This paper presents a detailed comparative analysis of conventional and AI-driven Maximum Power Point Tracking (MPPT) techniques utilized in photovoltaic (PV) systems. The study evaluates Fuzzy Logic Control (FLC) methods, the incremental conductance (INC) method, Perturb and Observe (P&O) methods with both fixed and variable step sizes, and the Simplified Model-Based State Estimation (SMSE-based) method. All simulations were rigorously conducted in the MATLAB/SIMULINK for ensuring consistent application of each technique, enabling a comprehensive comparison of their performance across various solar irradiance conditions. Results show that despite initial high oscillations, the SMSE-based method efficiently reaches the Maximum Power Point (MPP) with efficiency values of up to 99.9%. Fuzzy Logic Control Set-2 demonstrates exceptional performance with minimal oscillations and high …

This paper presents the use of a static synchronous compensators (STATCOM) device to improve the low voltage ride through (LVRT) ability of an electrical network consisting of wind farms that produce 9 MW and 1 MW PV stations during grid faults. A hybrid energy model is connected with 100 MVAR STATCOM at the point of common coupling (PCC) through line to line fault occurs on the grid. STATCOM control is used to detect the voltage at the PCC bus through occurring line to line (LL) faults by compensating reactive energy. A method of particle swarm optimization (PSO) is utilized for adjusting the optimum value of proportional—integral—derivative (PID) STATCOM control. STATCOM is controlled by (PID) and is compared with STATCOM controlled by fuzzy logic control (FLC). The proposed system has been performed utilizing Matlab/Simulink. Results of the simulation clear effectiveness and the ability of …

This paper introduces the enhancement of Visible Light Communications (VLC) for V2V using artificial intelligence models. Different V2V scenarios are simulated. The first scenario considers a specific longitudinal separation and a variable lateral shift between vehicles. The second scenario assumes random longitudinal separation and a specific lateral shift between vehicles. Significant obstacles that impair performance and dependability in V2V communication systems include bit errors, high power consumption, and interference. By combining Convolutional Neural Networks (CNNs), Generative Adversarial Network (GAN), Gated Recurrent Unit (GRU), and Deep Denoising Autoencoder (DDAE), this paper suggests a deep learning-based system to address these issues. The framework comprises four modules, a power reduction module that uses a GAN to generate low-power signals while maintaining signal …

rc welding power supplies play a critical role in the welding process by providing the necessary electrical power, control, and stability required to produce high-quality welds efficiently and safely. Investing in a high-quality welding power supply is essential for achieving optimal welding results and maximizing productivity in various welding applications. By incorporating these control techniques into arc welding power circuits, manufacturers can deliver versatile, efficient, and user-friendly power supplies that meet the diverse needs of welders across different industries and applications. These control techniques play a crucial role in achieving consistent weld quality, optimizing productivity, and ensuring operator safety in the welding process. A detailed overview of power circuit topologies and control techniques specifically tailored for welding power supply application was provided. It delves into the intricate design …

This study presents an integrated techno-economic, environmental, and sensitivity analysis of hybrid photovoltaic (PV) and wind energy systems designed to supply a peak load of 3.5 MVA to a remote tourist resort in Ras Al-Hekma City, Egypt. Multiple configurations; PV- and wind-based; were examined, each incorporating combinations of battery storage (BS), fuel cells (FC), and hybrid FC/BS systems under off-grid conditions. The assessment evaluates system performance, cost of energy (COE), capital and operational expenditures, and resilience across different scenarios using real-site solar and wind resource data. Among PV-based systems, the PV/BS configuration demonstrated the lowest COE at $0.076/kWh, offering simplicity and economic efficiency, while the PV/FC/BS setup provided a balanced trade-off between reliability and cost. For wind-based systems, Wind/BS achieved the lowest COE at $0.067/kWh, making it the most cost-effective, whereas Wind/FC/BS offered the highest resilience at a higher cost. A comprehensive sensitivity analysis identified solar irradiance, wind speed, and component costs as the most influential parameters affecting system performance and COE. The findings underscore the feasibility of deploying hybrid renewable energy systems in coastal, off-grid locations and contribute to Egypt’s strategic goals for renewable energy integration and sustainable development.

The increasing global demand for clean water and sustainable energy solutions has driven the exploration of hybrid renewable energy systems for desalination applications. This study investigates the optimal sizing of a stand-alone hybrid energy system comprising photovoltaic (PV) panels, fuel cells (FC), and battery storage (BS) to power a seawater desalination (SD) plant and meet the electrical load of a tourist resort in Ras Al-Hekma City, Egypt. The resort's total electrical demand of 3.5 MVA includes a reverse osmosis (RO) desalination plant, lighting, air conditioning, and a wastewater treatment facility. Three system configurations; PV/BS, PV/FC, and PV/FC/BS; were analyzed to determine the most cost-effective and reliable solution. The performance of each system was evaluated based on energy production, storage requirements, and economic metrics such as the cost of energy (COE) and net present cost (NPC). Results indicate that the PV/FC/BS hybrid system offers a balanced solution with a COE of 0.081 $/kWh, combining the reliability of fuel cells with the sustainability of solar energy and battery storage. This research highlights the potential of hybrid renewable energy systems to address water scarcity and energy challenges in remote coastal regions while contributing to Egypt's renewable energy goals.

Reliable multilevel inverter IGBT modules require precise loss and heat management, particularly in severe traction applications. This paper presents a comprehensive modeling framework for three-level T-type neutral-point clamped (TNPC) inverters using a high-power Insulated Gate Bipolar Transistor (IGBT) module that combines model predictive control (MPC) with space vector pulse width modulation (SVPWM). The particle swarm optimization (PSO) algorithm is used to methodically tune the MPC cost function weights for minimization, while achieving a balance between output current tracking, stabilization of the neutral-point voltage, and, consequently, a uniform distribution of thermal stress. The proposed SVPWM-MPC algorithm selects optimal switching states, which are then utilized in a chip-level loss model coupled with a Cauer RC thermal network to predict transient chip-level junction temperatures dynamically. The proposed framework is executed in MATLAB R2024b and validated with experiments, and the SemiSel industrial thermal simulation tool, demonstrating both control effectiveness and accuracy of the electro-thermal model. The results demonstrate that the proposed control method can sustain neutral-point voltage imbalance of less than 0.45% when operating at 25% load and approximately 1% under full load working conditions, while accomplishing a uniform junction temperature profile in all inverter legs across different working conditions. Moreover, the results indicate that the proposed control and modeling structure is an effective and common-sense way to perform coordinated electrical and thermal management, effectively allowing for predesign and reliability testing of high-power TNPC inverters.