Proceedings of the 2nd International Conference on Green Energy Conversion System

Based on Density Functional Theory (DFT) calculations, we investigate the structural and energetics properties of the atomic hydrogen adsorption on two-dimensional (2D) hexagonal AlN. The obtained results show that hydrogen in hollow site induces volume expansion (~ 1.12%) of AlN monolayer. Whereas volume contraction is found for hydrogen in bridge, top Al and top N adsorption sites, due to the slight decrease of the lattice parameters (~ 0.32–0.8%). Hydrogen atom prefers to form a bond with nitrogen than aluminum in AlN monolayer with bond length H-N of 1.05 Å.

The Pseudo-Potential method (PP) based on Density Functional Theory (DFT), was applied to investigate the site preference of hydrogen atom in the Mg3La alloy, which exhibits Fcc structure (space group 225). The relative stability of hydrogen atom at various interstitial sites (Wyckoff positions: 24d, 24e, 32f and 48g) was determined, with a particular attention to the hydrogenation effects on the stability and structural properties of the Mg3La alloy. The results were discussed in the light of the available theoretical and experimental results.

Today, the demand for electrical appliances, such as power converters, economic lamps, LEDs, speed drives, and regulators, is increasing in recent years, but despite their robustness and good dynamic responses, they inject harmonic currents into the network. This article presents in-depth studies on the effect of the use of Compact fluorescent lamps CFL on a Low Voltage (LV) local area network, as well as an interest in modeling this type called non-linear charge under PSIM and MATLAB Software.

This paper proposes a New Modulation Hysteresis Control block for a three phase four wire Shunt Active Power Filter (SAPF) for currents harmonics compensation generated by Compact Fluorescents Lamps (CFLs). This study employs the PQ power control strategy. The performance of the SAPF is evaluated under both simple hysteresis controller and under the new modulation hysteresis controller conditions using the Matlab/Simulink platform. The findings simulation results demonstrate that the proposed new technique can improve the power quality of the main, and the total harmonic distortion (THD) optimization, which also confirms the effectiveness of the approach.

Sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) are the most popular modulation strategies for multi-level inverters. This paper provides the theoretical analysis and simulation results of SPWM and SVPWM for three level inverters. This paper focuses on implementation of Space Vector Pulse Width Modulation (SVPWM) Technique for Three level Neutral Point Clamped (NPC) Multilevel Inverter and compare it with Sinusoidal Pulse Width Modulation Technique (SPWM). Simulation results were shown and compared in the view of THD for both the techniques. The result shows that the SVPWM is better for three level NPC inverter in THD point of view.

The considerable amount of energy contained in the exhaust gases of gas turbines represents a valuable potential that cannot be overlooked. The objective of this study is to identify the cycle that contributes the most to improving the performance of the simple gas turbine cycle (Joule-Brayton cycle) and reducing CO2 emissions to the environment through the recovery of exhaust gases. Many studies have focused on methods for better exploiting this potential. In this context, three different cycles with exhaust gas recovery were analyzed in this work: the cycle with conventional recovery, the cycle with alternative recovery, and the cycle with staged recovery. The aim of this study is to evaluate the benefits of the best cycle with exhaust gas recovery based on energy performance and environmental impact. The energy analysis shows a significant improvement in energy efficiency compared to that of the cycle without recovery. To better understand the behavior of these technologies and achieve their best integration, we analyze the influence of certain key parameters such as compression ratio, ambient temperature, and heat exchanger effectiveness. The results of the environmental analysis show that the amount of CO2 emissions in the cycles with recovery is significantly reduced.

Renewable energy sources offer unlimited potential for clean electricity production and their usage is rapidly growing. Hybrid energy systems incorporate various sources, requiring efficient control and supervision mechanisms. In this regard, this study proposes an artificial intelligence-based energy management system, utilizing fuzzy logic control, for a hybrid wind/photovoltaic system with battery storage. The proposed approach adjusts the system output to supply the load demand, offering benefits of precise control of the battery's state of charge (SOC) across five states. This is a marked improvement over traditional management systems that rely on two SOC states, namely SOCmin-SOCmax.

The paper is devoted to a study on design, optimization and experimental study of a renewable hybrid system (photovoltaic/wind turbine) with battery storage. The design of the studied system use the total incident energy approaches to determinate the size of photovoltaic and wind generators. The simulation study has been done under Matlab/Simulink. An application to pumping water is done for four various profiles measured at Bejaia area. To control the water pumping hybrid system, a power management control has been applied to coordinate the different sources. The simulation results obtained are shown and discussed to demonstrate the applicability of the suggested system. The overall hybrid pumping system with batteries has been then investigated by an experimental study, where tests have been made during different days and under various total dynamic heads (TDH) to show the different performances as flow rate and pump efficiency variations of the proposed system. A comparison of simulation and experimental results are presented and analyzed to conclude on the feasibility of the studied system for water pumping needs applied in a small-scale area of Bejaia a Mediterranean region in Algeria.

The choice of traction motor for the propulsion system is crucial in their design. In order to contribute to the actual research applied to electric vehicle powertrains field, this paper focuses on Doubly-Fed Induction Machines (DFIM) in traction systems. The theoretical study examines the DFIM’s steady-state features and performances based on the d-q reference model. Hence, an optimized control for an accurate rotor voltage amplitude and angle adjusting in steady state is proposed. The obtained reference voltages will be injected into a Voltage Source Inverters (VSI) in both stator and rotor sides, which are controlled through a Space Vector Pulse Width Modulation (SVPWM) technique. The overall of optimized control scheme has been implemented in real-time on a Digital Signal Processor (DSP) and has been experimentally tested on a laboratory prototype designed around two variable speed drives that feed a DFIM. The obtained results show that by properly determining the rotor voltage, the DFIM can operate optimally in a wide range of speed variations.

Induction motors (IM) are widely applied in manifold industrial applications, notably in the renewable energy sector, owing to their low maintenance requirements, economical cost, and high efficiency. This article outlines a Wind Turbine Emulation (WTE) system using a squirrel cage asynchronous machine under Direct Torque Control (DTC) approach. The proposed DTC strategy is based on a three-level Neutral Point Clamped (NPC) inverter fed the IM to proficiently imitate a small-scale wind-turbine behavior in a laboratory setting by regulating the waveform of the speed. The suggested control system reacts effectively as a wind turbine emulator in research laboratory by controlling the speed waveform with minimum torque and flux ripples. The simulation findings, carried out using Matlab/SIMULINK environment, confirmed the suitability of the DTC in WTE application.

