Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant

Abstract

This paper proposes an adaptive model predictive control (AMPC) approach with online parameter estimation for a V94.2 gas turbine mounted in the Damavand combined cycle power plant (CCPP). The AMPC is designed to simultaneously maintain the speed and temperature responses of the gas turbine within their desired levels in the presence of frequency drop or change in load demand. It implements an online parameter estimation and adaptive mechanism to enable the model parameters to follow any change in the V94.2 gas turbine power plant (GTPP) model and provide the best control performance possible. The effectiveness of the AMPC approach is assessed using an estimated model of a V94.2 gas turbine mounted in the Damavand CCPP. Additional analysis is also performed via a comparison study encompassing a classical MPC, H∞, and m synthesis robust control strategies and considering reference tracking performance, transient and steady-state responses, disturbance rejection capabilities, and robustness to parameter variations. The obtained results confirmed the effectiveness of the proposed approach in improving the robust stability and dynamics of the V94.2 GTPP in the presence of measurement noise, frequency disturbance, and unmodeled power plant dynamics along with its superior performance in terms of tracking capability and disturbance rejection properties.