Metodologia para análise da tarifa binômia para consumidores residenciais considerando microgeração distribuída

Abstract

In view of the continuous increase in the consumption of electricity in the country, due to the different climatic conditions due to the great territorial extension and the approximation of the maximum capacity of electric energy generation of its consumption, the electricity distributors were obliged to resort to thermoelectric plants to complement your amount of energy. Consequently, buying energy at a higher cost, being obliged to pass these values on to customers through the Tariff Flags, in addition to readjustments in the tariff itself. Concerned with the variation in the electricity tariff, many consumers have been looking for alternatives to reduce the economic impacts on their consumer units. Distributed microgeneration, in particular, photovoltaic solar energy is a relatively simple alternative and has been widely used by residential, commercial and even industrial consumers. The model known as net metering, used to regulate energy microgeneration systems in Brazil, together with the monomial tariff system, can generate a cross-subsidy between consumers from the same distributor. This phenomenon has generated discussions around the world, involving the application of a different tariff called binomial to microgenerators, in order to cover the fixed costs of distributors referring to these units. The eminent need for a revaluation of the tariff system due to new technologies implemented in the electricity sector, the proposed methodology considers a tariff model based on the maximum hourly demand, obtained by the load curves and divided by consumption classes. With data from typical homes, combined with the Hybrid Optimization Model for Eletric Renewables (HOMER) software, the main result is the technical and economic feasibility of applying the new tariff model, including data from consumers who own or intend to invest in Distributed Generation (GD). It should be noted that such analyzes are unprecedented in terms of the methodology developed and aim at financial balance between distributors and consumers. including data from consumers who own or intend to invest in Distributed Generation (GD). It should be noted that such analyzes are unprecedented in terms of the methodology developed and aim at financial balance between distributors and consumers. including data from consumers who own or intend to invest in Distributed Generation (GD). It should be noted that such analyzes are unprecedented in terms of the methodology developed and aim at financial balance between distributors and consumers.