Síntese e otimização de um sistema de poligeração para uma indústria de laticínios

• Ano de defesa: 2021
• Autor(a) principal: Correia, Victor Hugo Lôbo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Engenharia Mecânica; Programa de Pós-Graduação em Engenharia Mecânica; UFPB
• Palavras-chave em Português: Processamento de leite; Programação linear inteira mista; Energia; Sistema energético; Multigeração; Milk processing; Mixed-integer linear programming; Energy; Energy system; Multigeneration; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/20911

The food and beverage industry presents the highest rate of electricity consumption in the Brazilian industrial sector. In this sector, the dairy industry is remarkable because it represents an important activity for the national economy and has a high energy demand. In this context, the present study aims to synthesize and to optimize a polygeneration system for a dairy industry located in João Pessoa, Northeast Brazil, in order to improve energy efficiency and economic indicators. Initially, for each utility the monthly, daily, and hourly demand profiles were established over a representative year. The industry energy demands are steam, hot water, electricity, and chilled water. Based on the energy demands, a superstructure was built to represent all the possible processes and connections of the energy supply system and using commercially available equipment and locally available energy sources. The optimization model is based on mixed-integer linear programming and its objective function is to minimize the total annual costs of the polygeneration system. The model determines the optimal combination between pieces of equipment, connections, and energy sources inside the superstructure. Also, sensitivity analyses were carried out to assess the system’s behavior under variations of energy demands, fuel costs, and the capital recovery factor. The optimal system showed a reduction of 25,38% in the total annual cost when compared to the reference system which the optimization model does not allow the use of cogeneration and renewable energy. This reduction is reached by the combination of diesel and natural gas generators with electricity purchase from the local grid to meet electricity and chilled water demands. As a result of the sensitivity analysis, the optimal system demonstrated a good performance under fuel price variations, maintaining its original configuration in most of the scenarios. Regarding demand variations, the optimal solution does not present a resilient behavior.