Waste heat recovery from helically coiled tube heat exchanger of a household refrigerator system is attractive due to its free energy consumption for residential and commercial hot water production. In this chapter, we present an experimental and numerical investigation on a modified household refrigerator for hot water production useful for domestic purpose. This device helps undergraduate mechanical engineering students in understanding the basic natural heat transfer phenomenon between the helical condenser coil and the water in the tank. From the results, after 300 min of heating, the maximum water temperature achieved in the cylindrical tank is 51 °C. Therefore, this modified refrigerator can be utilized in hotels, industry and domestic purposes which need hot water.

In order to improve the heat transfer in helically coiled tube heat exchanger immersed in the water tank, we have developed a new coupled model containing both domestic refrigerator and water heater. In the numerical simulation, the three dimensional storage tank with immersed helical coil heat exchanger was simplified as an axisymmetric two dimensional model in order to reduce the calculated capacity and a total of mesh volumes. According to the obtained results, this model is able to predict the effect of condenser coil designs on the heating process of the domestic refrigerator coupled with water heating system. The results indicated that the heating characteristics in the variable pitch coil were improved in comparison with that of normal coil.

The objectives of the studies presented here are to develop an efficient method adapted to the energy production of an isolated hybrid power system located on the island of Djerba, Tunisia. To this end, we have proposed two optimization methods, based respectively on linear programming (LP) and software (HOMER), with the aim of minimizing the energy cost of the hybrid system while respecting constraints linked to all the elements of the system. We therefore compared the two optimization strategies. The proposed linear program yields an electricity cost of 0.206$/kWh, lower than the HOMER cost of 0.308$/kWh. This system would therefore have advantages in terms of energy independence in particular.

Photovoltaic (PV) solar power systems are gaining ground worldwide and represent a promising alternative to renewable energy generation. However, many studies have highlighted some disadvantages associated with the installation and operation of conventional solar power plants. Therefore, floating photovoltaic systems (FPV) have emerged as a new solar energy concept to reduce the negative impact on the environment caused by traditional photovoltaic system configurations. The FPV market has grown at an impressive rate over the past decade, with global installed capacity doubling year-on-year. This growth has been made possible due to the numerous advantages that FPV systems have over conventional systems, primarily related to land use and energy efficiency. The purpose of the study was to compare the FPV system with the conventional PV system (CPV). This research uses the MATLAB Simulink platform to simulate the entire block, and adapts the common photovoltaic power generation model to the floating solar photovoltaic power generation.

The topology of a bidirectional DC-DC converter is typically crucial in systems that require the bidirectional exchange of electricity. It is frequently used in composite energy storage and microgrids. Electric cars, systems, etc. The architecture is interleaved to increase power handling capability and decrease input side ripple current. By allowing current sharing between several phases, interleaving improves the converter’s power density by allowing for a smaller filter inductor and input and output capacitors. An N-phase non-isolated bidirectional DC-DC converter’s design and generalized phase shift specifications are presented in this publication. In MATLAB/Simulink, a two-phase non-isolated interleaved bidirectional DC-DC converter’s closed-loop simulation is performed while taking into account both the boost and buck modes of operation. The outcomes demonstrate equitable current sharing between phases, which lowers input current ripple, reduces the size of filter elements, and enhances converter thermal distribution. When integrating with non-isolated DC-DC converters in power systems, control strategies like proportional integral derivative (PID) and slide mode control (SMC) are also examined in terms of the parameters settling issue, response time, and complexity.

In this paper, we propose a sliding mode and Lyapunov Function based control for a DC microgrid. The microgrid involving renewable distributed generators (PV system and wind turbine), energy storage system (Battery), a solid oxide fuel cell a dump load (aqua_electrolyzer) connected to the same dc bus and an inverter connected to LCL filter which is connected to an AC load Fig. 1. The behavior of the whole system is represented by mathematical models derived from the different sources of the microgrid the dump load and the storage system are presented in Sect. 2. The decentralized control of the microgrid components are depicted with synoptic figures presented in Sect. 2. The energy management algorithm is adopted to ensure the power balance under variable power generation. Simulation results demonstrate that the proposed control method has acceptable performance, including robust tracking and a velvety transition under generation scenario and load power variation in the large range.

The DC/DC converters are widely used in photovoltaic generation systems as interfaces between the photovoltaic panels and the load, enabling the maximum power point (MPP) follow-up. To extract the maximum power, it is necessary to adjust the load to match the current and voltage of the solar panel. The converter must be designed to be directly connected to the photovoltaic panel and perform operations to search for the maximum power point (MPPT). DC/DC converters, together with maximum power point tracking systems (MPPT), are used to avoid these losses.

The Random sinusoidal pulse width modulation (RSPWM) is a non-conventional spread spectrum technique. It is proposed for the suppression of EMI and the improvement of power quality in a three-phase power inverter. This paper propose a digital modulation technique. It is implemented through a compact low-cost microcontroller ATMEGA2560 by developing suitable C coding for producing the required switching pulses for the inverter. A comparative analysis is also presented between the proposed random sinusoidal PWM modulation RSPWM and the conventional SPWM. It is shown that the implementation of RSPWM results in reduced EMI, a decreased Total Harmonic Distortion THD, and the noise effect is also improved significantly.

The energy efficiency of Photovoltaic (PV) systems is strongly linked to both manufacturing factors, such as the nature of the PV cells, and environmental factors (irradiance and temperature). However, during its operation, the PV system is subject to several types of faults that can affect its optimal operation. The soiling and shadowing, which create an inhomogeneous distribution of the incident irradiance on the PV cell or panel, is one of the most commonly encountered PV faults that leads to an overall degradation of the energy produced by this panel. The main objective of this paper is to study the thermal impact of the shadowing on the PV panels. For this, two types of shading have been created artificially: the first is the covering (total and partial) of the panel, and the second is the shading using a nearby opaque object. Thermal images were taken using the Fluke Ti25 IR thermal camera. The obtained results show the generation of hotspots on the shaded panel and a remarkable decrease in power produced.

In this paper, we address the crucial issue of energy consumption minimization in device-to-device (D2D) communications in the healthcare logistics domain. The growing demand for real-time communication and data exchange in healthcare environments has led to an increase in the use of D2D technologies, but the associated energy consumption can have a long-term impact on the sustainability of these systems. To tackle this challenge, we propose exploring the use of neural networks to predict the energy consumption of different D2D communication protocols and optimize the parameters to minimize this consumption. The objective of this article is to provide a thorough study on the use of neural networks for energy consumption minimization in D2D communications for healthcare logistics. We will use simulations to evaluate the results of this approach, and we will discuss the implications of our conclusions for the design of sustainable communication systems in healthcare environments.

