Title :
Hierarchical nonlinear model predictive control for combined cycle start-up optimization
Author :
Tica, A. ; Gueguen, Herve ; Dumur, D. ; Faille, Damien ; Davelaar, Frans
Author_Institution :
ASH Team, SUPELEC-IETR, Cesson-Svign, France
Abstract :
A hierarchical model predictive control (H-MPC) structure is proposed to improve the start-up performances of Combined Cycle Power Plants (CCPPs) start-up. The structure includes two layers. At each layer, the control problem aims at deriving the profile of the gas turbine (GT) load at different time scales. To achieve this, the profile is assumed to be described by parameterized functions, whose parameters are computed by solving an optimal time control problem, based on a model developed in the modeling language Modelica and subject to a number of constraints on the plant variables. Numerical results prove the potential advantages of the proposed approach.
Keywords :
combined cycle power stations; gas turbines; hierarchical systems; nonlinear control systems; optimal control; power system control; predictive control; CCPP start-up; H-MPC structure; Modelica; combined cycle power plant start-up; combined cycle start-up optimization; gas turbine load; hierarchical nonlinear model predictive control; modeling language; optimal time control problem; parameterized function; plant variables; start-up performance; Computational modeling; Load modeling; Mathematical model; Object oriented modeling; Optimization; Stress; Valves;
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2012.6425843