Aplicação de controle preditivo não linear multivariável com otimizador à operação transiente de turbina a gás
Ano de defesa: | 2017 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
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 Mecânica UFRJ |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11422/6003 |
Resumo: | Apply and to investigate a multivariable nonlinear modelbased predictive control strategy to avoid unsafe or inappropriate operation of a gas turbine. In this research, the controller maintains the rotational speed of the compressor constant in accordance with the grid frequency, during load changes. Additionally, in case the gas turbine is installed in a combined heat and power cycle, the discharge temperature must track a reference, to ensure the quality of the generated steam. The control is achieved by manipulation of the fuel flow in the combustion chamber and by adjusting the position of the variable inlet guide vanes of the compressor. The nonlinear dynamic behavior of a gas turbine with an industrial configuration is modeled with the aid of a first principle process simulator, which solves the mass and energy balances and the equations of state and shaft transient. In addition to speed and temperature control, the control strategy is applied to minimize fuel consumption and pollutant emissions. The inherent optimization process of the controller is solved and verified by means of three evolutionary algorithms and one direct search method. The proposed controller is successfully applied to the simulated gas turbine for load fall and load rejection scenarios and the strategy fulfills its goals in reducing fuel consumption and pollutants emissions. |