Ecole Supérieure de Technologie de Safi

In general, agriculture plays a crucial role in human survival as a primary source of food, alongside other sources such as fishing. Unfortunately, global warming and other environmental issues, particularly in less privileged nations, hamper the Agricultural sector. It is estimated that a range of 720 to 811 million individuals experienced food insecurity. Today's agriculture faced significant difficulties and obstacles, as do the surveillance and monitoring systems (climate, energy, water, fields, works, cost, fertilizers, diseases, etc.). The COVID-19 pandemic has exacerbated the susceptibilities and insufficiencies inherent in worldwide food systems. Current agricultural practices tend to prioritize productivity and profitability over environmental conservation and long-term sustainability. To establish sustainable agriculture capable of meeting the needs of a projected ten billion people in the next 30 years, substantial structural and automation changes are required. However, these obstacles can be overcome by employing smart technologies and advancing Artificial Intelligence (AI) in agricultural operations. AI is believed to contribute to global sustainability goals in multiple sectors, particularly in the incorporation of renewable energy. It is anticipated that AI will revitalize both existing and new agricultural fields by retrofitting, installing and integrating automatic devices and instruments. This paper presents a comprehensive review of the most promising and novel applications of AI in the agriculture industry. Furthermore, the role of AI in the transition to sustainability and precision agriculture is investigated.

Titanium dioxide was synthesized by the sol–gel method and titanium pillared purified clay was prepared with two titanium contents: 1.15 and 10.5 mmol of Ti per gram of clay. The composites were synthesized by immobilizing TiO2 onto surfactant-pillared clay via ion exchange reaction between clay with cation surfactant, cetyl-trimethyl ammonium bromide (CTMABr). The composition and texture of the prepared photocatalysts were characterized with X-ray powder diffraction (XRD), FT-IR spectroscopy, transmission electron microscopy (TEM) and energy-dispersive spectroscopy (EDX). The adsorption performance and photocatalytic activities of the prepared samples were investigated using 2,4-dichlorophenoxyacetic acid (2,4-D) and 2,4-dichlorophenoxypropionic acid (2,4-DP) as models of organic pollutants. The results were obtained that these photocatalysts can effectively degrade selected pesticides. The removal efficiency increases with the Ti content in the pillared clay.

Coupling energy and transport sectors is critical for optimum utilization of renewable energy. The present work proposes a grid-connected photovoltaic/wind/battery hybrid power system to generate electricity for supermarkets. The supermarkets are located at three geographically distinct cities in Morocco and integrate electric vehicle (EV) charging stations in their parking areas. HOMER grid software is used for the optimal design of the proposed hybrid renewable energy system (HRES) with an accurate utility tariff corresponding to the Moroccan scenario. Dakhla, which is a high windy site, is found to be the best implementation site with maximum renewable energy fraction (REF), minimum COE and operating costs of 71.66%, 0.0841 $/kWh, and 0.124 M$/year, respectively. The optimal grid-connected system consisted of 107 kW p of PV, 300 kW of wind, 12 batteries, and 65 kW capacity inverter for Dakhla site. The next identified best site is Casablanca while Fez remained at third place based on COE and annual operating costs. At all of these sites, the EV charging process is achieved, almost completely, with 7300 charging sessions annually. A series of sensitivity analyses is performed based on supermarket energy intensity, renewable energy availability, and carbon pricing and impact on the viability of HRES was evidenced.

This paper presents an annual performance evaluation of three maximum power point tracking (MPPT) methods. The used MPPT techniques (Perturb and Observe, Incremental Inductance and Sliding mode) are evaluated under an annual data of atmospheric conditions of the target site. The main contribution of this work is to consider real fluctuation conditions of solar irradiations, ambient temperatures and wind velocities. It was found that the Sliding mode provides higher energy yields independently of the period. Compared to the basic P&O and the IC techniques, sliding mode has the potential of generating up to 8.18% more electrical energy than other techniques.