With technological advancement and based on the principle of Communication of objects, oriented applications towards intelligent energy management are in line to be the simplest, most effective, while allowing to provide comfort to the human and minimize energy consumption. The use of certain standards communications protocols facilitates the deployment of wireless network. This article consists to design a «Smart Plug» able to receive and execute commands on various devices of the installation (lighting, heating, activation of rolling shutters) located on the same network.

This paper addresses the challenges associated with modeling storage systems and characteristics of hydrogen in the planning of island microgrids powered solely by renewable generation. We propose a novel Mixed-Integer Linear Programming (MILP) formulation that accounts for the non-constant efficiency of hydrogen chain storage, aiming to minimize error between Energy Management System (EMS) control and grid performance. Furthermore, our formulation incorporates flexible constraints to effectively manage surplus energy and mitigate energy wastage in scenarios with limited available resources. Through this research, we contribute to the development of optimized planning strategies for island microgrids, facilitating the integration of renewable energy sources and enhancing their operational efficiency.

This paper deals with the observability bound problem of a discrete-time nonlinear singularly perturbed systems (SPSs) subject to $$\mathcal {L}_2$$ L 2 disturbances. The considered system is represented by a coupled state multimodel (MM). A $${H_\infty }$$ H ∞ proportional-integral (PIMO), features by its robustness, is designed, ensuring that the state estimation error is asymptotically stable and satisfies the $${H_\infty }$$ H ∞ performance constraint for a proper bound of the singular perturbation parameter based on a quadratic Lyapunov function and the $${H_\infty }$$ H ∞ norm. Before designing this observer, a sufficient conditions described in terms of linear matrix inequalities (LMIs) are developed to ensure the robust stability bound of the considered system. Then, using the results of these two tasks, the observability bound of the system is determined.

This paper presents a control and implementation of a bidirectional on-board charger for V2G applications; An interleaved buck/boost converter is used in this system to reduce the size of the passive components of its filters and to improve the current ripple when the battery is being discharged. The DC-DC converter and the DC-AC inverter make up the core topology of the bidirectional on-board charger, which is connected in a cascading form. The border controller is the controller utilized in this suggested system. For V2G functionality, the converter will be operated in boost mode to step up voltage from a battery pack's low voltage (placed in a vehicle) to an appropriate high voltage at the DC-link capacitor before converting to AC using a single-phase inverter. PLL is used as a grid synchronization method to connect to the electric grid. The validation of this proposed system is validated through simulation and experimental results. Ultimately, the simulation and experimental results in MATLAB/Simulink show that the proposed technique is effective and fast response.

The Proton Exchange Membrane Fuel Cell (PEMFC) technology is the fastest growing technology. Nowadays, the latter is widely chosen as renewable energy source. Fuel cells are expensive to manufacture. Hence, modelling and simulation of its behavior are necessary in the aim to optimize its performance. In this work, we are focused on the PEMFC stack electric characteristic study. The concerned PEMFC stack produces a power of 100KW. The PEMFC stack are investigated by connecting a specific number of fuel cells in series. At the aim of accomplishing this step, a detailed model is investigated. It is developed based on the equivalent electric circuit of the PFMFC. A most significant one is adopted. Based on the PEMFC power, the number of PEMFC cells and the whole area of the PEMFC stack are suitably computed. The developed equivalent circuit model integrates the fundamental parameters of each sub-cell on the one hand. On the other hand, it involves the impact of temperature, oxygen partial pressure, hydrogen partial pressure and membrane water content. To demonstrate the performance of the used model, a simulation work using Matlab/Simulink tools is carried out. In fact, the PEMFC stack conceived equations are implemented in the form of masked blocs by using the subsystem concept in Matlab/Simulink environment. The electrical characteristics of the PEMFC stack behavior against temperature, oxygen partial pressure, hydrogen partial pressure and membrane water content are investigated. Most significant results are given and discussed.

In contemporary times, there exists a significant rise in the demand for electricity. This surge necessitates a robust demand for natural resources and fossils. Consequently, it is incumbent upon us to integrate novel renewable and clean energy sources. The focus of this paper centers on wind turbines, which provide electrical energy through a dual conversion process, involving the conversion of kinetic energy of the blade to mechanical energy and the mechanical to electrical energy. The permanent magnetic synchronous generator (PMSG) is the device responsible for the second energy conversion. Firstly, we present a model of the wind turbine to enhance our comprehension of the energy conversion process. Additionally, we provide an illustration of another model for the PMSG. We then proceed to present an optimization of the generator speed aimed at maximizing the system’s performance. This is achieved through the application of the strategy of maximum power point tracking (MPPT) with a PI regulator. Finally, we translate the mathematical model of the wind turbine and the PMSG into block diagrams using Simulink Matlab.

In the present work, the dielectric relaxation spectroscopy technique (DRS) is used to investigate the electrical properties of synthetic photoreticulated Polyisoprene films containing conductive particles of core–shell structure. The conduction threshold of these materials is situated below 0.5 wt% of Polyaniline. Such a low percolation threshold is desired to maintain the matrix flexibility. For the 40 wt% loaded film, the conductivity reaches more than 10–5 S/cm. This value is suitable for semi-conductive applications. As expected, the conductivity was found to be thermally activated. The application of Efros-Shklovskii model gives a short localization length of about 4 A°. At low frequencies, the dielectric constant of these composites at room temperature is very high, a jump from nearly 10 to 107 was recorded for the 40 wt% loaded film. This is probably due to the interfacial polarization between the three constituents. Such high values of the dielectric constant allow using these materials as high k dielectrics for energy storage applications.

Wind energy plays a major role in the production of electrical energy in the industrial world. Like any industrial system, the wind turbine can be threatened by anomalies likely to affect its performance or even cause a total shutdown of the installation. Therefore, fault diagnosis methods are necessary. In this work, in order to avoid the occurrence of a malfunction, either to avoid them or to limit their consequences, we used a model-based fault diagnosis technique to detect and isolate sensor faults and actuators in pitch angle systems. To do this, we used an observer applied to a “Benchmark” model for fault detection and isolation (FDI). Simulation results under the MATLAB/Simulink environment are presented to validate the effectiveness of this diagnostic method.

This research focuses on a photovoltaic system that powers an Electric Vehicle when moving in realistic scenarios with partial shading conditions. The main goal is to find an efficient control scheme to allow the solar generator producing the maximum amount of power achievable. The first contribution of this paper is the mathematical modelling of the photovoltaic system, its function and its features, considering the synthesis of the step-up converter and the maximum power point tracking analysis. This research looks at two intelligent control strategies to get the most power out, even with shading areas. Specifically, we show how to apply two evolutionary algorithms for this control. They are the “particle swarm optimization method” and the “grey wolf optimization method”. These algorithms were tested and evaluated when a battery storage system in an Electric Vehicle is fed through a photovoltaic system. The Simulink/Matlab tool is used to execute the simulation phases and to quantify the performances of each of these control systems. Based on our simulation tests, the best method is identified.

