Izvorni znanstveni članak
https://doi.org/10.13044/j.sdewes.d6.0220
Nonlinear Model Predictive Control applied to Transient Operation of a Gas Turbine
Thiago S. Pires
; Department of Mechanical Engineering, PEM-COPPE, UFRJ, Federal University of Rio de Janeiro, CP 68503, CT, Cidade Universitária, 21941-972, Rio de Janeiro, Brazil
Manuel E. Cruz
; Department of Mechanical Engineering, PEM-COPPE, UFRJ, Federal University of Rio de Janeiro, CP 68503, CT, Cidade Universitária, 21941-972, Rio de Janeiro, Brazil
Marcelo J. Colaço
; Department of Mechanical Engineering, PEM-COPPE, UFRJ, Federal University of Rio de Janeiro, CP 68503, CT, Cidade Universitária, 21941-972, Rio de Janeiro, Brazil
Marco A. C. Alves
; Department of Mechanical Engineering, UFJF, Federal University of Juiz de Fora, Rua José Lourenço Kelmer, s/n, Campus Universitário, 36036-900, Minas Gerais, Brazil
Sažetak
This work aims to investigate the application of a comprehensive nonlinear model-based predictive control strategy as a means to avoid unsafe or inappropriate operation of a gas turbine. Herein, the nonlinear model-based predictive control is employed to control compressor speed by varying the fuel flow in the combustion chamber. The methodology
complies with the gas turbine constraints explicitly in the optimization procedure and, therefore, the nonlinear model-based predictive control algorithm ensures that process constraints are not violated. The nonlinear dynamic behaviour of the gas turbine is modelled with the aid of a first principle process simulator, which solves the equations of
state and the conservation equations of mass, energy and momentum. The optimization procedure is achieved through the implementation of an evolutionary algorithm. Three scenarios are simulated: fuel consumption optimization, load removal/addition and load rejection. The proposed control strategy is successfully applied to both transient and
steady-state operational modes of the gas turbine.
Ključne riječi
Nonlinear model-based predictive control; Gas turbine; Process simulator; Optimization; Fuel consumption; Load rejection; Transient operation.
Hrčak ID:
209648
URI
Datum izdavanja:
31.12.2018.
Posjeta: 908 *