The need to evolve cleaner, decentralized, and digitalized energy distribution systems and services includes the electrification of means of transport as Electric Vehicles (EVs) achieve a greater market share. In this context, this work presents and applies, through a case study, the proposal of a new methodology for calculating the hosting capacity of EVs in low- and medium-voltage distribution systems. The proposal of a new methodology that combines deterministic and stochastic methods, while considering several operational criteria, as well as being applicable in both low and medium voltage, shows itself as a more germane and innovate approach. The results obtained demonstrated that the hosting capacity of EVs for the transformers pertinent to the distribution system under study is 100% for more than 50% of the simulations performed. The conductor overload criterion is the main limiting factor, representing 36.69% of violations for the 3.6 kW charger and 52.14% for the 7 kW charger. According to the executed evaluated projections, the distribution system under investigation will posses the capacity to host the growth of EVs in any of the scenarios presented in this study until 2025 for the 3.6 kW charger.

High impedance faults (HIFs) have been a major concern for protecting distribution systems and public safety hazards when involving downed conductors. The deployment of smarter grids brings new technologies for smart monitoring, automation, and protection of distribution networks. This paper presents a new method for a series of HIF detection and location in primary distribution feeders, using voltage unbalance measurements collected from smart meters (SMs) installed at low-voltage end-users. The methodology was tested in MATLAB and Simulink through steady-state simulations of a typical 13.8 kV distribution system, under load unbalance and different fault scenarios. Results show that the proposed method is robust and accurate for the detection of blown fuses and broken conductors, with or without ground faults, located either at the source or the load-side. The ease of implementation in SM design, formulation of parameters, and reliable simulation results show potential real-life applications.

The dynamic control of the power generation system is one of the most important elements in an offshore platform, since it is responsible for maintaining the electrical system stability both in steady‐state and transient operation, thus avoiding the complete loss of power supply and, consequently, large economic losses. In this regard, the Real-Time Digital Simulator (RTDS) becomes an important tool, as it allows to simulate the generation system dynamic in real-time with the possibility of testing actual control and protection devices, through a hardware-in-the-loop scheme. Typically, offline simulation studies of the generator dynamic control are carried out with limited information from manufacturers, which leads to the use of typical data for models and, therefore, the obtention of unreliable responses. However, to obtain a realistic behavior of the electrical system dynamic in the RTDS, an accurate representation of its models is necessary. In this sense, this paper presents the dynamic control validation process of the power generation system of an oil extraction platform in the RTDS, through the use of field data, such as actual regulators' parameters and field tests records. Several simulations of transient phenomena were carried out and the dynamic responses of speed and voltage regulators were analyzed. Comparative analysis between field and laboratory test results demonstrates the validation of the simulation model developed in the RTDS.