The use of hybrid renewable energy systems is growing as a viable option for clean power generation, fueled by the increasing demand for sustainable energy sources and the need to reduce carbon emissions. In this context, this paper evaluates the optimal configuration, as well as the economic and environmental performances of a hybrid solar PV/biogas/battery energy system designed to provide electricity to a commercial platform in Berkane- Morocco. The optimization model aims to determine the optimal capacity of renewable energy systems achieving the most cost-effective levelized cost of electricity, reducing greenhouse gas emissions, and utilizing locally available renewable energy resources. The model was developed using HOMER software incorporating real-measured data for electricity demand, solar irradiance, and biogas availability. It was found that the PV/biogas/battery combination is very optimal in terms of cost and emissions savings in comparison with the use of only one source of power generation. The optimal design of the energy system results in 231 kW of PV modules, 170 kW biogas generator, a 140-kW converter, and a 201 kWh Li-Ion battery park. The optimization results in an LCOE of 0.280 $/kWh; Moreover, the proposed system would save almost 40% of carbon dioxide (CO2) emissions in comparison with only biogas system. A sensitivity test has been performed, showing that the proposed hybrid system is sensitive to capital subsidies and discount rates. This study demonstrates the economic viability and environmental benefits driven by the integration of the hybrid of PV/Biogas/Battery system in Morocco, making it an attractive alternative for future sustainable development.

Protected crop production is rapidly expanding in the Mediterranean Basin, and particularly in Morocco. Increased local and overseas demand for these products led to a rapid development in greenhouse usage encouraged by government policies. The aim of this study is to investigate key design parameters that affect the thermal behavior and the heating/cooling energy need of a greenhouse situated in Agadir (Morocco). The parameters include the cladding material characteristics, shape, orientation, and air change rate. The greenhouse is modeled by a developed thermal model using TRNSYS software. The model considers the presence of the plants inside the greenhouse by adding the heat and humidity gain into the heat and water balance of the greenhouse using an evapotranspiration sub-model. The effect of evapotranspiration on the greenhouse thermal behavior was also examined in this study. A validation of the current TRNSYS simulation and evapotranspiration model was made using previous studies from the literature, and the comparison showed fair agreement. The relative error of the annually heating demand obtained by this model is 1.66%, and the evapotranspiration model used in this study shows relative deviation less than 6.5%. The results of this study indicate that the East-West greenhouse orientation is the optimum orientation as it can reduce the annual cost of air-conditioning of the greenhouse by 9.28% compared to North-South orientation. Quonset shape is the optimum greenhouse shape in Morocco as it can save 14.44% of annual cost of air-conditioning instead of the Even-span shape.

A two-dimensional numerical simulation of the melting process in a rectangular enclosure for different inclination angles, has been carried out. Galium as a phase change material (PCM) with low Prandtl number is used. A numerical code is developed using an unstructured mesh, finite-volume method and an enthalpy porosity technique to solve for natural convection coupled to solid–liquid phase change. The validity of the numerical code used is ascertained by comparing our results with previously published results. The effect of the inclination angle on the flow structure and heat transfer characteristics is investigated in detail. It is found that the melting rate inside the rectangular cavity increases by decreasing the inclination angle from 90° to 0°.

Access to clean and affordable energy in rural African regions can contribute greatly to social development. Hence, this article proposes the design, simulation, and optimization of a stand-alone photovoltaic system (SAPV) to provide non-polluting electrical energy based on a renewable source for a rural house located in Tazouta, Morocco. Real monthly electrical demands and hourly climatic conditions were utilized. An initial design process indicated that, with a 1080 Wp total capacity of PV modules and 670 Ah of battery storage, the proposed SAPV system was able to meet a considerable part of the dwelling load with an average solar fraction of about 79.1%. The rest of the energy demand was ensured by a diesel generator (DG). Also, a life cycle analysis of the PV system revealed that the life cycle cost is 10,195.56 USD and the unit electricity cost is 0.57 USD/kWh for an initial investment of 4858.68 USD. Thereafter, an optimum design based on Homer Pro software was carried out indicating that lower PV capacity can decrease the unit energy cost to 0.356 USD/kWh while reducing the solar fraction to 54.9%.

