Dynamic Modeling of Electromechanical Energy Conversion Systems in Advanced Gas Turbines using Adaptive Control Algorithms

Abstract

This paper introduces a rigorous dynamic modeling and control platform of the electromechanical energy conversion systems of single-shaft, heavy-duty gas turbines. As contemporary power grids become increasingly volatile with the integration of intermittent renewable power sources, traditional fixed-gain Proportional-Integral-Derivative (PID) controllers are becoming less effective in maintaining a stable frequency and protecting the thermomechanical limits of the turbines. To address this limitation, a non-linear dynamic model was developed incorporating governor droop, valve actuator inertia, combustion thermodynamics, and rotor swing dynamics. Then, a synthesized PID-based Model Reference Adaptive Control (MRAC) algorithm that dynamically adjusts control gains in real-time using the MIT rule was developed. Three critical operational stress tests applied to the proposed MRAC-PID architecture included a 20% step load disturbance, high-frequency load tracking, and parameter uncertainty with half the grid inertia. Quantitative analysis demonstrates that the MRAC-PID controller shows significant improvements in comparison with the classical PID, reducing the maximum frequency undershoot from -0.018 p.u. to (a 61.1% improvement), reducing thermal overshoots by 88.8%, and decreasing transient settling time by 63.8%. Moreover, the adaptive algorithm effectively eliminated valve chattering during stochastic load operation and mitigated severe torsional resonance during low-inertia operation.