The work presented in this paper aims to study the impact of pollution on the production of photovoltaic systems. The work proposes the establishment of a supervision and control system allowing real-time knowledge of the different sizes of the PV system as well as automatic intervention in the event of accumulation of dust or other. The communication with the operator is ensured by the GSM network. The proposed work is presented as a simple and easy solution that can be used to ensure good control of photovoltaic systems in polluted areas.

The fast development of intelligent techniques brings new method for wind turbine control. For adjusting the aerodynamic torque of the wind turbine when winds speed inconsistent, we use the pitch angle control. As conventional pitch control customarily use classic controller, the mathematical model of the system should be well known. In this works, a fuzzy logic control pitch angle controller is developed. The obtained results show that the fuzzy logic controller give better control performances than conventional control strategies.

Among the problems often encountered in the industry is the fouling of heat exchangers which can be defined as the deposition of undesirable materials, such as scale, suspended solids, and even insoluble salts on the internal surfaces of the heat exchanger. The presence of these deposits represents a resistance to fluid flow and heat transfer and increases the pressure loss and reduces the efficiency of the exchanger. Fouling of heat exchangers is unavoidable but can be mitigated by. Effective implementation of appropriate cleaning techniques. Periodic cleaning of heat exchangers is one option among the techniques to minimize losses due to fouling. However, cleaning activities in heat exchangers are costly. Consequently, the use of the reverse method with a fouling model to describe the fouling behavior and the experimental data makes it possible to obtain a better estimate of the value of the thermal resistance of fouling and thus a precise date for the cleaning. Our work consists in estimating the fouling resistance of the exchangers of the phosphoric acid concentration unit of the Tunisian chemical group using stochastic methods such as the genetic algorithm (GA) and the special swarm optimization (PSO). This method demonstrates a convergence towards the global minimum, even in the presence of several local minima, with great precision.

Today, most countries rely on renewable energy sources (RES), such as solar, wind, hydroelectric, biomass, geothermal, etc.… energies. Solar and wind energies in particular are widely used because they are naturally abundant and environmentally friendly. Electricity generation based on renewable energy is growing. Alternative energy sources and system development systems tend to develop traditional energy sources dependent on the greenhouse effect. Photovoltaic systems are used mainly because of their economic efficiency. The main application of off-grid solar photovoltaic (SPV) systems is water harvesting in rural areas that cannot be connected to the grid. In this application, photovoltaic (PV) and pump system control are key to improving overall efficiency. At this against this background, this work proposes a simple and efficient off-grid solar photovoltaic water pumping system (SPVWPS). The designed system is based on a DC-DC boost converter, a three-phase DC-AC inverter, and a three-phase asynchronous motor coupled to a centrifugal pump. P&O Method for Maximum Power Point Tracking (MPPT). Finally, the effectiveness of the proposed off-grid SPVWPS is verified using a 4-KVA prototype.

The identification of photovoltaic (PV) model unknown parameters using measured characteristic curves is of great importance for designers involved in modelling, simulation, and control of PV systems. This paper introduces an enhanced heuristic algorithm, namely ALO-CS (Ant Lion Optimizer-Cuckoo Search), which combines the strengths of both ALO and CS optimization algorithms. The primary objective is to accurately extract the parameters of various commercial PV modules. To the best of our knowledge, this novel approach has not been previously explored in the literature, making it a unique contribution. In order to evaluate its effectiveness, a comparative analysis is conducted against several state-of-the-art methods. The experimental and analytical results demonstrate that the proposed Hybrid ALO-CS algorithm outperforms improved JAYA and other methods in terms of accuracy and quality, establishing its competitive advantage.

The increasing demand for energy as well as the growing requirements for ecological conservation have led to the study and expansion of the use cleaner, unconventional and less environmentally friendly alternative energy sources. Photovoltaic energy is now used as a more valuable natural energy source, for it is free, plentiful, fresh and dispersed on Earth. The work aims to study an autonomous photovoltaic pumping system using a BLDC motor, a three-phase voltage inverter and a DC-DC zeta converter. The intelligent control of the zeta converter with the incremental conductance function (INC-MPPT) will track the maximum power point, while the algorithm will ensure a smooth start of the BLDC motor used to drive the centrifugal pump. The obtained simulation results confirm the efficiency and good performance of the BLDC motor.

Increased industrial activities are highly linked to increased carbon emissions, which have been identified as the main cause of the increase of global warming and contribute of a substantial amount of greenhouse gases into our environment. As such, an average carbon footprint of di-calcium phosphate (DCP) production from the Tunisian Chemical Group has been calculated and analyzed. The model established using the SimaPro software considers for carbon footprint evaluation using the “IPCC GWP 2013 100 a V1.03” for the impact assessment methodology. The specificity of this method is to assess the “climate change” impact. This study showed that direct emissions contributing for 1350.1 kg CO2 eq/t of DCP which 64.96% is attributed to the synthesis reaction of (DCP), with a significant proportion of 46.14% of phosphoric acid used as a raw material. Natural gas contributes with a percentage of 32.6%of total GHG emissions. While, greenhouse gas emissions from transportation and electricity represents 1.2% of total emission.

This paper introduces a novel approach for the fixed-switching frequency of a wind turbine-based induction generator in microgrid. The proposed strategy combines power control and modulated hysteresis control current. One of the advantages of this method is the constant switching frequency of the converter switches, which eliminates a major drawback of the classical hysteresis control. This approach also allows to obtain an AC current with sinusoidal forms and a constant frequency while ensuring minimal total harmonic distortion (THD) of the current. Simulations were conducted using Matlab/Simulink, and the results demonstrated considerable improvements with regard to the classical method, including reduced current THD supplied to the AC grid, and, improved dynamic response performance as well.

The growing interest in environmental sustainability and the permanent need for environmentally friendly transportation solutions have amplified the interest attributed to hybrid electric vehicles (HEVs) and accelerated their large commercialization. In this paper, the control and energy management of an electric vehicle powered by a fuel cell (FC) and supercapacitor (SC) is studied. The HEV is controlled using direct torque control and the vehicle speed is regulated using sliding mode controller (SMC). Simulation results yielded good vehicle performances and confirm the efficiency of the designed SMC controller. Moreover, robustness analysis was performed to evaluate HEV performance against possible variation in the parameters of its traction machine and the obtained results were satisfactory.

