scholarly journals A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Huashan Li ◽  
Fei Cao ◽  
Xianlong Wang ◽  
Weibin Ma
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Statistical Error ◽  
Global Solar Radiation ◽  
Measured Data ◽  
Temperature Data ◽  
New Model ◽  
Climatic Regions ◽  
Monthly Average ◽  
Temperature Records

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China.

scholarly journals Comparative Analysis of Global Solar Radiation Models in Different Regions of China

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Qingwen Zhang ◽  
Ningbo Cui ◽  
Yu Feng ◽  
Yue Jia ◽  
Zhuo Li ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Regional Climate ◽  
Global Solar Radiation ◽  
Specific Region ◽  
Temperature Data ◽  
Monthly Average ◽  
Climate Assessment ◽  
Crop Growth Modeling

Complete and accurate global solar radiation (Rs) data at a specific region are crucial for regional climate assessment and crop growth modeling. The objective of this paper was to evaluate the capability of 12 solar radiation models based on meteorological data obtained from 21 meteorological stations in China. The results showed that the estimated and measured daily Rs had statistically significant correlations (P<0.01) for all the 12 models in 7 subzones of China. The Bahel model showed the best performance for daily Rs estimation among the sunshine-based models, with average R2 of 0.910, average RMSE of 2.306 MJ m−2 d−1, average RRMSE of 17.3%, average MAE of 1.724 MJ m−2 d−1, and average NS of 0.895, respectively. The Bristow-Campbell (BC) model showed the best performance among the temperature-based models, with average R2 of 0.710, average RMSE of 3.952 MJ m−2 d−1, average RRMSE of 29.5%, average MAE of 2.958 MJ m−2 d−1, and average NS of 0.696, respectively. On monthly scale, Ögelman model showed the best performance among the sunshine-based models, with average RE of 5.66%. The BC model showed the best performance among the temperature-based models, with average RE of 8.26%. Generally, the sunshine-based models were more accurate than the temperature-based models. Overall, the Bahel model is recommended to estimate daily Rs, Ögelman model is recommended to estimate monthly average daily Rs in China when the sunshine duration is available, and the BC model is recommended to estimate both daily Rs and monthly average daily Rs when only temperature data are available.

scholarly journals Daily global solar radiation estimation based on air temperature: case of study south of Algeria

2019 ◽  
Vol 80 ◽  
pp. 01002
Author(s):  
Razika Ihaddadene ◽  
Nabila Ihaddadene ◽  
Mohamed El Hacen Ould Ahmedou Bemba Jed ◽  
Amaury De Souza
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
The Other ◽  
Extreme Temperatures ◽  
Statistical Parameters ◽  
New Model ◽  
Air Temperatures ◽  
Solar Conversion

Global solar radiation is needed for the analysis and scaling of solar conversion systems; however, global measurements of solar radiation are not available in all Algerian cities. The use of empirical models using an accessible parameter is a solution to this problem. In this study, seven empirical Models namely Hargreaves and Samani, Chen, M.F. Li, H.Li, Bristow and Campbell, Okonkwo and Abraha Savage have been employed to estimate daily average global solar radiation on the horizontal surface. These models use extreme temperatures (minimum and maximum). They were applied to three south Algerian sites (Biskra, Ghardaia, and Tamanrasset). The analyzed data were provided by the NASA site and cover four years (2001-2004). The validation of the models for predicting daily global solar radiation was done using four statistical parameters (R2, MBE, RMSE, and RPE). The results show that Bristow and Compbell Model shows better performance than the other models in all sites. A new model is proposed for each site. The results show that this later is the best one compared with the seven models analyzed. Therefore, the developed model can be suggested to estimate daily global solar radiation using only extreme air temperatures in south Algeria.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

scholarly journals Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Boluwaji M. Olomiyesan ◽  
Onyedi D. Oyedum
Keyword(s):  
Solar Radiation ◽  
Comparative Study ◽  
Global Radiation ◽  
Statistical Error ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Radiation Data ◽  
Proposed Model

In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years (1984–2005) of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET) Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA) for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE), mean percentage error (MPE), root mean square error (RMSE), and coefficient of determination (R2). Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano) and highest coefficient of determination, R2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

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