Alocação do material lignocelulósico no setor sucroenergético : formação da carteira eficiente de produção

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: Souza, Fábio Simone de
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Rio de Janeiro
Brasil
Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
Programa de Pós-graduação em Planejamento Energético
UFRJ
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11422/12295
Resumo: Considering the technological changes that have occurred in the sugarcane industry in the last decades, the electric power generation and second-generation ethanol production using sugarcane biomass, represent sustainable alternatives to supply and to energy security in Brazil. This thesis aims, through the Markowitz model, incorporate the uncertainties in the decision-making process of the mill and provides the percentage of Lignocellulosic Material (ML) that will be used to generate electricity and to produce cellulosic ethanol. This thesis concluded that, in the Base Scenario, 90.99% of ML must be used for the generation of energy traded on the Regulated Market and, as the cost of production of 2G ethanol will be reduced toward the percentage expected by industry experts (50% of production cost in Base Scenario), increases the percentage of ML available in the plant should be directed to its activity. The Net Present Value, when all the ML is directed to 2G ethanol production, becomes financial advantageous to the commercialization of electric energy, in any of the markets for sale of energy, at average prices of the historical market series, if there is at least a 40% reduction in its cost of production. From this scenario, it is expected to receive a higher income, but this is accompanied by a higher volatility of the returns generated. In this way, the Markowitz (1952) model is a powerful tool for ML allocation in the sugarcane industry, but it must be accompanied by complementary analyzes for verification and interpretation of their results.