Modelo de balanço energético híbrido baseado em Programação Dinâmica Dual Estocástica

• Autor(a) principal: Santos, Jefferson Bezerra dos
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
• Texto Completo: https://repositorio.ufpb.br/jspui/handle/123456789/22535
• topic: Matemática computacional; Geração eólica; Geração de energia; Modelo hidrotérmico; Computational mathematics; Wind generation; Power generation; Hydrothermal model; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

With the increase in demand for electric energy, major technological advances they are indispensable for efficient growth. In Brazil, hydroelectric is the main source generation, however, due to the disproportionate increase in demand and the scarcity of rainfall, activation of thermoelectric plants has been necessary to supply the demand, having as main disadvantages the environmental damage is greater than other sources such as hydroelectric and the associated cost depending on the fuel used cause a price increase. Glimpsing the need to perform an adequate management of the energy dispatch, in order to minimize the generation costs and a reduction of the environmental impact, in this work a model composed of three components: hydroelectric, thermoelectric and complementary wind generation. And the analysis of the implications of the variation in the productivity index and the probability of the planning scenarios, because it was not observed in the existing dispatch modeling methods a model where this analysis is done. In modeling, Dual Stochastic Dynamic Programming where to simulate the random behavior of the wind movement is used Brownian, assuming that the wind speed over time it is a continuous Gaussian process. For the numerical analysis of the results, we used actual load curve data and a sample wind curve. At the end the search results identified that the variation in the index of productivity and complementary wind generation brought decrease in cost. And the increased probability associated with the scenarios brought an increase in cost indicating that the scenarios used were not favorable for planning.