Avaliação do impacto da microgeração fotovoltaica na rede de distribuição de energia elétrica

• Autor(a) principal: Paixão, Joelson Lopes da
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• Texto Completo: http://repositorio.ufsm.br/handle/1/18803
• topic: Geração distribuída; Geração fotovoltaica; Rede de distribuição; Lógica fuzzy; Método de Monte Carlo; Dispersed generation; Photovoltaic generation; Distribution’s grid; Fuzzy logic; Monte Carlo method; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

The sources that make up the global energy matrix have been diversifying due to the emergence of efforts to replace polluting sources with alternative sources such as wind, photovoltaic and biomass. In Brazil, Normative Resolution No. 482 of 2012, of the National Electric Energy Agency (ANEEL), established the general conditions of access to microgeneration and mining distributed to the electricity distribution system (EDS) and to the energy compensation system power. Following this resolution and some government policies, the integration of the Dispersed Photovoltaic Generation (DPG) in the electric system began to be viable and its participation tends to increase in the next years. In 2015, Normative Resolution No. 482 was modified by No. 687. In this scenario of expansion of the DPG installation, it is necessary to estimate its potential for entry, as well as to assess the impact it will have on the EDS, to adapt it if necessary, and make planning more reliable, reflecting the reality of the system. Thus, the objective of this dissertation is to perform the analysis of the behavior of the network of a distributor, in the south of Brazil, considering the integration of the DPG in the distribution network. The modeling of the elements that compose the network, the loads, the DPG units and the simulations are performed in the OpenDSS software. The evaluation of the probability and percentage of insertion of the DPG units is done through a Fuzzy Inference System (FIS). This FIS allows the elaboration of integration scenarios based on the combination of factors that favor or not the implantation of photovoltaic generation (PG), such as trends in the electric sector (energy price), cost of PVS, attractiveness of the DPG and the time of return on investment. To define daily PG profiles, typical annual stratified generation curves obtained from the Monte Carlo Method (MCM) are used for a set of measurements performed on a 1 kWp test system installed in the study region. As the PG is variable and difficult to predict, the generation curves adopted in the simulations contemplate the scenarios with the highest probability of occurrence. In the case study, the simulations are performed considering the annual seasonality of the PG, with typical load curves for residential consumers on weekdays and weekends. From the simulations, feeder load curves, grid voltage profiles, power consumed, feeder losses and metrics are applied to the load curves. The study showed that the greatest variations in voltage and energy consumption levels occur in the spring and summer because the average solar radiation is more intense. With high percentages of DPG penetration (18% and/or 25%), there are periods in which reverse power flow occurs in the feeder and the network voltage drop profile is reduced. The DPG was also able to reduce peak loads during the day, as well as reduce the total energy consumed and the losses in the network. No overload, undervoltage or overvoltage were observed.