Exploring Global Solar Radiation: Enhancing Ground-Level Solar Radiation Prediction using Hottel's Semi-Empirical Model and Sunshine Duration Analysis (original) (raw)
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Advances in Science, Technology and Engineering Systems Journal, 2022
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Comparative Study of Solar Radiation Models for the Estimation of Solar Radiation Using Short-Term Meteorological Data in Lawra, Ghana, 2022
Monthly average daily global solar radiation data are essential for the design and study of solar energy systems. The performance and accuracy of eleven models for the estimation of monthly average global solar radiation were compared in this study. Nineteen months (Nov 2020 – May 2022) ground measurement data consisting of monthly mean daily sunshine duration, relative humidity, minimum and maximum temperatures, and global solar radiation collected from the Lawra Solar Plant were used. The models were compared using statistical indices. According to the indices, most of the models were in reasonably good agreement with the measured data. Two model equations, however, were found to have the highest accuracy and can thus be used to estimate monthly average global solar radiation in Lawra and other places with similar climatic conditions where radiation data is unavailable.
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Transactions in Gis, 2004
The solar radiation model r.sun is a flexible and efficient tool for the estimation of solar radiation for clear-sky and overcast atmospheric conditions. In contrast to other models, r.sun considers all relevant input parameters as spatially distributed entities to enable computations for large areas with complex terrain. Conceptually the model is based on equations published in the European Solar Radiation Atlas (ESRA). The r.sun model was applied to estimate the solar potential for photovoltaic systems in Central and Eastern Europe. The overcast radiation was computed from clear-sky values and a clear-sky index. The raster map of the clear-sky index was computed using a multivariate interpolation method to account for terrain effects, with interpolation parameters optimized using a cross-validation technique. The incorporation of terrain data improved the radiation estimates in terms of the model's predictive error and the spatial pattern of the model outputs. Comparing the results of r.sun with the ESRA database demonstrates that integration of the solar radiation model and the spatial interpolation tools in a GIS can be especially helpful for data at higher resolutions and in regions with a lack of ground measurements.
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Energy Sources, Part B: Economics, Planning, and Policy, 2006
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Renewable & Sustainable Energy Reviews, 2015
For the optimal design and selection of solar energy conversion systems, as well as for other fields of interest, such as architecture, agriculture, hydrology and ecology, the knowledge of accurate global solar radiation data is extremely important. However, due to the cost and difficulty in solar radiation measurements these data are not easily available for many countries. Therefore many empirical models have been developed by various researchers to predict global solar radiation from readily available data. The number of developed models is relatively high, which makes it difficult to choose the most appropriate one for a particular purpose and site. There are several studies in which authors evaluate different models for specific location. However, there is no comprehensive study in which these models are evaluated in case of global use. The main objective of this study is to evaluate different solar radiation models on global scale, which might be helpful in the selection of the most appropriate and accurate model based on the available sunshine data. Using the radiation data corresponding to 924 sites throughout the world we conducted a detailed statistical analysis of 101 different solar radiation models that are available in literature. Ten statistical indicators were used to assess models performance. In addition, we introduced specific global performance indicator (GPI), by means of which all analyzed models are depicted with a single parameter and easily ranked.
Solar Energy is the cleanest and the most abundant renewable energy in the world. Solar radiation data are the most important resources needed for solar energy system design. Knowledge of the amount of available solar radiation in any location of interest is of prime importance to the solar energy design experts. This study examines the influence of atmospheric components on solar radiation passing through the earth’s atmosphere. The intensity of solar radiation is attenuated as it passes through the earth’s atmosphere. Also, methods of solar radiation measurement and the various empirical models for estimating global solar radiation in areas where such data are not available are presented. However, no method can be acclaimed to be the best as the performance of the models vary with location. Hybrid parameter based models have been reported to predict global solar radiation on horizontal surface with a high degree of accuracy in many locations in across the globe. Finally, two simulation tools for analysing solar power system were discussed. RETScreen software is majorly used for photovoltaic applications while HOMER includes additional renewable energy simulation features which make it suitable for analysing hybrid power system.
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