Full factorial experimental design technique was used to study the main effects and the interaction effects between operational parameters in the photocatalytic degradation of oxalic acid in a batch photo-reactor using TiO2 aqueous suspension. The important parameters which affect the removal efficiency of oxalic acid such as agitation, initial concentration, volume of the solution and TiO2 dosage were investigated. The parameters were coded as X1, X2, X3 and X4, consecutively, and were investigated at two levels (−1 and +1). The effects of individual variables and their interaction effects for dependent variables, namely, photocatalytic degradation efficiency (%) were determined. From the statistical analysis, the most effective parameters in the photocatalytic degradation efficiency were initial concentration and volume of solution. The interaction between initial concentration, volume of solution and TiO2 dosage was the most influencing interaction. However, the interaction between agitation, initial concentration and volume of solution was the least influencing parameter.

Historically, the development and design of distribution systems (DSs) and microgrids (MGs) were based primarily on alternating current (AC) as a traditional approach due to many advantages such as eliminating the need for synchronization, as well as the ease of integrating distributed energy resources (DERs). Recently, given the democratization of DER through local installations of renewable energy systems and appliances using power electronics, direct current microgrids (DC-MGs) are gaining more and more momentum. In order to enable durable and economically viable use by integrating DC and AC DERs into microgrids, hybrid AC/DC microgrids (HMGs-AC/DC) present one of the most promising approaches in eliminating the need for AC-DC or DC-AC conversions. The improvement of energy efficiency, protection, management, and control of this kind of systems are relevant research topics. This article provides an overview of theoretical works and industrial applications of hybrid AC/DC microgrids/distribution systems. In addition, an efficiency/energy-losses study of different literature-based works is discussed. Accordingly, a critical analysis is provided, and research perspectives related to this subject are outlined. This review article can be considered as a guide for future research on the efficiency and energy losses of hybrid AC/DC distribution systems/microgrids.

Middle East and North Africa region's abundant solar and wind resources provide a valuable opportunity to diversify energy production and offer a high potential for renewable energies. Thus, the solar water heating systems offer a key element in the deployment of renewable energy throughout the region. To this end, a model was developed and validated to evaluate the performance of these systems with different collectors. Then, an exhaustive energetic, exergetic, environmental and economic analysis of all the region's countries was carried out on the basis of the required meteorological data. Regarding the results for the entire region, the maximum solar fraction values attain 60 % and 83 % for the flat plate and evacuated tube systems, respectively. Under current economic assumptions, propane water heating is cheaper on a life cycle cost basis than electric and diesel heating throughout North Africa. Also, the use of auxiliary electric generators is suitable for all countries in the Middle East region except for Manama-Jordan, Abu Dhabi-UAE and Ankara-Turkey.

The objective of this paper is to assess the potential of machine learning algorithms in predicting the indoor air temperature in a greenhouse using the outdoor data. A dataset gathering the main weather data and the indoor air temperature of a greenhouse located in Agadir, Morocco was used for this purpose. Machine learning models including support vector machine based-regression, ensemble trees and Gaussian process regression are compared against multiple linear regression models. This comparison was carried out on the basis of a 5-fold cross validation framework and across unseen data. The results show that all predictive models are capable of describing the indoor air temperature of the greenhouse and perform well (R2 > 0.9), with only 10% fraction of the dataset as training data. The Gaussian process regression outperforms all models, with R2 = 0.94 in the 5-fold cross validation test. However, the computational time related to the training of Gaussian process regression model is slightly higher than other machine learning models.

The presented data are related to the article "Solar Irradiance and Temperature Influence on the Photovoltaic Cell Equivalent-Circuit Models" (Chaibi et al., 2019). Data include the open-circuit voltage, the short-circuit current and the output power of the Shell SM55 mono-crystalline Photovoltaic (PV) Solar Module obtained from a PV panel modelling based on the single-diode and the double-diode circuit models, coupled with Chaibi and Ishaque parameter extraction techniques (Chaibi et al., 2018, Ishaque et al., 2011). The I-V curves as simulation results are provided at various levels of solar irradiance and temperature.

