Correlating clearness index with cloud cover and other meteorological parameters for forecasting the global solar radiation over Morocco

Yakoubi, H.; Mghouchi, Y. El; Abdou, N.; Anas, Hajou; Khellouki, A.

doi:10.1016/j.ijleo.2021.167145

Cited by 14 publications

(5 citation statements)

References 36 publications

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“…The source of the data used is critical to the performance of a model [7] and the more relevant data available, the better the prediction. With regards to data type, some studies pair the solar energy produced from solar panels with either exclusively historically observed data [8][9][10][11][12][13][14][15][16][17][18] or forecast data [19][20][21][22]. Others use only the historical PV output data [23,24].…”

Section: Data Source and Typementioning

confidence: 99%

A Unique Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

Tolulope¹,

Falope²,

Lao³

et al. 2022

Preprint

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Section: Data Source and Typementioning

confidence: 99%

A Unique Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

Tolulope¹,

Falope²,

Lao³

et al. 2022

Preprint

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“…They also proposed the use of probability metrics q 50 , q 95 , and q 99 based on the frequency distribution of global solar radiation to estimate the periods in which photovoltaic systems generate surplus energy. Sengupta et al [30] established that in the first stages of solar projects, extensive information on the solar resource must be available and the origin and period of data collection must be detailed (they worked with 50 global and regional databases with solar radiation information and environmental conditions). Using a statistical approach, they established two criteria to select the appropriate information: the variability that responds to the spatio-temporal differences in the solar resources in the world.…”

Section: Introductionmentioning

confidence: 99%

Continuous Solar Thermal Energy Production Based on Critical Irradiance Levels for Industrial Applications

Martínez-Rodríguez,

Silviano-Mendoza,

Fuentes-Silva

et al. 2024

Energies

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The design of a solar thermal installation is based on the lowest irradiance levels that occur during winter. However, there are consecutive days with irradiance levels well below those used for the design, which are called in this work “critical irradiance levels”. To solve this challenge, a statistical analysis is carried out to find a representative percentile of 22 years of consecutive days with “critical irradiance levels”. A case study of a cotton-dyeing industrial process requires 18.5 m3 of hot water and operates for 2.75 h at temperatures between 40 and 90 °C. Environmental variables for 22 years were analyzed and validated to design a solar thermal installation (solar collector network and storage system) and a coupled heat pump. The fifth percentile, with three consecutive days and low irradiance levels, was the most repetitive. For this case, a storage system of 46.5 m3 guaranteed heat load at target temperature. The simple payback was 14.1 years, and the energy cost was 0.094 USD/kWh, which was competitive against the energy cost from using fossil fuels, 0.064 USD/kWh. The design based on critical environmental conditions guarantees a continuous supply of energy to the industrial process and defines the minimum availability of solar energy to supply a process.

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“…The sunshine-based model was the first to be developed among the four types of models. Later, the model based on average daily temperature (T a ) (Sheik and Rao, 2021), cloud cover (CC) (Yakoubi et al, 2021), and other meteorological parameters was developed to improve accuracy (Naserpour et al, 2021). The input of multiple meteorological parameters improves the prediction accuracy of the model, but at the cost of the model's complexity (Okundamiya and Emagbetere, 2016).…”

Section: Introductionmentioning

confidence: 99%

The applicability of sunshine-based global solar radiation models modified with meteorological factors for different climate zones of China

et al. 2023

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With the development of renewable energy, the exploitation and utilization of solar energy resources also need continuous progress, but solar radiation data shortage has become a serious concern. A method for estimating global solar radiation has been developed to address this issue. The sunshine-based model is currently the most widely used model due to its high calculation accuracy and few input parameters. This paper will first review 13 subcategories (8 categories in total) of the global solar radiation prediction model based on sunshine. Subsequently, the astronomical factors were introduced to modify empirical coefficients, and 8 new categories of models based on sunshine rate were introduced. The radiation data from 83 meteorological stations in China was used to train and validate the model, and the performance of the model was evaluated by using evaluation indicators, such as coefficient of determination (R2), root mean square error (RMSE), mean absolute bias error (MABE), mean bias error (MBE), and global performance index (GPI). The results show that the R2 value of the unmodified empirical model is in a range of 0.82–0.99, and the RMSE value is in a range of 0.018–3.09. In contrast, with the introduction of the astronomical factor, the model accuracy improves significantly, and the modified power function model (N3) gains its best performance. The R2 of model N3 is in a range of 0.86–0.99, and the RMSE value is in a range of 0.018–2.62. The R2 increases by 0.49%, while the RMSE value 6.44%. Above all, it does not require the input of other meteorological parameters for predicting the value of global solar radiation.

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Correlating clearness index with cloud cover and other meteorological parameters for forecasting the global solar radiation over Morocco

Cited by 14 publications

References 36 publications

A Unique Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

A Unique Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

Continuous Solar Thermal Energy Production Based on Critical Irradiance Levels for Industrial Applications

The applicability of sunshine-based global solar radiation models modified with meteorological factors for different climate zones of China

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