Detecting and locating high impedance faults (HIF) in overhead distribution networks (ODN) remains one of the biggest challenges for manufacturers and researchers due to the complexity of this phenomenon, where the electrical current magnitude is similar to that of the loads. To simulate HIF, the selection of the HIF model is important, because it has to correctly reproduce the characteristics of this phenomenon, so that it does not negatively influence the simulations results. Therefore, HIF models play a fundamental role in proposing solutions and validating the effectiveness of the proposed methods to detect and localize HIF in ODN. This paper presents a systematic review of HIF models. It is intended to facilitate the selection of the HIF model to be considered. The models are validated based on experimental data from medium voltage (MV) laboratories, specifically, recorded waveforms from two HIF tests conducted in an MV lab were analyzed and compared with three established HIF models. The efficacy of these models was assessed against MV lab test data to ensure a precise representation of both transient and steady-state conditions for fault conductance and current waveforms. The findings show that the two nonlinear resistor models better approximate the waveforms obtained in the experimental tests performed in this study.

High impedance faults (HIFs) detection in overhead distribution networks have been a major challenge for utility engineers for a long time. The current flowing to ground path is so low that conventional protection does not detect HIFs. The problem becomes more critical when HIFs occur in rural feeders with many single-wire earth return networks, since the neutral protection is usually set above the normal unbalance current of the circuit to avoid its undue actuation, limiting the sensitivity of this protection for single phase-to-ground faults. Methods based on harmonic content analysis for HIF detection stand out for their simplicity, practicality, and ease of implementation. However, so that such methods do not present reliability issues, the harmonic indices thresholds need to be well adjusted, reconciling dependability and security of the HIF detection function. This paper presents a study of the harmonic components presents in the HIF current waveforms, obtained through experimental tests in a 13,8 kV distribution network, using Fast Fourier Transform. The study analyzed the harmonic components of the current waveforms recorded on a SEL-751 relay in 74 FAI events.

The detection and localisation of high impedance faults (HIFs) in overhead distribution networks, particularly those caused by tree contact, remain challenging due to their low fault current magnitude, nonlinear behaviour, and high waveform variability. This study addresses these challenges by experimentally validating and parameterising a two‐variable‐resistor series model for HIFs. Controlled tests were conducted at the 13.8 kV Extra High Voltage Laboratory (LEAT) of the Federal University of Pará (UFPA), Brazil, using three tree types to collect waveform data. The faults were modelled in ATPDraw software and validated through waveform comparisons, achieving an R ² coefficient above 0.89, demonstrating excellent agreement between simulated and measured signals. Additionally, comprehensive parameterised data tables detailing resistance variations over time and voltage are provided. These findings not only reduce the need for costly experimental setups in early‐stage studies but also provide a solid foundation for developing and testing advanced HIF detection and localisation algorithms, thus contributing to improved power distribution system reliability.

In recent years, renewable energy sources have experienced significant growth within power systems. However, their high penetration levels in localized areas can lead to operational challenges such as reverse power flows in distribution lines and voltage violations along distribution networks. As a result, assessing the hosting capacity of distribution systems has become essential to ensure the safe and effective integration of renewable energy. This study presents a bibliometric analysis, with a Honduran perspective, aimed at identifying and categorizing the optimization methods employed to evaluate hosting capacity in distribution networks. In addition, it explores the practical measures adopted to mitigate the consequences of unregulated photovoltaic integration, including advanced inverter functions such as volt-watt and volt-var control, as well as network solutions like on-load tap changers. By analyzing past research contributions and mitigation efforts, the study seeks to inform future strategies that foster the development of more efficient, resilient, and sustainable electrical systems capable of supporting high levels of distributed generation.

In recent years, renewable energies have experienced exponential growth in power systems. However, an excess of renewable energy in a specific area can generate reverse power flows in transmission lines, overvoltages, and overloads. Therefore, analyzing the hosting capacity in distribution systems is essential to ensure the proper integration of renewable energies into the distribution network. Initially, an IEEE 13-Bus Distribution Network was selected and modeled using OpenDSS software, and through the integration of Python with OpenDSS, a binary search algorithm was applied to determine the hosting capacity at each node. The results show that hosting capacity decreases as the distance from the substation increases and is higher when closer to it. Additionally, they reveal that high levels of uncontrolled renewable energy penetration can compromise the reliability of the electrical grid by exceeding critical technical limits, such as the current-carrying capacity of conductors, transformer overloads, and over-voltages. Based on the proposed methodology, it is possible to increase the hosting capacity of distribution networks with a proper integration strategy by monitoring the growth of renewable energy.

High Impedance Faults (HIF) are serious disturbances that occur in power distribution systems. Due to the low current levels, conventional overcurrent-based protection systems do not detect this type of fault. Some studies have been carried out in the diagnosis of this type of disorder in order to accelerate their detection and location, reducing the risk to people, environment, property, and damage to utilities. A HIF computational model that is faithful to the real characteristics influences decisively model-based HIF detection and localization tasks. In this paper, a HIF model widely used in the literature is the first time confronted with real oscillography data captured during actual HIF incidents in overhead distribution networks. The results show that the measured steady-state current signals match the HIF model.