Pulse width modulation (PWM) techniques are primordial to high performance and great efficiency of inverters. The Selective Harmonic Elimination (SHE) technique determines in advance the switching angles, by taking into account the desired output voltage amplitude and harmonics to be eliminated. Thus, resolution of non-linear equation systems to set the switching angles poses crucial problem for the initial values choice. So, to remedy this problem, we propose in this work to formulate initial conditions by linear mathematical approximations, in order to approximate them to exact values that define pulse-width modulation. This formulation allows gain on the one hand the harmonics eliminated number (N) which will increase and on the other hand the computation time, which is often important. In this paper, we present transcendental equations resolution for switching angles (even or odd) and for two types of control patterns, namely: $${\uptheta }_{{\text{N}}} < {60}{^\circ }$$ θ N < 60 ∘ and $${\uptheta }_{{\text{N}}} < {90}{^\circ }$$ θ N < 90 ∘ . In order to validate our study, we demonstrated switching angles variation law as a function of modulation index using MATLAB simulation.

Electric motor control represents an important interest for industry. Thus, induction machines provide major source of acoustic noise. Field Oriented Control FOC offers an attractive solution to achieve high performance in variable-speed applications. This control consists to make the asynchronous machine control analogous to that of the DC machine where there is a natural decoupling between the rotor flux and electromagnetic torque. SVPWM and RPWM modulation techniques are also applied to supply systems in closed loop. The aim of this paper is to analyze the interaction between the inverter and the machine in closed loop and to estimate the level of noise emitted by the FOC control as a function of the modulation technique applied. For that we demonstrated and discussed the performance of the FOC control on the electrical and mechanical quantities produced by the machine. In addition, we have shown and compared the stator current harmonic spectra for each modulation technique in open and closed loop.

This paper presents a diagnosis method to detect, isolate and estimate faults occurring in permanent magnet synchronous generator (PMSG). This method is based on a dynamical sparse recovery (SR) algorithm that is able to reconstruct online and with finite-time convergence a sparse vector of numerous faults from few system measurements. The faulty PMSG system is affected by a partial inter-turn short circuit and voltage dip faults. Using Matlab/Simulink environment, some scenarios are presented to present the efficiency of SR method for diagnostic of PMSG system.

Many researchers have paid great attention to fault diagnosis technologies in order to reduce worst operations and maintenance costs. Accordingly, this work presents a new method to detect, isolate and estimate faults occurring in permanent magnet synchronous generator (PMSG). This method is based on a dynamical sparse recovery algorithm that is able to reconstruct online and with finite time convergence a sparse vector of numerous faults from few system measurements. The faulty system is modeled in case of permanent magnet demagnetization and voltage dip faults and its dynamical modelisation is adapted to the proposed algorithm under some theoretical conditions. The system model with the proposed algorithm is implemented under Matlab/Simulink environment and its effectiveness is verified upon simulation results for such fault scenarios.

The company “Timab Tunisie” wishes to set up a PV central with a power of 1 MW connected to the network. The objective is to compensate for its energy needs in terms of electricity. This central will make it possible to save primary energy about 465.43 toe/year and reduce interrupted CO2 emissions by around 1108 tCO2/year. The work presented in this article aims at the design and modeling of the PV generator. PV central is equipped with five independently controlled static converters. Digital MPPT controllers integrated in the inverters ensure the search for maximum power delivered. After the description of the structure of the system, we present the simulation results for different climatic conditions as well as an estimate of the annual energy production.

In this paper, we consider two boost choppers connected in parallel, with two different sources, and a load with low power demand. The two boost choppers can enter in a discontinuous mode of operation by providing a small current that approaches zero. To prevent this, we propose a new strategy for power distribution based on the value of the current at the limit between continuous and discontinuous modes. In the case of a very low power demand, one boost chopper can be disconnected, ensuring a continuous mode operation for the remaining boost chopper.

In this work, we have studied a tidal energy conversion system using a synchronous generator with permanent magnets and connected to grid. To achieve the objectives, a Park modeling of the machine was carried out with an oriented flux vector control, which allowed the machine to operate at variable speed. For the control of the grid side converter, we used hysteresis current control loops. To guarantee a constant DC bus voltage level, a method based on the calculation of the TSR error equipped with a PID regulator was used. The results of the various simulations of the entire conversion chain, carried out under the MATLAB/Simulink environment, made it possible to evaluate the performance of the proposed control algorithms.

The advent of the Internet of Things (IoT) has revolutionized various industries by connecting physical devices and enabling them to exchange data. However, One of the key challenges faced by IoT nodes is the limited availability of energy resources. Therefore, optimizing energy efficiency in IoT nodes has emerged as a crucial research area. This paper presents a solution aimed at addressing this challenge, an optimized solar energy harvesting system for IoT nodes, using solar photovoltaic energy. Our work introduces a novel approach called MPPT HHO-HBA. This approach combines two optimization techniques, Harris Hawks Optimization and Honey Badger algorithm. The aim of our approach is to optimize the Maximum Power Point Tracking (MPPT) of solar panels for IoT nodes to maximize their power output and increase the overall network’s lifetime. To ensure that the harvested solar power is effectively used, a SEPIC converter is employed to boost the electrical energy generated by the solar panel. The proposed approach is implemented in MATLAB/Simulink, and the effectiveness of the methodology is assessed using appropriate metrics. The results demonstrate that the proposed method surpasses previous strategies in terms of efficiency. Additionally, our system has the capability to power numerous sensor nodes, contributing to enhanced sustainability and reduced carbon footprint compared to traditional energy sources.

The utilization of TEM00 mode laser beams is critical in precise material processing, optical communication, and high-resolution imaging. While TEM00 mode solar laser beams have been achieved, the need for a highly accurate and continuously operating solar tracking system presents significant challenges. A solar laser pumping approach is here proposed to enable the production of four uniform and stable TEM00 mode solar laser beams even in the presence of solar tracking errors. The solar radiation was collected and concentrated using a heliostat—parabolic mirror system. An aspheric lens further concentrated the solar rays into a homogenizer that evenly distributed the solar power flux onto four Nd:YAG rods positioned within a single pump cavity. Through Zemax® and LASCAD™ software analysis, successful generation of four uniform and stable 1064 nm continuous-wave solar laser emissions was numerically demonstrated, exhibiting similar TEM00 power levels and beam quality factors. The system showed resilience against solar tracking errors of up to ± 0.2°.

This paper discusses the use of machine learning to track the maximum power point. In order to train neural networks, the error back propagation approach is employed. The advantage of neural networks is their quick and accurate tracking of maximum power points. This method makes use of a neural network to provide the reference voltage for the maximum power point under various atmospheric circumstances. The maximum power point can be tracked by properly controlling the dc-dc boost converter. Simulation results are obtained using MATLAB/SIMULINK to verify theory analysis.

