12 citation statements)

References 44 publications

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“…Understanding of the accuracy of analysis and proposed models is quantified in terms of the statistical error analysis. The mean bias error (MBE), Equation 8, specifies the average deviance of the calculated values from observed values and is an indicator of a model's long-term performance [12,33]. Positive MBE calculations correspond to an over-estimation, while negative MBEs indicate under-estimation.…”

Section: Statistical Error Analysismentioning

confidence: 99%

Non-linear multivariate models for the estimation of global solar radiation received across five cities in South Africa

Govindasamy

Chetty

2019

J. energy South. Afr.

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South Africa continues to lag globally in the adoption of renewable energy systems despite a notable decrease in the cost of applicable renewable energy technologies over the past five years. Most applications of potential solar renewable energy systems are currently in various stages of investigation, leaving this readily accessible resource capacity idle. The present study proposes linear and non-linear analysis of multivariate models for estimating global solar radiation (GSR) received across five cities in South Africa. The significance of this study is to provide effective GSR estimation in the application of solar technologies, while increasing their implementation. The dependency of GSR on meteorological variables such as air temperature, relative humidity and relative sunshine duration was evaluated for January 2007 to June 2018 to realise estimation models for each of the study sites. The Hargreaves-Samani and Angstrom-Prescott empirical models served as the basis for single variable analysis of GSR reliance on each meteorological parameter and their relative variations. The results indicated that the proposed non-linear, multivariate equations perform better than the empirical models as well as linear, single variable regression equations. The suggested models are site-specific and demonstrate a strong correlation to historic GSR values with low, acceptable error indicators. It was also recognised that second-and third-order relationships between the clearness index and multiple meteorological variables provide a more accurate description of GSR for most of the cities under study. These methods are cost-effective, easily accessible and appropriate for the evaluation of the feasibility of solar photovoltaic technologies in South Africa.

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Section: Statistical Error Analysismentioning

confidence: 99%

Non-linear multivariate models for the estimation of global solar radiation received across five cities in South Africa

Govindasamy

Chetty

2019

J. energy South. Afr.

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“…Se ha utilizado la raíz cuadrada del cuadrado medio del H A(T ) 0.5 H o (6) error (RMSE), el error medio (MBE), llamado también sesgo o desviación, coeficiente de determinación ( R 2 ) y el Modelo 4, Sarkar y Sifat [22] se basa en la reg res ió n cuadrática para estimar la radiación solar global a partir de la diferencial de temperatura máxima y mínima está directamente relacionado con la fracción de radiación extraterrestre recibida a nivel del suelo. La relación viene dada por ecuación (7).…”

Section: E Estadísticos De Evaluaciónunclassified

“…[21] presentan métodos para estimar la radiación solar a partir de la diferencia entre la temperaturas máximas y mínimas, porcentaje de posible insolación y de la humedad relativa. [22] plantea modelos basados en regresió n para estimar la radiación solar global, para 34 estaciones meteorológicas que están proporcionando radiación solar. [23] desarrollara modelos para predecir la radiación solar glob al diario para lugares donde existe un enorme potencial de radiación, planteando modelos exponenciales, modelos exponenciales modificados, modelos de series de potencia dependientes de la diferencia de temperaturas extremas del aire del lugar.…”

Section: Introductionunclassified

Estimation of solar radiation by model dependent on extreme temperatures for the region of Puno, Peru

Huaman¹,

Mamani²,

Ramos³

et al. 2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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The objective of this research was to identify a model to estimate solar radiation for the Puno region based on extreme temperatures. For which seven models have been considered to estimate global solar radiation, to make the adjustments of the models, d a ta from the 2016-2018 period of the DAVIS meteorological station for the city of Puno were considered, where the coefficients of the models were adjusted considering 1097 data. To choose the appropriate model, the correlation coefficient between measured and estim a ted so la r radiation data was used. Then, the data measured by SENAMHI for the thirteen provinces of the Puno region have been considered. Concluding, it was possible to identify two models to estimate solar radiation in the Puno region, considering as input variable the difference in extreme temperatures and the latitude of the place, a correlation coefficient of 0.855 was obtained for the measured and estimated solar radiation data. . . . For the estimation of solar radiation in the Puno region, the data on extreme temperatures from SENAMHI for the thirteen provinces have been considered, reaching estimates of solar radiation through the regression model of order four.

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“…Meteorological information such as the surrounding clearness index, relative humidity, air temperature, sunshine duration, wind speed, clearness index are generally utilized parameters for the deduction of sun-powered vitality at numerous places in the world. Several solar energy models using weather data such as humidity [23], snow conditions [24], ambient temperature [25] cloudiness [26], sunshine duration [27,28] have been established in the beginning of the quantification of solar energy around various places the world. Recently, several regression models to determine the horizontal global solar radiation on a plane surface as a function of sunshine duration have been made [10,[29][30][31][32].…”

Section: Solar Radiation Datamentioning

confidence: 99%

Empirical models for estimating the global solar radiation of Jubail Industrial City, the Kingdom of Saudi Arabia

Mujabar

Venkateswara

2021

SN Appl. Sci.

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Empirical models provide precise and cost-effective information on solar energy assessment. The main objective of this work is to create and examine some regression models (linear, quadratic and logarithmic), for the estimation of the monthly global solar radiation potential in the Jubail Industrial City of Saudi Arabia. The industrial city has more solar energy potential, and the global horizontal irradiance is ranging from 4000 to 7000 Wh/m2/day. In order to initiate the green energy development in the city, site-specific hybrid models, which includes the ambient temperature, sunshine hours and relative humidity have been developed. Precise equation for the three proposed models is built up and examined for the industrial city. All the three empirical models provide good results. The statistical error estimation of the developed models reveals that the estimated and measured values appear exceptionally great and deliver similar outcomes. The values of the correlation coefficient and coefficient of determination of the quadratic model are 0.939 and 0.925, respectively, which are the highest among the three models. The mean absolute percentage error of the quadratic model is only 6.17%, and the other statistical errors are also comparatively low for the quadratic model. Therefore, the quadratic model gives an improved approximation on the estimation of solar energy parameters in which the errors between the measured and calculated values are smaller. Thus, the present regression models provide valuable data on the solar strength probable in the industrial city, and the data could be used for future energy planning.

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Global solar radiation estimation from commonly available meteorological data for Bangladesh

Cited by 18 publications

References 44 publications

Non-linear multivariate models for the estimation of global solar radiation received across five cities in South Africa

Non-linear multivariate models for the estimation of global solar radiation received across five cities in South Africa

Estimation of solar radiation by model dependent on extreme temperatures for the region of Puno, Peru

Empirical models for estimating the global solar radiation of Jubail Industrial City, the Kingdom of Saudi Arabia

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