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In recent years, regulating a wind energy conversion system (WECS) under fluctuating wind speed and enhancing the quality of the electricity provided to the grid has become a hard challenge for many academics. The current research provides a better control strategy to decrease the occurrence of chattering phenomena. Combined with the Maximum Power Point Tracking (MPPT) strategy and a pitch angle control, the control is possible to increase the performance and the efficiency of the Permanent Magnet Synchronous Generator (PMSG) based Wind Energy Conversion System. This study attempts initially to regulate the generator and the grid side converter to track the wind speed reference established by the MPPT algorithm. And secondly, to relieve the chattering problem associated with the conventional sliding mode control (CSMC), the proposed sliding mode control (PSMC) is based on a novel smooth continuous switching control. Besides, the suggested sliding mode control stability is confirmed using Lyapunov’s stability function. The complete system was evaluated in the MATLAB/Simulink (MathWorks, Natick, MA, USA) environment using a 2 MW PMSG’s power, under random fluctuations in the wind speed to show the suggested approach’s efficiency and robustness, which was then compared to the CSMC and other common approaches available in the literature. The simulation results reveal that the recommended sliding mode control approach delivers good speed, accuracy, stability, and output current’s ripple.

Wind energy conversion systems (WECSs) are considered green generators, environmentally friendly, and fully suitable energy sources to replace fossil energy sources. WECS’s output power is hugely dependent on the random nature of the wind. There are many solutions to improve the output power for WECSs, such as adjusting the profile of turbine blades, locating installation places, improving generators, etc. Nevertheless, maximum power point tracking (MPPT) algorithms for WECSs are optimal and the most effective because they are flexible in controlling different variable wind speeds and match all types of WECS. The parameters on the generator side control or the grid side control will be adjusted when MPPT algorithms are used, allowing the output power of WECSs to be maximized while maintaining stability in variable-speed wind. There are various MPPT algorithms, but the current problem is their efficiency and whether it requires deep knowledge to select the best MPPT solutions because each method has different advantages and disadvantages. This study has implemented an overview of modern maximum power tracking algorithms applied to permanent magnet synchronous generators in WECS with MPP methods based on speed convergence, efficiency, self-training, complexity, and measurement of wind parameters.

The present study evaluated the efficacy of pregnant mare serum gonadotropin (PMSG) and PMSG encapsulated in chitosan-tripolyphosphate nanoparticles in enhancing reproductive performance in short-term progesterone estrus-synchronized Ossimi ewes. Seventy-five healthy ewes were randomly assigned to three groups (  = 25 per group). Group 1 (representing current standard practice) received 25 mg progesterone acetate for 7 days, 600 IU PMSG on day 6, and 250 μg prostaglandin F (PGF ) on day 7. Group 2 followed the same regimen as Group 1, except for administering 300 IU of PMSG-loaded chitosan-tripolyphosphate nanoparticles on day 6, followed by an intramuscular injection of 250 μg PGF on day 7. Group 3 received 150 IU of PMSG-loaded chitosan-tripolyphosphate nanoparticles on day 6 and 250 μg PGF on day 7. Estrus detection occurred between days 7 and 11, with a gonadotropin-releasing hormone (GnRH) injection at breeding. Group 1 had a significantly shorter onset of estrus (54.40 ± 4.50 h;  < 0.05) compared to Group 2 (71.60 ± 0.51 h) and Group 3 (72.20 ± 4.81 h). Pregnancy and lambing rates were highest in Group 2 (100%;  < 0.05), and Group 2 produced more fetuses (40) than Group 1 (30) and Group 3 (25). Fecundity was also highest in Group 2 (160%;  < 0.05). Follicular diameter was greater in Group 2 on day 9, although the number of large follicles was similar across groups. The number of corpora lutea significantly increased on day 7 compared to day 0 in all groups. Progesterone levels peaked on day 7 and declined by day 9 across all groups. These results suggest that administering 300 IU of PMSG encapsulated in chitosan-tripolyphosphate nanoparticles can enhance reproductive performance more effectively than conventional PMSG, offering a promising strategy to improve fertility in short-term progesterone-synchronized ewes.

Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using Matlab®/Simulink®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.

With the rapidly increasing usage of renewable sources, especially wind power, maximizing the power produced from wind energy conversion system (WECS) has become a major concern. Various methods are utilized in the domain of wind turbine performance enhancement for tracking the maximum power point (MPP). Among them, the perturb and observe (P&O) approach is widely applied because of its straightforward implementation. Nevertheless, the primary drawback of this approach is the imprecision caused by variations at the peak power point. Consequently, due to wind’s arbitrary and complicated characteristics, using an intelligent optimization technique is compulsory as it can give effective tracking performance. In this study, a recently developed nature-inspired metaheuristic, termed the Greater Cane Rat Algorithm (GCRA), which emulates the cognitive foraging behavior of greater cane rats during and after the breeding season. The GCRA approach seeks to regulate the boost converter by computing the duty cycle value using the voltage and current variables. The Wind Energy Conversion System (WECS) incorporates a wind turbine, a Permanent Magnet Synchronous Generator (PMSG), a rectifier, and a DC/DC boost converter that is linked to a load. The wind system can track the maximum power via a mechanical sensorless tracker system without the need to connect an additional mechanical sensor. The suggested strategy is compared to various tracking methodologies, including the classical Perturb & Observe (P&O), Particle Swarm Optimization (PSO), and Gray Wolf Optimization (GWO). The obtained results, which have been executed in the environment of MATLAB/SIMULINK R2022b, illustrate that the proposed approach improves the performance of the tracking system under different wind profiles step, realistic, and ramp variation of the wind velocity. The proposed strategy outperforms a tracking efficiency that exceeds 99%, surpassing other considered tracking approaches, which are at 95.5%, 94.7%, and 91.4% with the least error ratio and the best tracking for the power coefficient ratio.

Wind energy plays a crucial role as a renewable source for electricity generation, especially in remote or isolated regions without access to the main power grid. The intermittent characteristics of wind energy make it essential to incorporate energy storage solutions to guarantee a consistent power supply. This study introduces the design, modeling, and control mechanisms of a self-sufficient wind energy conversion system (WECS) that utilizes a Permanent magnet synchronous generator (PMSG) in conjunction with a Water pumping storage station (WPS). The system employs Optimal torque control (OTC) to maximize power extraction from the wind turbine, achieving a peak power coefficient ( C p ) of 0.43. A vector control strategy is applied to the PMSG, maintaining the DC bus voltage at a regulated 465 V for stable system operation. The integrated WPS operates in both motor and generator modes, depending on the excess or shortfall of generated wind energy relative to load demand. In generator mode, the WPS supplements power when wind speeds are insufficient, while in motor mode, it stores excess energy by pumping water to an upper reservoir. Simulation results, conducted in MATLAB/Simulink, show that the system efficiently tracks maximum power points and regulates key parameters. For instance, the PMSG successfully maintains the reference quadrature current, achieving optimal torque and power output. The system’s response under varying wind speeds, with an average wind speed of 8 m/s, demonstrates that the generator speed closely follows turbine speed without a gearbox, leading to efficient power conversion. The results confirm the flexibility and robustness of the control strategies, ensuring continuous power delivery to the load. This makes the system a feasible solution for isolated, off-grid applications, contributing to advancements in renewable energy technologies and autonomous power generation systems.

