Estudo e desenvolvimento do uso de redes neurais artificiais para tomada de decisão no chaveamento de banco de baterias e compensação de crédito em unidades consumidoras com geração distribuída

Abstract

The use of Battery Banks is mostly done by users of the electricity grid who cannot or do not wish to be without energy supply in the event of a distribution failure by the concessionaire’s network. Thus, they are installed to meet the demand for energy when the supply is insufficient to do só. The idea of this work, however, is to use Battery Banks with a different purpose from their common applications and explore possible advantages of their use combined with distributed generation to achieve greater use of electrical energy, thus reducing its cost to the user. The Battery Bank, charged by photovoltaic energy, would not be activated only in the event of a lack of energy distribution by the concessionaire, but when the price of energy and consumption reached a combined maximum, with the intention of reducing the electricity bill. Allied to this idea, the work explores the normative resolution of ANEEL and the white tariff, which provides for a credit compensation system for the consumer, which will be used to automatically reduce the electricity bill of the consumer unit. Thus, the objective of the work is to decide to whether it is possible and feasible to implement a Distributed Generation together with a Battery Bank to significantly reduce the monthly cost of electricity for various consumer models. For the analysis and prediction of the switching of the battery bank, an artificial intelligence will be used in the development of the analysis that will weigh the parameters and conclude if it is possible to reduce costs significantly.