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A physical model to investigate the melting process around a multiple of heating cylinders in the presence of the natural convection has been carried out. A numerical code is developed using an unstructured finite-volume method and an enthalpy porosity technique to solve for natural convection coupled to solid-liquid phase change. It is found that during the melting process around the cylinders, natural convection circulation around each cylinder interacts with the other cylinders to influence the melt shape. In addition to natural convection, the heat source arrangement is an important factor in determining the melt shape.

The aim of this work is to propose a method to determine the elastic parameters and the thickness of a thin epoxy film located inside a 3-layer aluminum/epoxy/aluminum structure, based on ultrasonic measurements. This study is conducted at low frequencies, to allow the vibration of the whole structure. First, the direct problem is addressed. The sensitivity of the vibration modes to the parameters of interest is studied to select the most sensitive one for a given parameter to be determined. Second, the identification of the parameters with the selected modes is obtained by a minimization of the characteristic equation. This process is applied to experimental data: the longitudinal and shear wave velocities and the thickness of the epoxy film are obtained within a 3% error range.

Energy management using state flow for designing an intelligent micro-grid for a specific combination vehicle to building (V2B) in specific geographic region is proposed. Renewable energy based PV solar with impact of ambient temperature is also undertaken in both STC and NOCT mode. In this paper, a complete energy system design is analyzed and simulated under different scenarios and operation condition. Backup energy storage system including plug-in hybrid electric vehicle and diesel generator are used to ensure an uninterruptible power supply in case of low solar irradiation. A direct voltage control is adapted to regulate the ac load voltage. The under study system is validated by simulation using Matlab/Simulink.

We solve, for the first time, electromagnetic wave propagation equations in heterogeneous media using the spectral moments method. This numerical method, first developed in condensed matter physics, was successfully applied to acoustic waves propagation simulation in geophysics. The method requires the introduction of an auxiliary density function, which can be calculated by the moments technique. This allows computation of the Green's function of the whole system as a continued fraction in time Fourier domain. The coefficients of the continued fraction are computed directly from the dynamics matrix obtained by discretization of wave propagation equations and from the sources and receivers. We illustrate this method through the study of a plane wave diffraction by a slit in two-dimensional (2-D) media and by a rectangular aperture in three-dimensional (3-D) media. Comparison with analytical results obtained with the Kirchhoff theory shows that this method is a very powerful tool to solve propagation equations in heterogeneous media. Last, we present a comparison with other computing methods.

This paper presents a first attempt at using the spectral moments method (SMM) to solve Maxwell's equations in twisted anisotropic media in the presence of defects. This numerical method, previously developed in condensed matter physics, allows computation of Green functions for very large systems. The dynamic matrix of the discretized system is built from the medium parameters. Green functions, calculated for a given source, representing a point source at infinity and given receiver, are developed as a continued fraction whose coefficients are related to the moments and directly computed from the dynamic matrix. In this study we compute the light transmitted through thin surface-stabilized ferroelectric liquid crystal cells with a chevron structure and a twisted director distribution. The efficiency and accuracy of the method are analysed by comparing the results obtained by SMM with the analytical solution obtained using the Jones matrix formalism. Finally, we apply SMM to compute the transmitted light with different director configurations. We show, by comparisons with experimental data, that the simplest director configuration is certainly the most probable.

In this research work, a numerical simulation is carried out to study the performance of coupled mixing and heating generated by chaotic advection in a mixer comprising rotating rods uphold inside a cylindrical tank. The effect of the number of the rotating rods on both the chaotic advection and the thermal efficiency of the mixer is presented. It is found that the use of noncontinuous wall rotations is necessary to ameliorate the heat transfer by chaotic mixing. The increase in the number of rod within the mixer can also promote the thermal performance of the mixer.