A new empirical model for forecasting the diffuse solar radiation over Sahara in the Algerian Big South

Bailek, Nadjem; Bouchouicha, Kada; Al-Mostafa, Z. A.; EL-Shimy, M.; Aoun, Nouar; Slimani, Abdeldjalil; Alshehri, Saad M.

doi:10.1016/j.renene.2017.10.081

Cited by 78 publications

(29 citation statements)

References 41 publications

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“…The three datasets of long-term monthly averages for the period 1990 to 1994 for the Bechar site, 2012 to 2014 for the Tamanrasset station and 2010-2015 for Adrar which are representative stations of the Algerian Big South (see Figure 1), with subject to conditions of quality control and unrealistic data as described in (Bailek et al (2018)).…”

Section: Characteristics Of Location Under Study and Its Meteorologicmentioning

confidence: 99%

Developing a new model for predicting global solar radiation on a horizontal surface located in Southwest Region of Algeria

Bailek

Bouchouicha²,

Abdel-Hadi

et al. 2020

NRIAG Journal of Astronomy and Geophysics

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Global solar radiation data is essential in the design of solar energy conversion devices. The most widely used model in the estimation of the global solar radiation coming to the earth's surface is the Angtröm-Prescott model. In this model, relative sunshine duration plays an important role. In the current study, it was attempted to review different models and to determine the best performing model developed for the city of Bechar and two locations of Algerian Big South desert for solar energy projects and compare them with the different established models available in the literature up until now, based on measured sunshine hours data. The new models give high accuracies on the application, where (R 2) ranges between 0.70 and 0.99. In addition, MBE and RMSE values are very low in the studied stations. The results presented in this paper are quite useful for quick estimation of global solar radiation data required for performance evaluation of solar collector used for different applications of solar energy.

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Section: Characteristics Of Location Under Study and Its Meteorologicmentioning

confidence: 99%

Developing a new model for predicting global solar radiation on a horizontal surface located in Southwest Region of Algeria

Bailek

Bouchouicha²,

Abdel-Hadi

et al. 2020

NRIAG Journal of Astronomy and Geophysics

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“…After the data sorting, Energies 2019, 12, 1416 4 of 23 every missing value was replaced with interpolated values by means of various approaches for time series analysis. In addition, this method provides that if there are some missing days or a datum is incorrect, it can be replaced with the means of two nearest non-missing values [39].…”

Section: Data Collectionmentioning

confidence: 99%

Forecasting Daily Solar Radiation Using CEEMDAN Decomposition-Based MARS Model Trained by Crow Search Algorithm

Rezaie-Balf

Maleki²,

Kim

et al. 2019

Energies

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The precise forecasting of daily solar radiation (DSR) is receiving prominent attention among thriving solar energy studies. In this study, three standalone models, including gene expression programing (GEP), multivariate adaptive regression splines (MARS), and self-adaptive MARS (SaMARS), were evaluated to forecast DSR. A SaMARS model was classified as MARS model when using the crow search algorithm (CSA). In addition, to overcome the limitations of the standalone models, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was employed to enhance the accuracy of DSR forecasting. Therefore, three hybrid models including CEEMDAN-GEP, CEEMDAN-MARS, and CEEMDAN-SaMARS were proposed to forecast DSR in Busan and Incheon stations in South Korea. The performance of proposed models were evaluated and affirmed that the accuracy of the CEEMDAN-SaMARS model (NSE = 0.878–0.883) outperformed CEEMDAN-MARS (NSE = 0.819–0.818), CEEMDAN-GEP (NSE = 0.873–0.789), SaMARS (NSE = 0.846–0.769), MARS (NSE = 0.819–0.758), and GEP (NSE = 0.814–0.755) models at both stations. Therefore, it can be concluded that the optimized CEEMDAN-SaMARS model significantly enhanced the accuracy of DSR forecasting compared to that of standalone models.

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“…Concentrated Solar Power (CSP) systems mainly use DNI in its energy capturing and conversion processes due to its directional nature and field of view (aperture angle) that depends on the concentration factor [7]. Therefore, the accurate computation of DHI is of vital importance to design, assess the performance and operate such systems [8].…”

Section: Introductionmentioning

confidence: 99%

Prediction of diffuse horizontal irradiance using a new climate zone model

Abreu

Canhoto

2019

Renewable and Sustainable Energy Reviews

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Knowledge on the diffuse horizontal irradiance (DHI), and direct normal irradiance (DNI) is crucial for the estimation of the irradiance on tilted surfaces, which in turn is critical for photovoltaic (PV) applications and for designing and simulating concentrated solar power (CSP) plants. Since global horizontal irradiance (GHI) is the most commonly measured solar radiation variable, it is advantageous for establishing a suitable method that uses it to compute DHI and DNI. In this way, a new model for predicting the diffuse fraction (K d) based on the climate zone is proposed, using only the clearness index (K t) as the predictor and 1-min resolution GHI data. A review of the literature on models that use hourly and sub-hourly K t values to compute K d was also carried out, and an extensive performance assessment of both the proposed model and the models from the literature was conducted using ten statistical indicators and a global performance index (GPI). A set of model parameters was determined for each climate zone considered in this study (arid, high albedo, temperate and tropical) using 48 worldwide radiometric stations. It was found that the best overall performing model was the model proposed in this work.

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A new empirical model for forecasting the diffuse solar radiation over Sahara in the Algerian Big South

Cited by 78 publications

References 41 publications

Developing a new model for predicting global solar radiation on a horizontal surface located in Southwest Region of Algeria

Developing a new model for predicting global solar radiation on a horizontal surface located in Southwest Region of Algeria

Forecasting Daily Solar Radiation Using CEEMDAN Decomposition-Based MARS Model Trained by Crow Search Algorithm

Prediction of diffuse horizontal irradiance using a new climate zone model

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