As wind energy becomes more common in modern power networks, it is becoming more important to keep turbines running smoothly even when the grid is having major problems. This study examines the utilization of a Dynamic Voltage Restorer (DVR) within a Permanent Magnet Synchronous Generator (PMSG)-based grid-connected Wind Energy System (WES) to improve Low Voltage Ride-Through (LVRT) performance. The DVR reduces the consequences of grid faults by adding the right series compensation voltage, which brings the Point of Common Coupling (PCC) voltage back to its rated value. A significant contribution to this study is the creation of a cost-effective DVR configuration powered by the existing DC-link of the back-to-back converter (BTBC). This allows the DVR to draw the necessary active power during disturbances without needing an external Battery Energy Storage System (BESS). To improve dynamic responsiveness, a fuzzy logic controller is employed with the DVR feedforward control approach. This makes it better at rejecting disturbances. To keep the DC-link voltage stable during fault events, a brake chopper (BC) is also added. We use comprehensive simulations in MATLAB/Simulink R2024a to test the proposed system. The results show that the fuzzy-controlled DVR can quickly, smoothly, and reliably restore voltage in a variety of faulty conditions. This greatly improves the LVRT performance of PMSG-based WES. A comparative examination shows that the fuzzy-controlled DVR is better than the standard PI-based DVR when it comes to transient behavior, voltage regulation accuracy, and post-fault recovery. This makes the grid code more compliant, and the overall reliability of the system improved.

Magnetic gearboxes (MGs) are increasingly explored in wind turbines as a reliable alternative to mechanical gearboxes, which suffer failures and costly maintenance. By integrating MG with Permanent Magnet Synchronous Generator, an Integrated Pseudo-Direct-Drive PMSG (IPDD–PMSG) is achieved, offering higher efficiency, contact-free operation, and improved system reliability. The proposed design improved the performance of the IPDD–PMSG systems in torque and efficiency for 2 MW wind turbines . A multi-objective optimization is implemented to achieve maximum volumetric torque density (VTD) as well as minimum cost. Both Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) heuristics methods of optimization are investigated in order to reach the best algorithm. Results showed that GA offers better convergence and higher-performing solutions, while PSO ensures a greater diversity of cost/VTD trade-offs. Thus, the proposed methodology enables optimized and balanced design systems and offers a significant improvement in VTD and cost of the system. The finite element approach verifies the geometry using the variables found by optimization.

To address the DC-link voltage control issue in flywheel energy storage systems (FESSs), a DC-link voltage control strategy using a capacitor-energy-based super-twisting sliding mode controller (CE-STSMC), integrated with a disturbance observer, is proposed in this article. First, an exponential term is incorporated into the STSMC algorithm to enhance its convergence rate. Then, the improved STSMC is employed as the voltage-loop controller to mitigate the insufficient anti-disturbance capability of conventional control methods. To improve the system robustness, a nonlinear disturbance observer (NDOB) is developed to estimate the load power. The estimated disturbance is further feedforward-compensated into the improved STSMC controller. Finally, experiments are carried out on a 2.2 kW FESS prototype under DC-link voltage step and sudden load-change conditions, which demonstrates the effectiveness and superiority of the proposed control strategy.

The synergetic control technique (SCT) has the solution for understanding the symmetry inherent in the non-linear properties of wind turbines (WTs); therefore, they achieve excellent performance and enhance the operation of the WT. Small-scale WTs are efficient and cost-effective; they are usually installed close to where the generated electricity is used. This technology is gaining popularity worldwide for off-grid electricity generation, such as in rural homes, farms, small factories, and commercial properties. To enhance the efficiency of the WT, it is vital to operate the WT at its maximum power. This work proposes an efficient and fast maximum power point tracking (MPPT) technique based on the SCT to eradicate the drawbacks of the conventional methods and enhance the operation of the WT at the MPP regardless of wind speed and load changes. The SCT has advantages, such as robustness, simplified design, fast response, no requirement for knowledge of WT characteristics, no need for wind sensors or intricate power electronics, and straightforward implementation. Furthermore, it improves speed convergence with minimal steady-state oscillations at the MPP. The investigated configuration involves a wind-driven permanent magnet synchronous generator (PMSG), uncontrolled rectifier, boost converter, and variable load. The two converters are used to integrate the PMSG with the load. Three scenarios (step changes in wind speed, stochastic changes in wind speed, and variable electrical load) are studied to assess the SCT. The results prove a high performance of the suggested MPPT control method for a fast convergence speed, boosted WT efficacy, low oscillation levels, and applicability under a variety of environmental situations. This work used the MATLAB/Simulink program and was then implemented on a dSPACE 1104 control board to assess the efficacy of the SCT. Furthermore, experimental validation on a 1 kW Darrieus-type WT driving a PMSG was performed.