Fuzzy economic model predictive control for thermal power plant

In a modern thermal power plant, fuzzy model predictive control (MPC) is an effective method for realising load tracking and economy of boiler-turbine system, by using fuzzy modelling technique considering the plant thermal dynamic. The power plant economy is generally handled in a hierarchical MPC (HMPC) architecture, in which the upper layer realises the economic optimisation while the low layer realises the dynamic tracking. However, while this HMPC architecture realises the steady-state optimisation, it may neglect the dynamic optimum of the total power plant process. This study develops a fuzzy economic MPC to utilise the economic index directly as the cost function. It integrates economic optimisation and dynamic tracking of the boiler-turbine system control into one framework. Since a fuzzy model is used to approximate the system's non-linear behaviour, a linear feedback controller can be constituted for guaranteeing the feasibility and stability of the boiler-turbine system through linear matrix inequality. Simulation results are given to show the effectiveness of the proposed controller.