Independent models for estimation of daily global solar radiation: A review and a case study

Hassan, Muhammed A.; Khalil, A.; Kaseb, S.; Kassem, Mohamed A.

doi:10.1016/j.rser.2017.07.002

Cited by 45 publications

(13 citation statements)

References 56 publications

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“…Many empirical models have been developed to produce shortwave radiation estimates. In some environments, relatively simple day of year models provide adequate performance [2, 3], using only astronomical and static geographical (latitude, longitude, topography) inputs. For other environments and applications, however, it is necessary to integrate some kind of meteorological predictors to the model, in the form of sunshine-hour or cloud cover data or as direct meteorological inputs of temperature, precipitation, humidity, and/or other relevant atmospheric conditions [4, 5].…”

Section: 0 Introductionmentioning

confidence: 99%

Estimating variability in downwelling surface shortwave radiation in a tropical highland environment

et al. 2019

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Surface incoming shortwave (solar) radiation data are an important component of many scientific analyses, but direct measurements are not commonly available. Estimates can be obtained from gridded meteorological analysis or reanalysis systems, such as the Global Data Assimilation Systems (GDAS) and Modern Era Retrospective Reanalysis System (MERRA-2), or calculated using empirical models dependent on meteorological variables such as air temperature. The purpose of this analysis was to compare multiple methods for estimating daily shortwave radiation in a tropical highland environment in Ethiopia. Direct solar radiation outputs of GDAS and MERRA-2, topographically corrected outputs of the two analysis systems, and empirically estimated solar radiation values calculated with the systems’ air temperature data were compared to see which produced the most reliable radiation values. GDAS appeared to underestimate the seasonal variability, resulting in low correlation (R 2 ) with in situ data and large mean bias error (MBE). In comparison, MERRA-2 did not underestimate variability, but produced larger bias than the empirical model estimates. There was an improvement in correlation and reduction in MBE when using the GDAS air temperature predictions in the empirical model, but the opposite was true for MERRA-2. The empirical model using station air temperature data ( stationT ) produced the highest correlation across all four stations, with best performance at the lower elevation sites. The direct shortwave radiation outputs of MERRA-2 produced comparable correlation values, with larger R 2 at stations at higher elevation. Topography possibly influenced these results, as MERRA-2 performed comparably to stationT at the stations in moderate terrain, but not in steeper terrain. This work can serve as a starting point for analyses in other tropical highland regions, where continuous in situ solar radiation data are rarely available.

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Section: 0 Introductionmentioning

confidence: 99%

Estimating variability in downwelling surface shortwave radiation in a tropical highland environment

et al. 2019

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“…Crossvalidation was utilized to prevent overfitting of the ANN model. During the cross-validation process, the number of folds was varied from 1 to 5, and the closest fold to the mean was taken as the final fold [36,37]. The training is based on the backpropagation technique to set the optimum weights of the feed-forward neural network [38,39].…”

Section: Mrr= Vcmentioning

confidence: 99%

Towards an Adaptive Design of Quality, Productivity and Economic Aspects When Machining AISI 4340 Steel With Wiper Inserts

et al. 2020

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The continuous pursue of sustainable manufacturing is motivating the utilization of new advanced technology, especially for hard to cut materials. In this study, an adaptive approach for optimization of machining process of AISI 4340 using wiper inserts is proposed. This approach is based on advance yet intuitive modeling and optimization techniques. The approach is based on Artificial Neural Network (ANN), Multi-Objective Genetic Algorithm (MOGA), as well as Linear Programming Techniques for Multidimensional Analysis of Preference (LINMAP), for modeling, optimization and multicriteria decision making respectively. This integrated approach, to best of the authors' knowledge, has been deployed for the first time to adaptively serve different designs of manufacturing processes. Such designs have different orientations, namely cost, quality, productivity, and balanced orientation. The capability of the proposed approach to serving such diverse requirements answers one of the most accelerating demands in the manufacturing community due to the dynamics of the uprising smart production lines. Besides, the proposed approach is presented in a straightforward manner that can be extended easily to other design orientations as well as other engineering applications. Based on the proposed design, a balanced general setting of 197.4 m/min, 0.95 mm, and 0.168 mm/rev was recommended along with other settings for more sophisticated requirements. Confirmatory experiments showed a good agreement (i.e., no more than 7% deviation) with the predicted optimum responses. This shows the validity of the proposed approach as a viable tool for designers to promote holistic and sustainable process design. INDEX TERMS Adaptive design, Artificial neural networks, Genetic Algorithm, Modeling, Wiper inserts, Turning, NOMENCLATURE ANN Artificial Neural Network B Balanced design DOC Depth of Cut EC Intensive cost-oriented design EP Intensive productivity-oriented design EQ Intensive quality-oriented design f Feed GRA Gray Relation Analysis IC Intensive cost-oriented design IP Intensive productivity-oriented design IQ Intensive quality-oriented design LINMAP

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“…Thus, the slight improvement of accuracy of the models with complex structure and more number of empirical coefficients is unable to prove the superiority to simple models yet satisfactory accuracy. This has been stressed by several studies [18,179]. Accordingly, it is necessary to explore the optimal trade-off between the accuracy and the complexity, which is mainly depended on the application of the estimation and the data availability.…”

Section: Concludingsmentioning

confidence: 99%

“…It is also crucial for designing solar furnaces [15], concentrating solar collectors [16] and sizing photovoltaic cells [17]. However, measurement of solar radiation is limited by a limited number of observation stations mainly due to the financial and technical limitations [18][19][20]. Lack of sufficient solar radiation data has been reported worldwide [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China

Chen

He²,

Yang

et al. 2019

Renewable and Sustainable Energy Reviews

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Global solar radiation is a core component of scientific research and engineering application across a broad spectrum. However, its measurement is limited by a small number of observation stations due to the technical and financial restricts. Estimating solar radiation with the meteorological variables using empirical models is of benefit to obtain solar radiation data at global scale. Yet, there are various options of available empirical models to select the most suitable one. This study conducted a most comprehensive collection and review of empirical models employing the commonly measured meteorological variables and geographic factors. A total of 294 different types of empirical models were collected and classified into 37 groups according to input attributes. Such collection built an empirical model library providing an overall overview of the developed emperical models in literatures. Furthermore, the collected models were calibrated and evaluated at three meteorological stations in the Three Gorges Reservoir area in China. This study suggests that these model-comparing processes can assist the governments, scientists and engineers in tailoring the most fitted model for specific applications and in particular areas.

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Independent models for estimation of daily global solar radiation: A review and a case study

Cited by 45 publications

References 56 publications

Estimating variability in downwelling surface shortwave radiation in a tropical highland environment

Estimating variability in downwelling surface shortwave radiation in a tropical highland environment

Towards an Adaptive Design of Quality, Productivity and Economic Aspects When Machining AISI 4340 Steel With Wiper Inserts

Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China

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