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In order to describe the behavior and the performance of the photovoltaic modules we can found in the literature different equivalent circuit models such us: single diode model (SDM), double diode model (DDM), three diode model (TDM). Almost of the authors obtained that the SDM is the best solution to describe the electrical characterization of the PV modules. The PV parameters can be extracted by three common approaches: Analytical based on the derivation of mathematical equations, Numeric or iterative usually use non-linear optimization techniques, among all the technique the Newton Raphson is widely used. The last one is meta-heuristic approach characterized by their global search point and their soft computing algorithms. The aim of this study is to explore and discuss the behavior of the single-diode model, which require five parameters are estimated using Particle Swarm Optimization approach. The performance of this method is evaluated using the experimental values of R.T.C France PV cell at irradiation G = 1000 W/m2 and at temperature T = 33 °C. The obtained results are also compared with results of the others computing approach. After this study, we can conclude that the proposed PSO method has the best performance because the RMSE obtained using this approach is around the 1.73.10−4 A and low than those obtained through all compared algorithms.

The degradation cost of air pollution is estimated to be 1.62 percent of Morocco's Gross Domestic Product. Several studies focused on the high-resolution spatial modeling effect. As a result, in this study, we investigated the CHIMERE model performances in Agadir city using two resolutions, C1(0.1°=11 km) and C3 (0.02°=2 km). The numerical results are compared to ozone monitoring data for spring/summer 2010. The results show that the statistical performance improves for the C3, which improves the model's ozone forecasting. Given the seasonal performance differences, future efforts should concentrate on upgrading the quality of input data to provide more accurate information.

A greater understanding of ozone damage to the environment and health led to an increased demand for accurate predictions. This study provides two new accurate hybrid models of ozone prediction. The first one (CHIMERE-NARX) is based on a NARX model as a post-processing of the CHIMERE model. In the second (CHIMERE-NARX-DWT), a discrete wavelet transform (DWT) has been added. Our models were built and validated using ozone measurements from the Mediouna station in Casablanca, Morocco, from February 1

Ozone concentration generally affects a health system, including human health, and an ecosystem, including plant properties and soil processes. Based on high-performance computing, this study used the transport chemistry model CHIMERE to model ozone pollution in the city of Agadir. The aim is to investigate the integrating horizontal and vertical transport effect on ozone concentration and computation time. The findings are validated experimentally by measurements and also compared with other studies. The results highlighted four main points: First, the CHIMERE ozone modeling remains acceptable with a correlation coefficient of 70%. Second, the combination Adv00 based on the Upwind method gives good results in terms of ozone concentration with a significant implementation time, equivalent to 80 minutes for 360 hours of prediction, which means an optimization in computational performance. Third, it is required to optimize all possible parts of the modeling process to reduce costs and time. Fourth, detailed local emission information is recommended to get a clearer picture of the correction of the CHIMERE output. The present work can serve as guidance for the CHIMERE settings in the case of limited computational infrastructure for long-term studies and studies using a high spatial resolution to predict polluted air.