Multi-objective economic model predictive control for gas turbine system based on quantum simultaneous whale optimization algorithm. (1st March 2020)

• Record Type: Journal Article
• Authors: Hou, Guolian; Gong, Linjuan; Yang, Zhile; Zhang, Jianhua
• Is Part Of: Energy conversion and management. Volume 207(2020)
• Publication Date: 2020-03-01
• Subjects: Gas turbine system -- Combined cycle unit -- Multi-objective economic model predictive control -- Quantum simultaneous whale optimization algorithm; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2020.112498
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: An MOEMPC strategy is formulated considering economic indexes and terminal cost. A novel quantum simultaneous whale optimization algorithm is adopted. The proposed method is applied into the controller design of gas turbine system. Abstract: The gas turbine system is a major contributor of the thermal power generation process and an important complementary to the future high penetration of intermittent renewable generations. The rapidity, efficiency, and economy operation of the gas turbine system calls for advanced control algorithms and associated parameter optimization methods, which are intractable due to the strong coupling impact of complex turbine systems. In this paper, a multi-objective economic model predictive control (MOEMPC) method based on quantum simultaneous whale optimization algorithm is proposed for gas turbine system control. Firstly, the objective function of the MOEMPC strategy is formulated simultaneously considering economic indexes, terminal cost function, and stability constraints. The economic indexes reflect the change of energy consumption and throttle loss in real-time, while the terminal cost function and stability constraint guarantee the tracking accuracy under variable operation point and external disturbance. Secondly, a novel quantum simultaneous whale optimization algorithm is adopted to handle the optimization problem of MOEMPC. The introductions of the quantum coding and simultaneous search in original whale optimization algorithm have improved the convergence rate and accuracy immediately. Finally, the proposed method is applied into the controller design of gas turbine system in combined cycle unit. The simulation results have indicated the superiority of the presented strategy in terms of desired economic performance, high precision, rapidity, and robustness.