Publication date: 15/09/2023

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Summary: Our planet is powered by energy, and it is increasingly necessary to adapt to the growing demand, especially when it comes to electrical energy. It happens that a large part of the population is unaware of the source or origin of energy generation. However, with discussions about the environmental damage caused by polluting sources, particularly those derived from fossil fuels, the energy market has been seeking solutions and alternatives that have a lesser impact on the environment. In this way, there has been a strong demand for renewable sources of electrical energy, leading to advancements in various areas, including Distributed Generation (DG), which represents an alternative model of electricity generation/distribution compared to the centralized power supply system. Despite offering various benefits, the increased integration of DGs can directly impact the operation of distribution networks, altering parameters related to voltage profile, system stability, and short-circuit levels. Among the technologies that implement this model is photovoltaics, which allows for propagation and competitiveness compared to other sources, especially in Brazil due to its favorable conditions for harnessing this type of energy. In this study, two scenarios will be analyzed. In the first scenario, an assessment of current variability in a distribution network within the IEEE 13-bus system was conducted using a simplified model of photovoltaic generators. Regarding the demand of the system loads, the power levels supplied by the generators were adjusted based on load curve data and specific meteorological conditions from two regions with
different climatic profiles, referred to as Region 1 and Region 2. In the second scenario, a heuristic technique was used to allocate photovoltaic generators within the IEEE 33-bus distribution system to adjust the voltage profile in accordance with PRODIST/ANEEL regulations and reduce losses in the system. For this purpose, Probabilistic Power Flow was employed with the assistance of the Monte Carlo method to introduce uncertainties in generation. In both cases, the methodology proved to be efficient. In the 13-bus feeder, it was shown that DG can directly impact the current levels of the feeder, with maximum variations of 94.08% and 90.66% for each of the two regions analyzed. In the 33-bus system, there was an improvement in the voltage profile and a significant reduction in losses in the system, around 35%.

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