Modelo de gestión energética en micro redes

Abstract

Energy management is a tool for optimizing the use of electrical energy, so that it is distributed efficiently, through adjustments in the generation and / or demand for electrical energy. This undergraduate work is a review of the state of the art in energy objectives and policies related to energy management implemented or projected in countries such as Germany, the United States, China, Poland and some Latin American countries, Argentina, Colombia, Ecuador, Chile and Peru, as well as a review of the mathematical methods used in energy management in microgrids and the elements of distributed energy resources involved in the studies. Based on the bibliographic review, a six-step energy management methodology is proposed, with the aim of evaluating the feasibility of using microgrids based on the evaluation of wind and solar energy generation in non-interconnected areas (ZNI) of Colombia. The proposed methodology is based on the predictive model and uses the use of artificial intelligence through two types of artificial neural networks to modify the generation potential of renewable energy sources (wind and solar). (RNA) Feed-Forward and Layer Recurrent. As a base data methodology use information of 10-year historical meteorological data. The proposed methodology is applied to a case study, from the Tumaco-Nariño region (Colombia), to assess whether the energy density of the area is sufficient for a town with a demand of 207 kW-month. Matlab 2017b was analyzed as software to perform the calculations and in RNA training. The results of the case study presented a feasibility evaluation for the implementation of a microgrid in the ZNI with the participation of solar and wind energy sources.