This paper introduces the Efficient Metaheuristic BitTorrent (EM-BT) algorithm, aimed at optimizing the placement and sizing of photovoltaic renewable energy sources (PVRES) and capacitor banks (CBs) in electric distribution networks. The main goal is to minimize energy losses and enhance voltage stability over 24 h, taking into account varying load profiles, solar irradiance, and temperature effects. The algorithm is rigorously tested on standard distribution networks, including the IEEE 33, IEEE 69, and ZB-ALG-Hassi Sida 157-bus systems. The results reveal that EM-BT outperforms established methods like Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA), demonstrating its effectiveness in reducing energy losses and maintaining stable voltage profiles. By effectively combining PVRES and CBs, this research highlights a robust approach to enhancing both technical performance and operational reliability in distribution systems. Additionally, the consideration of temperature effects on PVRES efficiency adds depth to the study, making it a valuable contribution to the field of power system optimization.

In this study, we present a comprehensive optimization framework employing the Multi-Objective Multi-Verse Optimization (MOMVO) algorithm for the optimal integration of Distributed Generations (DGs) and Capacitor Banks (CBs) into electrical distribution networks. Designed with the dual objectives of minimizing energy losses and voltage deviations, this framework significantly enhances the operational efficiency and reliability of the network. Rigorous simulations on the standard IEEE 33-bus and IEEE 69-bus test systems underscore the effectiveness of the MOMVO algorithm, demonstrating up to a 47% reduction in energy losses and up to a 55% improvement in voltage stability. Comparative analysis highlights MOMVO's superiority in terms of convergence speed and solution quality over leading algorithms such as the Multi-Objective Jellyfish Search (MOJS), Multi-Objective Flower Pollination Algorithm (MOFPA), and Multi-Objective Lichtenberg Algorithm (MOLA). The efficacy of the study is particularly evident in the identification of the best compromise solutions using MOMVO. For the IEEE 33 network, the application of MOMVO led to a significant 47.58% reduction in daily energy loss and enhanced voltage profile stability from 0.89 to 0.94 pu. Additionally, it realized a 36.97% decrease in the annual cost of energy losses, highlighting substantial economic benefits. For the larger IEEE 69 network, MOMVO achieved a remarkable 50.15% reduction in energy loss and improved voltage profiles from 0.89 to 0.93 pu, accompanied by a 47.59% reduction in the annual cost of energy losses. These results not only confirm the robustness of the MOMVO algorithm in optimizing technical and economic efficiencies but also underline the potential of advanced optimization techniques in facilitating the sustainable integration of renewable energy resources into existing power infrastructures. This research significantly contributes to the field of electrical distribution network optimization, paving the way for future advancements in renewable energy integration and optimization techniques for enhanced system efficiency, reliability, and sustainability.

Recent advancements in renewable energy technologies, alongside changes in utility infrastructure and progressive government policies, have bolstered the integration of renewable-based distributed generation units within distribution systems. This paper introduces the Energy Valley Optimizer, a novel tool designed for the strategic placement of distributed generation units and capacitor banks. This placement is crucial not only for optimizing energy loss and enhancing bus voltage stability but also for promoting sustainable energy use and reducing environmental impact over the long term. By minimizing energy loss and voltage fluctuations, the optimizer contributes to a more sustainable and resilient energy system. It achieves this through the optimal allocation of resources across various load patterns within a 24 h period and is tested on the ALG-AB-Hassi-Sida 157-bus distribution network in South Algeria. Comparative analysis with existing algorithms—such as the Liver Cancer Algorithm, Walrus Optimization Algorithm, and Zebra Optimization Algorithm—demonstrates the superior performance of the Energy Valley Optimizer. It not only enhances technical and economic efficiencies but also significantly lowers the total cost of energy over 24 years, thus supporting sustainable development goals in energy management.

This paper explores the electric field distribution near a string of six NJ120 high voltage insulators through experimental measurements under various conditions. Using a distributed capacitance method with custom probes connected to an Arduino-based system, tests were conducted on clean and polluted insulators. Pollution was simulated using a tuf-based solution with conductivities ranging from 0.5 to 1.97 mS/cm. Measurements were taken at 13 heights and four distances (1 to1.75 m) under applied AC voltages of 15 to 80 kV. The study also investigates the effects of damaged insulators, placed at different positions (near the high voltage terminal, in the middle, and near the ground), as well as the role of guard rings in improving field uniformity. Results indicate that pollution and damaged insulators significantly increased field intensity, particularly near the high voltage terminal. Guard rings effectively reduced field peaks, with larger radii and optimal placement providing the best performance. These findings contribute to optimizing high voltage insulator design for enhanced reliability.

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Introduction. This paper delves into the practical application of multilevel technology, particularly focusing on the capacitor-clamped converter as a promising solution for medium-to-high voltage power conversion, with specific emphasis on direct AC-AC switching conditions. Problem. The limitations of conventional single-cell matrix converters (MC) in efficiency and performance for medium-to-high voltage power conversion applications are well-recognized. Goal. The primary objective is to investigate the performance of the 3 phase modular multilevel matrix converter (3MC) with three flying capacitors (FCs) modeling. This investigation utilizes the Venturini method for gate pulse generation, aiming to compare the performance of the 3MC with standard converter designs. Methodology. To achieve the research goal, the Venturini method is adopted for generating gate pulses for the 3MC, representing a departure from conventional approaches. Detailed simulations employing MATLAB/Simulink are conducted to comprehensively evaluate the performance of the 3MC in comparison to conventional converter designs. Results. The simulation outcomes reveal a significant reduction of 73 % in total harmonic distortion (THD) achieved by the 3MC. This reduction in THD indicates improved robustness and suitability for medium-to-high voltage power conversion systems necessitating direct AC-AC conversion. These results highlight the efficacy of the 3MC in enhancing power conversion efficiency and overall performance. Originality. This paper contributes novel insights into the practical implementation of multilevel technology, particularly within the realm of capacitor-clamped converters. Furthermore, the utilization of the Venturini method for gate pulse generation in the 3MC represents an original approach to enhancing converter performance. Practical value. The research findings present significant advancements in multilevel transformer technology, offering valuable guidance for optimizing transformer design in various industrial and renewable energy applications. These contributions serve to enhance the development of reliable and efficient power systems, addressing critical needs in the energy sector. References 54, tables 3, figures 4.