Modelagem e dimensionamento de sistemas híbridos de geração de energia: caso para as Ilhas Galápagos
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Data
2021-02-22
Autores
Llerena Pizarro, Omar Rosendo
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
O setor elétrico das Ilhas Galápagos é dependente dos combustíveis fósseis para a geração de eletricidade, utilizando apenas 15% das fontes renováveis existentes no arquipélago. Portanto, neste cenário, torna-se importante a realização de estudos que visem a implementação de Sistemas Híbridos de Geração de Energia (SHGE) que incrementem a participação de tais recursos renováveis, de modo a diversificar a sua matriz energética, diminuir a dependência dos combustíveis fósseis, e promover o desenvolvimento sustentável nas Ilhas. O dimensionamento adequado destes SHGE traz benefícios técnicos, econômicos e ambientais. Neste contexto, este trabalho apresenta o desenvolvimento de uma ferramenta para a modelagem matemática, simulação, e dimensionamento de SHGE. Para tal finalidade, desenvolveu-se um algoritmo de otimização multi-objetivo no MATLAB®. As variáveis de decisão contínuas (número de componentes) e as variáveis de decisão discretas (modelos/tipos dos componentes) envolvidas no projeto do SHGE são tratadas independentemente pelo Particle Swarm Optimizer (PSO) e pelo Binary Particle Swarm Optimizer (BPSO), respectivamente. O objetivo da otimização é minimizar o valor presente líquido dos custos, e maximizar a confiabilidade operacional do sistema. O algoritmo misto proposto (PSO-BPSO) é utilizado para dimensionar sistemas solar-bateria-diesel e solar-bateria-biogás para as Ilhas Galápagos. Os resultados mostram que a técnica proposta apresentou igual, e em alguns casos, melhor desempenho que os outros métodos comparados. Nos resultados, observa-se que os SHGE que combinam painéis fotovoltaicos (PV), baterias (BT) e geradores à diesel (DG) são as configurações ótimas com um custo de US$ 116.681,20 para a Ilha Floreana e um custo de US$ 856.878,46 para a Ilha San Cristóbal. Por outro lado, as configurações PV-BT implicam custos mais elevados devido à necessidade do uso de bancos de baterias maiores. No caso dos sistemas solar-baterias-biogás, estes resultaram ser aproximadamente 30% mais baratos. Finalmente, conclui-se que o PSO-BPSO proposto neste trabalho mostrou ser uma ferramenta simples e eficaz para o dimensionamento de SHGE tanto para abordagens mono-objetivo, quanto para abordagens multi-objetivo.
The electrical sector in the Galapagos Islands is dependent on fossil fuels for electricity generation, using only 15% of the renewable sources in the archipelago. Therefore, in this scenario it is important to carry out studies aimed at the implementation of Hybrid Power Generation Systems (HPS) which increase the participation of such renewable resources in order to diversify islands' energy matrix and reduce the dependence on fossil fuels thus promoting sustainable development. The adequate sizing of the HPS brings technical, economic, and environmental benefits. In this context, this work presents the development of a tool for mathematical modeling, simulation, and sizing of the HPS. For this purpose, a multiobjective optimization algorithm was developed in MATLAB®. The continuous decision variables (number of components) and discrete decision variables (models/types of components) involved in the HPS project are handled independently by the Particle Swarm Optimizer (PSO) and the Binary Particle Swarm Optimizer (BPSO), respectively. The purpose of optimization is to minimize the net present value of costs, and to maximize the operational reliability of the system. The proposed mixed algorithm (PSO-BPSO) is used to design solarbattery-diesel and solar-battery-biogas systems for the Galapagos Islands. The results show that the proposed technique presented the same, and in some cases, better performance than the other compared methods. The results reveal that the HPS configuration which combines photovoltaic panels (PV), batteries (BT) and diesel generators (DG) is the optimal configuration with a cost of US $ 116,681.20 for Floreana Island and a cost of US $ 856,878.46 for San Cristóbal Island. On the other hand, PV-BT configurations incur higher costs due to the need OF larger battery banks. Solar-batteries-biogas systems turned out to be approximately 30% cheaper. Finally, the PSO-BPSO proposed in this work proved to be a simple and effective tool for the sizing of HPS for both mono-objective and multi-objective approaches
The electrical sector in the Galapagos Islands is dependent on fossil fuels for electricity generation, using only 15% of the renewable sources in the archipelago. Therefore, in this scenario it is important to carry out studies aimed at the implementation of Hybrid Power Generation Systems (HPS) which increase the participation of such renewable resources in order to diversify islands' energy matrix and reduce the dependence on fossil fuels thus promoting sustainable development. The adequate sizing of the HPS brings technical, economic, and environmental benefits. In this context, this work presents the development of a tool for mathematical modeling, simulation, and sizing of the HPS. For this purpose, a multiobjective optimization algorithm was developed in MATLAB®. The continuous decision variables (number of components) and discrete decision variables (models/types of components) involved in the HPS project are handled independently by the Particle Swarm Optimizer (PSO) and the Binary Particle Swarm Optimizer (BPSO), respectively. The purpose of optimization is to minimize the net present value of costs, and to maximize the operational reliability of the system. The proposed mixed algorithm (PSO-BPSO) is used to design solarbattery-diesel and solar-battery-biogas systems for the Galapagos Islands. The results show that the proposed technique presented the same, and in some cases, better performance than the other compared methods. The results reveal that the HPS configuration which combines photovoltaic panels (PV), batteries (BT) and diesel generators (DG) is the optimal configuration with a cost of US $ 116,681.20 for Floreana Island and a cost of US $ 856,878.46 for San Cristóbal Island. On the other hand, PV-BT configurations incur higher costs due to the need OF larger battery banks. Solar-batteries-biogas systems turned out to be approximately 30% cheaper. Finally, the PSO-BPSO proposed in this work proved to be a simple and effective tool for the sizing of HPS for both mono-objective and multi-objective approaches
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Palavras-chave
SHGE, PSO-BPSO, otimização multi-objetivo, energia renovável, Galápagos, HPS sizing, Multi-objective optimization, Renewable energy, Energia - Fontes alternativas, Geração distribuída de energia elétrica, Otimização matemática, Modelos matemáticos