The optimal allocation and size of decentralized generating units are essential to minimize power losses, while meeting the demand for active and reactive power in a distribution system. In other words, most of the total energy produced can be efficiently exploited by end users. In addition, if the DGs are of optimal size and location in the distribution system, the reliability, stability and efficiency of the power system are guaranteed. This paper focuses on reducing power losses and improving the voltage profile by accurately identifying the optimal location and sizing of Distributed Generation based on three indexes, namely the IVM Index Vector Method, the VDI Voltage Deviation Index and the VSI Voltage Stability Index. Two types of DGs were considered for the analysis: DGs operating with unit power factor and DGs operating with a lagging power factor. Three optimization algorithms are applied to determine the optimal sizes of decentralized generation units in a power distribution network which are GWO, WOA and PSO. The results obtained in this article show that the three algorithms give very similar values. DG at lagging power factor gives better results compared with those obtained with DGs at unity power factor. In terms of loss reduction and minimum bus voltage, the best results are obtained for the VSI index with a DG at a power factor of 0.9.

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.

Integrating large numbers of electric vehicles will lead to operational and planning difficulties for distribution networks. The installation of electric vehicle charging stations (EVCS) increases power losses, affects stability, and degrades the reliability of the distribution network, resulting in dissatisfaction among customers. This work describes the impacts of the integration of electric vehicle charging stations on power losses, voltage stability index, and the main reliability indices as a function of the position and size of electric vehicle charging stations. This investigation was carried out on the IEEE 33 bus test system. According to the results, a high concentration of EVs increases peak demand, leading to greater energy losses, adversely affecting stability, and degrading reliability indices of the distribution network. The choice of installation points for EVCS is therefore very important, as some points induce greater energy losses than others and affect stability and reliability more than others. Measures to mitigate the effects of EVCS installation on distribution networks are crucial.

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Integrating electric vehicle charging stations (EVCS) into the energy distribution network presents significant challenges. A wide range of work has been carried out to understand this possible impact and, in particular, to assess the loading capacity of distribution networks, with or without network management solutions. A high concentration of EVs can increase peak demand, leading to higher energy losses, voltage drops, etc., which can reduce the efficiency and reliability of power distribution. This article focuses on the impact of integrating EVCS into the power distribution network and the deployment of distributed generation (DG) to mitigate these challenges.In this study, the Whale Optimization Algorithm (WOA) and moth-flame optimization (MFO) are adopted to select the optimal size and location of distributed generation on the distribution network in the case of EVCS integration to reduce energy losses and improve the voltage profile. Analysis is carried out on the IEEE 33 bus distribution network.