Estimation of clear sky global solar radiation in Algeria

This work aims to create a decision support and geographic information system aimed at optimizing the management of forest capital in the Adrar region. Through this awareness, we question the place of geographic information in the dialogue process and the approach to sustainable development. Cadastral data, satellite images, cartographic and photographic data will be presented. Data processing and data integration will be discussed. The expected results must provide knowledge beyond reach without these tools. They clarify the importance of satellite images and the spatial component of geographic information. In the current context of sustainable development, geographic information appears necessary for decision-making.

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“…The wilaya of Adrar is located in the southwest of Algeria; it extends between the geographic coordinates [8]:…”

Section: Study Sitementioning

confidence: 99%

Realization of a Geographic Information System for aid decision-making for forest management

Benatiallah

Hidaoui

Nasri³

et al. 2020

AJRESD

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“…The final model, constructed using the subtractive clustering approach and refined by ANFIS, exhibited significant improvement over the initial model. Reference [16] developed fifteen ANFIS-based models based on deferent combinations of parameters along with membership functions (T avg ) and (RH), hour angle (HA), along with the Gaussian membership function to estimate GSR models in four sites in Algeria.…”

Section: Introductionmentioning

confidence: 99%

Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

Halima,

Djelloul,

Mehdi

et al. 2024

CMC

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When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the testing phase of Coefficient of Determination (R = 0.9005), Mean Absolute Percentage Error (MAPE = 8.40%), and Relative Root Mean Square Error (rRMSE = 12.56%). Nevertheless, the ANFIS model outperformed the GA-ANN model in forecasting daily GSR, with the best values of indicators when testing the model being R = 0.9374, MAPE = 7.78%, and rRMSE = 10.54%. Generally, we may conclude that the initial ANN stand-alone model performance when forecasting solar radiation has been improved, and the results obtained after injecting the genetic algorithm into the ANN to optimize its weights were satisfactory. The model can be used to forecast daily GSR in dry climates and other climates and may also be helpful in selecting solar energy system installations and sizes.

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“…Measuring stations are rare in all countries; other running costs were incurred through monitoring and maintenance photovoltaic solar station. From this we use several models of solar radiation built in literature to estimate different components of solar radiation [3][4][5][6][7][8][9][10][11][12][13]. These models are constructed in the form of correlation.…”

Section: Introductionmentioning

confidence: 99%

Forecasting of Solar Radiation using an Empirical Model

Benatiallah¹,

Bouchouicha²,

Benatiallah³

et al. 2019

AJRESD

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Global demand for energy is increasing rapidly and natural energy resources such as oil, gas and uranium are declining due to the widespread diffusion and development of the industry in recent years. To cover energy needs, research is being conducted on renewable energy. One of the renewable energies that can meet the world's demand so far is solar energy, which is free and inexhaustible in most parts of the world, and it has become an economic source. In this article we will make a forecast of the empirical Campbell model which will allow us to estimate the daily global irradiation on a horizontal plane and to compare it with the results measured at the Adrar site. The results show that the mean absolute percentage error (MAPE) less than 7%, the mean bias error does not exceed 3% in absolute value, relative RMSE does not exceed 7% and the correlation coefficient greater than 0.99 for the annual global radiation. It was concluded that this model could be used to predict the global solar radiation for Adrar site and for other sites with similar climatic conditions.

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Estimation of clear sky global solar radiation in Algeria

Cited by 10 publications

References 11 publications

Realization of a Geographic Information System for aid decision-making for forest management

Realization of a Geographic Information System for aid decision-making for forest management

Solar Radiation Estimation Based on a New Combined Approach of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) in South Algeria

Forecasting of Solar Radiation using an Empirical Model

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