Análise dos impactos na energia incidente em redes de distribuição com elevada integração de geração distribuída fotovoltaica - Bravim, Matheus dos Reis (2023)
The production of electricity from sources close to consumers is growing due, among other factors, to the growing global concern with the reduction of polluting gas emissions, the reduction in the cost of generation technologies, such as photovoltaics, and the economics benefits for the user. However, the addition of these sources can change the original power grid parameters such as power flow, voltage levels and short circuit levels. Power incident (EI) is one of the most important risks associated with arc flash and is related to short circuit current and fault clearing time. This study used OpenDSS and MATLAB® software to simulate 13-node and 34-node IEEE feeders in order to analyze the impact of high penetration distributed photovoltaic generation (GDFV) on original EI levels. Under the conditions of this study, the results observed that for any 13-node feeder the EI increased for the same arc elimination time by up to 5% compared to the scenario without GDFV integration, indicating an increased risk associated with burns from electric arcs. For the 34-node feeder, EI levels and arc limiting distance (AFB) were reduced by up to 32% compared to the scenario without GDFV integration, indicating that the GDFV integration can contribute to the reduction of risks associated with the electric arc. In those cases, variations in EI did not require alteration (increase or reduction) of the category of personal protective equipment (PPE) flame retardant in relation to the original condition of the network (without integration of both GDFV). In addition, it was observed that the arc elimination time was a determining factor in the levels of EI, being responsible for large increases in EI and AFB as time increases. These results highlight the importance of simulation studies to map EI variation scenarios in feeders due to GDFV integration, in order to avoid scenarios with high maximum EI, which represent an increase in network risks, and to look for minimum EI scenarios to reap the benefits of risk mitigation.