Abstract
This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load–frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.
Highlights
In recent years, gas turbines (GT) have reached a primary position in thermal power generation field because of their fast deliveries of power and availability of natural gas (NG) (Rayaprolu 2009)
The application of subspace identification to gas turbine process This section discusses the process of gas turbine technology, the preparation of data signals, and the simulation results for the method of subspace technique for both phases of research (IEEE Power System Dynamic Performance Committee 2013; Modau and Pourbeik 2008)
A load demand signal extracted from the data during classical closed loop control is used as one of the set-point signals injected to the model predictive control (MPC), with higher exhausted temperature setpoint of 565CƟ and the frequency should be maintained at 50 Hz
Summary
Gas turbines (GT) have reached a primary position in thermal power generation field because of their fast deliveries of power and availability of natural gas (NG) (Rayaprolu 2009). If the system automation is upgraded with potential to correct such signals by the MPC, these signals will optimize in advance which means reduced process variations while keeping faster load following capability due to higher stored/kinetic energy in the plant This can make the CCGT works close to its optimum efficiency by expanding the pressure ratio and the firing temperature by MPC. The method of subspace identification is based on the advanced matrix linear algebra techniques which are singular value decomposition and oblique projection. We shall define the block Hankel matrix that contains the past inputs and outputs Wp. The general steps for subspace identification are (Ruscio 2009; Overschee and Moore 1996): 1.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
