The Prediction of the Wind Speed and the Solar Irradiation in the Sahel Using the Artificial Neural Networks (Case Study: Site of Nouakchott)

The development of a model for predicting meteorological variables using artificial intelligence was our solution for modeling a wind and solar system, this modeling was carried out in two stages. The first step is to predict the meteorological variable (wind speed, solar irradiation) at the plant level and the second step is to use a generated energy model to convert these wind speed or irradiation forecasts into a forecast of the generated energy by the plant. In this study we modeled the wind speed and the solar irradiation curve of the Nouakchott (case study: 30 MW power plant and 50 MW power plant) using artificial neural networks (ANN). The development of the curve is carried out by carrying out a series of experiments which made it possible to converge towards a methodology offering good precision, using the data measured from the meteorological variable over two years at the level of the Nouakchott site. The evaluation of the meteorological variable forecasting model, by calculating the statistical parameters, made it possible to record a normalized average absolute error between 0.121 and 0.126 and a regression factor R (measures the correlation between output-Target) by 98.4% and 98.5% and the comparison between different existing methods in literature show the goodness of the proposed models.