Observation and calculation of the solar radiation on the Tibetan Plateau

Liu, Jiandong; Liu, Jingmiao; Linderholm, Hans W.; Chen, Deliang; Yu, Qiang; Wu, Dingrong; Haginoya, Shigenori

doi:10.1016/j.enconman.2011.12.007

Cited by 74 publications

(50 citation statements)

References 35 publications

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“…The systematic deviations of estimates of the southern area (Benin City) for the months March and August, especially, perhaps is as a result of seasonal change (onset and peak of the rainy season, respectively). Moreover, vapor is one of the most important meteorological factors seriously influencing the transmission of solar radiation (Liu et al 2012). The relative percentage error for each month produced by Equation (6) rarely exceeds ± 10%, but Equations (1)-(5) fall within ± 20% except for the southern region where Equations (4) and (5) give significant underestimation.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of various global solar radiation models for Nigeria

Okundamiya

Emagbetere

Ogujor

2015

International Journal of Green Energy

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This study assessed the performance of six solar radiation models. The objective was to determine the most accurate model for estimating global solar radiation on a horizontal surface in Nigeria. Twenty-two years meteorological data sets collected from the Nigerian Meteorological agency and the National Aeronautics and Space Administration for the three regions, covering the entire climatic zones in Nigeria were utilized for calibrating and validating the selected models for Nigeria. The accuracy and applicability of various models were determined for three locations (Abuja, Benin City, and Sokoto), which spread across Nigeria using seven viable statistical indices. This study found that the estimation results of considered models are statistically significant at the 95% confidence level, but their accuracy varies from one location to another. However, the multivariable regression relationship deduced in terms of sunshine ratio, air temperature ratio, maximum air temperature, and cloudiness performs better than other relationships. The multivariable relationship has the least root mean square error and mean absolute bias error, not exceeding 1.0854 and 0.8160 MJ m −2 day −1 , respectively, and monthly relative percentage error in the range of ± 12% for the study areas.

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Section: Resultsmentioning

confidence: 99%

Evaluation of various global solar radiation models for Nigeria

Okundamiya

Emagbetere

Ogujor

2015

International Journal of Green Energy

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“…According to Podestá et al [13], the A-P model, explaining 96-97% of the Rs variability with RMSE of 1.5 MJ m À2 d À1 , outperformed the temperature based models explaining 79-86% of the Rs variability with RMSE of 3.2 MJ m À2 d À1 . The better performance of the A-P formula was also implied in Liu et al [14], Zhou et al [15] and Chen et al [16] using data from China. Although the empiricism of the A-P model is sometimes criticized [17] by modelers of the complex atmospheric transfer models, the simplicity, lower computational cost and easily accessible input data make it more attractive in applications and it is undoubtedly one of the most widely used models worldwide.…”

Section: Introductionmentioning

confidence: 53%

“…For example, they are calculated as function of n=N [28], of Z and n=N [29], of u, Z and n=N [30]. They are also treated as a cubic [39] of and a four-order function of n=N [40] this belief that complex models are continued to be proposed, evaluated and recommended [14,22,37]. However, it should be cautious to recommend a complex model in the absence of information on t-statistic [32], since a slightly better Rs estimates does not mean a significant improvement over a simple one.…”

Section: Models Of Amentioning

confidence: 98%

Towards increasing availability of the Ångström–Prescott radiation parameters across China: Spatial trend and modeling

Zhong

Zhao

et al. 2014

Energy Conversion and Management

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“…2, that the measured solar radiation values are proportional to the observed average temperatures, throughout the year. Previous studies have considered similar linear equations to predict solar radiation, for example, the classical Angstrom model (Angstrom, 1924) that assumes that the magnitude of solar radiation is proportional to sunshine (Angstrom, 1924;Meza, 2000;Liu, 2012;and Yakubu, 2012).…”

Section: Air Temperature Based Modelsmentioning

confidence: 99%

“…Most temperature-based models in the literature (Meza, 2000;Liu, 2012) assume that solar radiation is a function of the difference between daily maximum and minimum air temperature. This is based on the assumption that the difference generally indicates daily cloudiness.…”

Section: Air Temperature Based Modelsmentioning

confidence: 99%

Models for Calculating Monthly Average Solar Radiation from Air Temperature in Swaziland

Dlamini¹,

Varkey²,

Mkhonta³

2017

Preprint

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Solar radiation is the main energy source for mankind and an accurate data of solar radiation levels for a particular location is vital for the optimum operation of solar energy transducers such as photovoltaic cells and solar thermal collectors. In this work, we show that there is a linear relationship between recorded monthly average temperatures and solar radiation in Swaziland. The correlation can be utilized to develop two mathematical models for the estimation of solar radiation: one from the measured monthly average temperatures and the other based on the square-root of the difference between measured maximum and minimum monthly average temperatures. Both models fit the data well and can be applied to estimate solar radiation in other parts of the region Keywords: solar energy; solar radiation; climatic data; solar radiation estimation. INTRODUCTIONAn accurate knowledge of solar radiation levels for a particular location is a prerequisite in the determination of the performance of various solar energy transducers such as photovoltaic cells and solar thermal collectors. Solar radiation data is also important in disciplines such as building designs and agricultural processes, e.g. evapo-transpiration of plants. However, weather stations will, at times, not have data on solar radiation because the instruments for radiation measurement, such as pyrometers and solarimeters, may not be available. As a result, mathematical models have been developed and calibrated to estimate solar radiation in different parts of the world such as in Brazil (Dos Santos, 2014), Iran (Saffaripour, 2013), India (Bajpai, 2009), Algeria/Spain (Chegaar,1998), China (Li, 2014a; 2014b), Bangladesh (Datta, 2013), Chile (Meza, 2000), USA (Allen, 1997) and Nigeria (Umoh, 2013). These models estimate solar radiation as a function of meteorological parameters such as temperature, atmospheric pressure, relative humidity, the number of sunshine hours, wind speed, cloud cover, and rainfall.

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Observation and calculation of the solar radiation on the Tibetan Plateau

Cited by 74 publications

References 35 publications

Evaluation of various global solar radiation models for Nigeria

Evaluation of various global solar radiation models for Nigeria

Towards increasing availability of the Ångström–Prescott radiation parameters across China: Spatial trend and modeling

Models for Calculating Monthly Average Solar Radiation from Air Temperature in Swaziland

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