In this research work, the control of an electric vehicle powered by a photovoltaic system is examined. A triple-junction solar cell made of InGaP/InGaAs/Ge with a high efficiency served as the foundation for the used photovoltaic generator. The fourth case studies that are examined involve standard test settings, a step change in solar radiation with a constant temperature, a step change in temperature with a constant sun radiation, simultaneous step changes in temperature, and solar radiation conditions. An electric vehicle's three-phase permanent magnet motor (PMSM) serves as the foundation for its traction system. The control approach relies on the field oriented control strategy. All of the control algorithms and the designed system are implemented in Matlab/Simulink. Significant results are provided and discussed for a wide range of speeds, including the two operating modes under step changes in environmental circumstances.

This paper presents an intelligent estimator for a wind system. This estimator is based on the combination of two powerful tools that are neural and multi-model approach. This estimation approach based on artificial intelligence is exploited to estimate currents of an isolated wind system based on PMSG. The studied system contains a turbine which, under the wind, drives in rotation a PMSG that generates electricity towards an isolated site via multilevel controlled rectifier.

This work present an improvement of a Hybrid PV system performance based on the use of both MPPT algorithm and multilevel inverters. Inverters are an essential element in renewable energy production systems. Conventional inverters have several drawbacks such as overvoltage problems at the semiconductor terminal in high-power applications, and the obtaining of a non-sinusoidal voltage that is rich in harmonics. Multilevel inverter topologies can be arranged in many different combinations; among the popular multilevel inverter topologies are Diode Clamped Multilevel Inverters (DCMLI). Two types are studied and compared that are three and five Diode Clamped Multilevel Inverter (DCMLI). The modeling and the control of the PV system are developed and implemented in Matlab/Simulink environment. Simulation results are presented and analyzed up.

The three-phase inverter, connected to the grid by an LCL filter, is vulnerable to multiple faults, therefore an active fault-tolerant control is required to preserve the electrical power conversion between renewable resources and the grid. In this work, we provide a flatness analysis of the inverter and its LCL filter, the goal being to determine whether the flatness-based control structure stays accurate under both healthy and faulty circumstances.

This paper provides a performance enhancement for direct torque control (DTC) and direct power control (DPC) applied to two-level back-to-back converter feeding the rotor of doubly fed induction generator (DFIG) powered by random speed wind turbine (WT). For this purpose, the sector number in the DTC and DPC is extended from 6 to 12 sectors. While, the switching table based on hysteresis controllers are replaced by fuzzy logic controller (FLC) in both DTC and DPC control. The designed fuzzy 12 sectors DTC (F12S-DTC) and fuzzy 12 sectors DPC (F12S-DPC) significantly reduce ripples in the system under consideration, thanks to error-level consideration and precise localization of the rotor flux vector. The simulation results obtained with the proposed control structure show satisfactory improvements in terms of torque/flux and GSC active/reactive power ripples reduction.

The aim of the present work is to provide new insights on how the nitrogen concentration affects the stability, thermal, and mechanical properties of the Ti2AlC MAX Phase. To this purpose, the DFT-based pseudopotential method combined with the Debye Quasi-harmonic model is applied. The results display a strong dependency of the studied properties on the nitrogen concentration; indeed, the stability and rigidity of the Ti2AlC alloys are substantially improved by nitrogen insertion even at elevated temperatures. Ti2AlC, Ti2AlN, and Ti2AlC0.5N0.5 are brittle and dynamically stable at 0 K with their hexagonal structures. The results are deeply discussed in light of the available theoretical and experimental results.

This article discusses the proposal of hybrid systems utilizing various Renewable Energy Sources (RES), such as wind and solar energy conversion, to enhance system efficiency while reducing generating costs and emissions. These hybrid systems are connected through microgrids, providing a practical and efficient way to integrate renewable energy sources and ensure power supply in diverse scenarios. To achieve high reliability and efficiency, the article employs the P&O Maximum Power Point Tracking (MPPT) method for both Photovoltaic (PV) and Wind-Turbine systems. Simulation results using MATLAB / Simulink demonstrate the impact of climatic conditions on the dynamic behavior of the microgrid.

This paper proposed a method for simulating, modeling, and controlling a hybrid grid-connected power system—a system that is really rather complicated. We research effective ways to use two renewable energy sources without interfering with the main network. The photovoltaic source and the wind source are the two renewable energy sources that make up our hybrid energy system (HES). In order to recoup the system investment cost, it is preferable for these two systems to operate at full capacity. Where a fuzzy logic algorithm-controlled DC/DC boost converter comes after the solar generator (PVG). The induction motor utilized in the wind system serves as a variable speed generator that is directly linked to the turbine. Realizing that our study does not take pitch angle control into account. In spite of changes in wind speed, the MPPT control technique, which is based on the ideal peak speed ratio, is employed to achieve the highest level of energy efficiency. The Point of Common Collecting (PCC) is used to link the two systems. Finally, the results of the simulation demonstrate the viability of our method and the successful implementation of the suggested control technique for medium-sized HES in the production of electricity.

This research paper presents a new approach to examine the behavior of a grid connected Squirrel Cage Induction Generator (SCIG) system, both in steady state and dynamic condition. The SCIG which is driven by a wind turbine via a gearbox, is connected to the distribution system through Power Electronics Converters (PECS), filters, and step-up transformers. The main focus of this paper is on the vector strategy employed for the SCIG, which allows independent control of flux and electromagnetic torque on the PWM converter, while achieving maximum power point tracking (MPPT). The grid side converter plays a crucial role in regulating the DC link voltage, injecting active power through d-axis current, and controlling reactive power injection through q-axis current. The effectiveness of the proposed method is demonstrated through simulation results. The simulation of the entire system are conducted within the MATLAB/Simulink environment, and the obtained results are considered satisfactory.

The shell-and-tube heat exchangers are widely used in various energy conversion systems. In this work, the modelling of the exchanger type of a Liquefied Petroleum Gas (LPG) production unit was carried out using the Bell Belaware method and the Taborek version by playing on the main geometric parameters such as the transverse flow area and leakage zones. Thus, the results obtained are validated by real exchanger study data. Due to the application of this method to shell and tube heat exchangers equipped with baffles, high precision is attained. The heat transfer coefficients obtained show good agreement with the study data.

The PMSG speed uses maximum power point tracking below the rated speed, which corresponds to low and high wind speed, and the maximum energy can be captured from the wind. Pitch angle control is the most common means for adjusting the aerodynamic torque of the wind turbine when wind speed is above rated speed and various controlling variables may be chosen, such as wind speed, generator speed and generator power. As conventional pitch control usually use PI controller, the mathematical model of the system should be known well.

