Previsão de consumo de energia elétrica e elaboração de modelos de otimização em cooperativa de eletrificação rural

Detalhes bibliográficos
Ano de defesa: 2011
Autor(a) principal: Pinheiro, Elisângela
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
BR
Engenharia de Produção
UFSM
Programa de Pós-Graduação em Engenharia de Produção
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://repositorio.ufsm.br/handle/1/8212
Resumo: This dissertation aims to build a set of tools based on mathematical models to assist a rural electrification cooperative in taking strategic decisions on investing in electrical generation in face of erratic and non-periodic future scenarios. Time series analysis using the Box-Jenkins methods for forecasting was employed to construct the models to predict future energy consumption. Qualitative analysis of future scenarios using Kohler method, that is suited to regional applications, was used. An heuristic approach with hierarchical levels was employed to define the parameters of a mathematical model for the application of integer linear programming at a lower level. This mathematical program was used to optimize the location of photovoltaic solar power plants within a transformer substation area and its branches to minimize disbursements in assets investments, and operations and maintenance costs. The model was tested in a cooperative with six substations, 572 branches, 7,574 cooperative members and a 2,737 km length network. In results obtained was SARIMA models (1,1,1) x (0,1,1) 12. In total, obtained an increase of 1.292 kW for the six substations in the next five years, representing a disbursement R$ 17,170,000.00 if the cooperative to chooses to build a photovoltaic solar power plant to meet this increase of consumption.