Uma nova metodologia NMPC integrada com uma camada de otimização para maximizar a produção de óleo offshore com especificações de qualidade

• Ano de defesa: 2019
• Autor(a) principal: Ribeiro, Leonardo Dorigo
• 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 Engenharia Química; UFRJ
• Palavras-chave em Português: Controle preditivo não linear; Otimização; Processo de produção de óleo e gás offshore; CNPQ::ENGENHARIAS::ENGENHARIA QUIMICA
• Link de acesso: http://hdl.handle.net/11422/13616

The oil and gas industry is impacted by low growth economic cycles. For this reason, techniques of NMPC and optimization that help the operability of the plant are very important for the business. However, the use of these tools in industry requires overcoming some challenges, for instance: find accurate models of the process, computational time suitable for obtaining the solution and integrate the layers of control and optimization. In this work a methodology is proposed to obtain analytical models based on hammerstein structure, reducing the computational time. Unlike most common approaches that transform NMPC internal model, described by differential-algebraic equations (DAE), into an approximate system of nonlinear algebraic equations (NLA) using, for instance, orthogonal collocation. In the proposed approach, the obtained NLA is an exact description of the original DAEs system. The proposed algorithm was applied to a non-isothermal CSTR integrated with an optimization layer. The results show that the proposed structure presents significant reduction in computational time without performance loss, when compared with the NMPC using rigorous model. Moreover, the proposed strategy demonstrated good performance in tracking the targets sent by the optimization layer, without model mismatches between layers. An important contribution of the work is the application of the proposed NMPC integrated with an optimization layer in an oil and gas production process. The results show good performance of the proposed algorithm to stabilize the process during slug flow conditions, keeping the quality requirement inside the constraints and driving the process to the optimal point obtained in the optimization layer.