In recent modern power systems, the number of renewable energy systems (RESs) and nonlinear loads have become more prevalent. When these systems are connected to the electricity grid, they may face new difficulties and issues such as harmonics and non-standard voltage. The proposed study suggests the application of a whale optimization algorithm (WOA) based on a fractional-order proportional-integral controller (FOPIC) for unified power quality conditioner (UPQC) and STATCOM tools. These operate best with the help of their improved control system, to increase the system’s reliability and fast dynamic response, and to decrease the total harmonic distortion (THD) for enhancing the power quality (PQ). In this article, three different configurations are studied and assessed, namely: (C₁) WOA-based FOPIC for UPQC, (C₂) WOA-based FOPIC for STATCOM, and (C₃) system without FACTS, i.e., base case, to mitigate the mentioned drawbacks. C₃ is also considered as a base case to highlight the main benefits of C₁ and C₂ in improving the PQ by reducing the %THD of the voltage and current system and improving the systems’ voltage waveforms. With C₂, voltage fluctuation is decreased by 98%, but it nearly disappears in C₁ during normal conditions. Additionally, during the fault period, voltage distortion is reduced by 95% and 100% with C₂ and C₁, respectively. Furthermore, when comparing C₁ to C₂ and C₃ under regular conditions, the percentage reduction in THD is remarkable. In addition, C₁ eliminates the need for voltage sag, and harmonic and current harmonic detectors, and it helps to streamline the control approach and boost control precision. The modeling and simulation of the prepared system are performed by MATLAB/Simulink. Finally, it can be concluded that the acquired results are very interesting and helpful in the recovery to the steady state of wind systems and nonlinear loads, thereby increasing their grid connection capabilities.

Solar energy, a prominent renewable resource, relies on photovoltaic systems (PVS) to capture energy efficiently. The challenge lies in maximizing power generation, which fluctuates due to changing environmental conditions like irradiance and temperature. Maximum Power Point Tracking (MPPT) techniques have been developed to optimize PVS output. Among these, the incremental conductance (INC) method is widely recognized. However, adapting INC to varying environmental conditions remains a challenge. This study introduces an innovative approach to adaptive MPPT for grid-connected PVS, enhancing classical INC by integrating a PID controller updated through a fuzzy self-tuning controller (INC-FST). INC-FST dynamically regulates the boost converter signal, connecting the PVS’s DC output to the grid-connected inverter. A comprehensive evaluation, comparing the proposed adaptive MPPT technique (INC-FST) with conventional MPPT methods such as INC, Perturb & Observe (P&O), and INC Fuzzy Logic (INC-FL), was conducted. Metrics assessed include current, voltage, efficiency, power, and DC bus voltage under different climate scenarios. The proposed MPPT-INC-FST algorithm demonstrated superior efficiency, achieving 99.80%, 99.76%, and 99.73% for three distinct climate scenarios. Furthermore, the comparative analysis highlighted its precision in terms of control indices, minimizing overshoot, reducing rise time, and maximizing PVS power output.

In Egypt, the climate has a direct impact on the dried date fruit production. The traditional drying method or open sun drying (OSD) leads to pollution of the final product caused by sand-laden winds, rain, or animals and harmful insects, etc. This study is aimed at designing, implementing, and experimentally validating a solar dryer based on IoT technology and integrated with a PV system in Aswan, Egypt. The purpose of the dryer is to monitor and control the quality of the three most popular date fruit varieties and determine the most effective drying method, with an algorithm that operates the system automatically for optimal performance and high-quality products. The automatic solar dryer (ASD) significantly affects the final moisture content and color characteristics and reaches the equilibrium moisture content (EMC) at a faster rate for dried date samples compared to the OSD. The drying rate of ASD was 29.03% (Sakkoti), 31.04% (Malkabi), and 25.49% (Gondaila) higher than OSD. Also, the dried date fruit samples reached EMC on the ASD after 8 days for both Malkabi and Gondaila and 9 days for Sakkoti, while it took 14 to 15 days on OSD. The maximum open circuit voltage , short circuit current , and output power were 41.70 V, 8.84 A, and 365.09 W, respectively. All values of total color change () after open-air drying of dry date varieties were higher than solar drying for both drying systems. This study can be then more helpful for producers of dried foods.

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.

The Single-Phase Induction Motor (SPIM) has gained widespread adoption in various power applications. This article introduces a new study and analysis of SPIM, focusing on its high-frequency (HF) modeling within the conducted electromagnetic interference (EMI) frequency range of interest (150 kHz– 30MHz). This research is crucial for ensuring electromagnetic compatibility (EMC), evaluating electromagnetic interference issues, optimizing machine design, and complying with EMC standards. To identify common-mode current propagation paths accurately, a precise impedance analyzer is required to determine the common-mode impedances models of the high-frequency motor. The article proposes an HF modeling method based on a genetic algorithm (GA), which offers the advantages of high accuracy, versatility, and fast simulation time. This approach effectively reproduces models, trends, and relationships observed in real data, indicating a high level of fidelity and reliability in its predictions. Case studies validate the efficiency of the proposed HF modeling method. These precise predictions of undesired HF phenomena provide valuable insights into identifying areas where parasitic currents may propagate in the motor and understanding the impact of each motor phase on the overall behavior of the motor’s common-mode impedance.