Electrical power transformer is critical equipment in power plant and electrical power transmission and distribution. To facilitate the fault diagnosis of this electrical transformer a Bayesian network was developed and used for information fusion. 7 transformer elements were examined. 22 faults were taken care of in this study. 14 information’s mainly taken from existing test and measurement equipment have been used and the main lines of their interpretations have been formulated. The main result of this contribution was a useful fault diagnosis manual for handling real problems in electrical power transformer maintenance. This contribution can help and serve as an expert decision support system for maintenance engineer. By detecting, diagnosing and decision making, the availability of electrical power transformer was improved.

All sectors are adopting open innovations such as intelligent automation with the use of sophisticated technology such as artificial intelligence (AI) to accomplish systematic procedures for Internet of Things (IoT) systems. The practical deployment of AI-enabled smart systems is now limited by a lack of security levels and confidence in detecting IoT system threats. Because Blockchain can decrease AI vulnerabilities and AI can increase Blockchain's performance, these two technologies are complementary. In the literature, there is little research aimed at protecting intrusion detection systems (IDS) based on ML (Machine Learning) against evasion and poisoning attacks adopting, in most cases, statistical schemes based on traditional methods or ML and resulting in additional deployment and runtime costs. Although the power of machine learning tools is insufficient, these techniques are used to protect themselves against attacks. For this reason, we aim, in this article, to propose a new framework called intellig_block for the detection of cyber threats in ML models which will be used to develop IDS. In intellig_block, the execution of the classification technique will be decentralized, by hashing the model file and we integrate this hash as a smart contract. The experimental result shows encouraging results and low execution time and overhead in terms of gas consumed.

Matrix converters (MCs) have become a popular research topic in the last decade due to their potential to provide amplitude and frequency conversion, bidirectional power flow and input displacement factor control, all in a single-stage converter (SSC). These converters are capable of transforming both voltage and frequency simultaneously and can be used in multi-phase systems. However, despite their advantages, matrix converters are not commonly used in commercial applications. There are several reasons for this lack of adoption. study provides a comprehensive analysis of the various aspects of MC topologies, including the principles of bi-directional switch, modulation techniques, input filter design, and protection issues. MC are still highly appealing for certain applications despite their mentioned drawbacks. This is due to the need to avoid energy storage elements like capacitors and inductors, the cost of power semiconductors continuing to decrease, and the MC's ability to be cost competitive while offering bidirectional flow capability and displacement factor control for regeneration requirements. The MC utilizes two types of space vector modulation methods: direct space vector modulation (DSVM) and indirect space vector modulation (ISVM) strategy. This paper focuses exclusively on the examination of the ISVM strategy and its implementation through the use of the MATLAB/Simulink area.

This work deals with the electrical, optical and structural properties of Aluminum (Al) doped Zinc Oxide (ZnO) thin films. The layers were prepared by the sol–gel method and deposited onto glass substrates using the spin coating technique. The effect of Al incorporation on the electrical and optical properties of the samples was investigated by the four-probe method and the UV–Vis spectroscopy while the X-ray diffraction technique was used to investigate their structure. According to the transmittance curves analysis, the films exhibited a high optical transmission up to 90%. It has been found that the apparent optical gap decreases with increasing the doping level. The electrical resistivity was found to be in the range of 10−3 Ω. cm for the doped films. All the samples exhibited a hexagonal Wurtzite structure. The best performances were obtained for the 4% Al doped film presenting the highest conductivity and crystallinity combined to a good transparency. These low-cost films could be successfully used as transparent electrodes in Photovoltaic applications.

Photovoltaic energy is widely used, because it is clean, free and its technology is now well mastered. This paper presents a new fuzzy direct power control (FDPC) technique to control the active power extracted from the photovoltaic array and sent to the grid, to compensate the reactive power and to reduce the total harmonic distortion (THD) of the grid current caused by the connection of non-linear loads. A fuzzy inference system is used to select the switching states of the inverter, and its input includes active/reactive power variations and the position of the line voltage vector. To illustrate the performance of the proposed technique in a grid-connected photovoltaic system, a simulation model was developed using Matlab/Simulink and Sim Power System, under variable irradiation and non-linear load connected to the grid. The simulation results demonstrate the effectiveness of the proposed FDPC technique.

Increasing energy deficit is not a new challenge for Tunisia. The country is dependent on Algerian gas imports and intent to get its oil supplies from Libya. Its historical and social ties with both countries put it in a privileged position when it needs their support. As to other available options, the Tunisian energy security policy was modified to include renewable energy, and it has not spread. Yet changes at the international and regional levels have challenged the status-quo of Tunisian energy security policy. On the other hand, issues related to energy security have become prominent after 2011 in Tunisia. Within the last decade, populist discourse has challenged the official statistics about national energy resources. In this climate of mistrust, social unrest and rejection of foreign energy companies presence led to the departure of some energy investors while production decreased. This situation has eventually pushed Tunisia to look for new markets for its phosphate exports and new partners. As internal and external factors changed, Tunisia is at a turning point. This paper questions the resilience of Tunisian energy security policy as a discourse and practice after 2011.

Intermediate Band Solar Cells (IBSCs) represent a novel and promising advancement in solar cell technology. These cells hold great potential for high conversion efficiencies, with theoretical values reaching 63.2% under black body illumination and 65.1% under the AM1.5 spectrum. Notably, these efficiency levels are comparable to those achieved by optimized triple-junction solar cells, which attain 63.8% and 67.0%, respectively. This paper focuses on the development of an IBSC structure based on ZnTeO and leverages the power of an Artificial Neural Network (ANN) to model and enhance the performance of the IBSC. The use of an ANN brings significant advantages, particularly in reducing the need for an extensive database. By employing a small representative dataset, the ANN-based approach proves to be highly effective in optimizing the IBSC's efficiency. Importantly, the proposed methodology is not limited to IBSCs alone; it can be extended to other types of solar cells as well. This versatility promotes the realization of promising photovoltaic devices that boast both low-cost manufacturing and high efficiency. This research marks a significant step forward in the quest for efficient and affordable solar energy conversion technologies.

This paper studies a hybrid control strategy for enhancing power generation from floating offshore wind turbines (FOWTs) in low-wind conditions. To handle the uncertain dynamics of the FOWT a super-twisting (STW) control strategy is proposed. Later, to improve the performance of the STW control and to reduce the control effort, the STW control and a radial basis function neural network (RBFNN) are integrated to approximate the uncertainties and unmodeled dynamics. Using the OpenFAST simulator, we compare the strategy’s effectiveness with and without neural network integration.

