A comparative study of correlation functions for estimation of monthly mean daily global solar radiation for Jaipur, Rajasthan (India)

Marwal, V. K.; Punia, R.C.; Sengar, Namrata; Mahawar, S.; Dashora, P.

doi:10.17485/ijst/2012/v5i5.8

Cited by 15 publications

(5 citation statements)

References 9 publications

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“…Low values for all statistical error measures are desired [34]. Previous studies propose that percentage errors between -10% and 10% are acceptable [34,35]. Statistical analysis reported in the present study was calculated using the errortypes given by Equations 8-14.…”

Section: Statistical Error Analysismentioning

confidence: 94%

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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: 94%

“…The coefficient of determination (R 2 ), Equation 14, is a measure of the correlation between the dependent variables that are predicted from the independent variables. Low values for all statistical error measures are desired [34]. Previous studies propose that percentage errors between -10% and 10% are acceptable [34,35].…”

Section: Statistical Error Analysismentioning

confidence: 98%

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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“…Marwal V.K. et al [23] used bright sunshine hours duration data for Jaipur and developed six regression equations. They compare these equations based on the following relative measures: regression coefficient, MBE, and RMSE.…”

Section: Empirical Models For Estimating Solar Radiation With Their I...mentioning

confidence: 99%

“…The first step of the method is to generate the value of the sky clearness index (K T ) using a feedforward multilayer perceptron network (FFMLP) with backpropagation learning algorithms by using the input variables latitude, longitude, day number, and sunshine ratio. The 28-weather station recorded data were used for training (23) and testing (5). In the second part of the paper, the generated value of the sky clearness index (K T ) is used to predict global solar radiation and diffuse radiation by the various equations suggested by the authors.…”

Section: Years (2010-2019)mentioning

confidence: 99%

Estimation of Solar Radiation with Consideration of Terrestrial Losses at a Selected Location—A Review

et al. 2023

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The United Nations has set an ambitious goal to achieve net zero carbon emissions by 2050. This objective requires shifting towards green and renewable energy sources instead of conventional fossil fuels to address the global energy crisis without emitting greenhouse gases. While the energy radiated by the sun is one of the most abundant sources of energy available, its efficient and optimal use remains a significant challenge. To facilitate solar-energy-based applications, estimating the amount of solar energy available is crucial. Empirical and soft computing is the most-used method to estimate solar energy. This paper aims to analyze the existing techniques used in various models for estimating and predicting the quantity and quality of solar radiation using readily available data. Additionally, the study aims to identify the most appropriate techniques for developing prediction models using available explanatory variables. To fully harness the potential of solar energy, it is necessary to limit the terrestrial loss of solar radiation by minimizing the harmful effects of anthropogenic factors that reduce the quantity and quality of solar radiation in the area. This paper provides valuable insights to identify opportunities to maximize the potential of solar energy in different locations.

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“…Marwal [25] found that cubic correlation was the best while logarithmic correlation has proved to be worst for Jaipur, Rajasthan (India). They proposed power correlation which showed the values of statistical parameters close to cubic and has a simple form.…”

Section: Models Developedmentioning

confidence: 99%

Comprehensive review on empirical models to estimate global solar radiation on horizontal surfaces

Aggarwal¹

2021

IJAEMS

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In the present scenario of global warming and climate change, use of solar energy is becoming imminent. Researchers are working on developing models to predict global solar radiation based on meteorological and geographical parameters. A number of models have been developed in the past which have been summarized in the present study. The techniques to develop models have also been presented. In the era of global warming, the role of air pollutants in estimating GSR is more important than developing very complex models. Models related to this aspect have also been discussed.

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A comparative study of correlation functions for estimation of monthly mean daily global solar radiation for Jaipur, Rajasthan (India)

Cited by 15 publications

References 9 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 with Consideration of Terrestrial Losses at a Selected Location—A Review

Comprehensive review on empirical models to estimate global solar radiation on horizontal surfaces

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