In this study, a lacunar Polyoxometalate (POM) of Dawson type (α2P2W17O61)10− was prepared and tested in the complexation of (Ni2+) in aqueous solution. The stability of the formed complex (α2P2W17O61Ni)8− according to the reactional medium pH and the time were studied. The stoichiometry and the constant of stability of this formed complex were also studied. From where it was noted that this compound has rather high constant of stability, it was calculated to be β = 1.57 × 106. Thus this compound has interesting proprieties for fixing heavy metals such us nickel existing in industrial waste water.

A model is developed to assess the thermodynamic performance of an Ejector-Compression Refrigerating Machine (ECRM). Four Low GWP refrigerants with zero Ozone Depletion Potential (ODP) are considered: R1234yf, R152a, R290, and R717. The thermodynamic performance of the ECRM is evaluated in critical and non-critical conditions. In critical conditions, the simulation tests show that the critical pressure and critical temperature increase with the boiler temperature; and the entrainment ratio falls as the generator temperature augments. In non-critical conditions, the results reveal that there exists an optimum generator temperature and a motive ratio for which the entrainment ratio is maximum. The best entrainment ratio is achieved with R290 with the highest generator temperature and lowest motive and compression ratios, and the lowest entrainment is obtained with R717 with the highest generator temperature, motive ratio, and compression ratio.

This study focused on the removal of organic matter from real textile effluents by natural clay. The raw clay used in this work was collected from the region of El-Hamma in Tunisia. The clays were characterized by means of Fourier-transform infrared spectroscopy (FTIR) and BET surface area analysis. The different physical and chemical parameters of the textile discharges (pH, Electrical conductivity, SS, COD) were evaluated. Experimental results showed that the maximum COD removal depends on the adsorbent dose and contact time. The adsorption kinetics is well described by the pseudo-first-order model. The equilibrium adsorption data were analysed by Langmuir and Freundlich isotherm models.

The research focuses on the solar generator's components, which are connected to a DC bus that supplies power to the load. To optimize energy harvesting, a maximum power point tracking (MPPT) system is incorporated into the inverter control. The MPPT algorithm enables the power converters to constantly identify the highest power output from the photovoltaic (PV) array, accounting for changes in solar irradiance and temperature. The inverter efficiently converts DC power to AC power while integrating the MPPT function to regulate the system's voltage and current. Additionally, the system is connected to an active filter, which helps reduce load harmonics.

The liquid water generation in the Gas Diffusion Layer (GDL) of a Proton Exchange Membrane Fuel Cell (PEMFC) increases the resistance to oxygen flow toward the catalyst layer. Water flooding inside the GDL can affect the PEMFC performance especially at higher current densities. Therefore, a good understanding of the effect of liquid water amount in the GDL is crucial to water management and, subsequently, to the performance of the fuel cell. The purpose of the present study is to investigate the effect of the microstructure characteristics of the GDL on the water flooding and liquid water distribution inside the GDL. A one-dimensional theoretical model has been developed. Results indicate that the porosity gradient has a significant effect on the liquid water saturation and the performance of the PEM fuel cell.

This paper presents a detailed comparative study of bipolar and unipolar Sinusoidal Pulse Width Modulation (SPWM) techniques in DC-AC inverters, focusing on their efficacy in reducing harmonic distortions, which are detrimental to power system performance. Both SPWM strategies are implemented using the cost-effective and high-performance PIC18F2431 microcontroller, tasked with controlling a single-phase inverter to produce a pure sine wave output. An in-depth analysis of Total Harmonic Distortion (THD) levels at various modulation index reveals that while both SPWM methods significantly curtail harmonics, the unipolar SPWM inverter exhibits a more uniform THD reduction across the entire modulation range. Conversely, the bipolar SPWM inverter, though starting with higher THD levels, demonstrates a drastic reduction as modulation index increase, especially when enhanced by the application of an LC low-pass filter. This filter is instrumental in further refining the inverter's output, achieving impressively low THD values below 1% at full modulation, and ensuring a high-quality sinusoidal AC waveform. The comparative results accentuate the nuanced performance differences between the two SPWM strategies and underscore the critical role of LC filters in optimizing inverter output for a variety of power applications.

This study presents an innovative battery management strategy for cathodic protection systems fueled by photovoltaic sources. Addressing the corrosion of vital structures such as pipelines, the integration of photovoltaic generators offers a dynamic solution. The system encompasses a 640Ah Lithium-Ion battery, a supervisory control module, and three operational switches (“Charging”, “Direct”, “Discharging”). Through derived equations, the battery’s charging and discharging behaviors are meticulously examined based on photovoltaic and battery power interactions. Simulation results validate the effectiveness of the Maximum Power Point Tracking (MPPT) control mechanism and underscore the supervisory module’s significance in protecting battery health and fortifying cathodic protection. This research underscores the pivotal role of efficient battery management in prolonging battery life and ensuring steadfast pipeline safeguarding. By harmonizing photovoltaic energy, supervisory control, and battery management, this approach presents a robust and sustainable avenue for energy optimization within cathodic protection systems.

The principal technology investigated here is a “Polymer-Electrolyte Membrane (PEMFC)” fuel cell stack, which is used to power a DC motor without a brush (BLDC). In order to regulate the current and speed of brushless DC motors, this work presents a back-calculation method specifically made for anti-wind-up controllers. The performance of the proposed controller is analyzed via simulated operations at varying operational settings, such as with varying reference speeds. The proposed controller is compared to the standard proportional-integral (PI) controller in terms of overshoot, errors, rise times, and settling times. Matlab/Simulink is used to model the system, allowing us to see how the suggested brushless DC motor reacts to the proposed controller.

The use of clean energy has now become a major concern for every society. Their relevance is strongly influenced by the economic impact of the facilities and their environmental, social and economic benefits compared to conventional energy sources, particularly fossil fuels (coal, gas, oil, etc.) As the global demand for sustainable energy solutions continues to rise, the integration of renewable energy sources into various sectors becomes increasingly important. This feasibility study focuses on the integration of photovoltaic (PV) systems in the greenhouse structures of Zina Fresh, a company specialized in production and export of cherry tomatoes. To achieve this, RETScreen Expert software is used to validate the techno-economic and environmental sustainability of installing a grid-connected solar photovoltaic system in the company. Climatic data from the National Aeronautics and Space Administration (NASA) for the various locations and some financial parameters were used for the assessment. From the result, all the selected locations are recommended for solar photovoltaic project from all the available indices. The annual electrical potential of the installation amounts to 430 MWh for the first year, the best payback period of 6.7 years and the maximum GHG emission reduction of 184 tons of CO2 which is equivalent to 16.9 ha of forest absorbing carbon.