Background: To achieve the goal of automatic generation control of better system frequency
regulation and to control the tie-line active power deviations, this paper presents a genetic algorithm
optimized model predictive control (GA-MPC) scheme for load frequency regulation of two area
interconnected power systems.
Methods: Three different power systems: thermal-thermal system, thermal-nuclear system and thermalgas
system, interconnected by tie-lines, have been considered to assess the performance of the proposed
control scheme (GA-MPC). Inorder to evaluate the effectiveness of the proposed controller, a
comparitive analysis is performed between the controller scheme, auto-tuned PID controller and autotuned
MPC, in terms of performance indices namely: overshoot/undershoot and settling time of the
transient response of the test systems. Sensitivity analysis has also been performed to test the efficacy
and robustness of GA-MPC, MPC and PID controllers, when subjected to variations in loading
conditions, tie-line synchronizing coefficient and turbine time constant. Also, dynamic response of the
thermal-thermal system with GA based MPC controller is studied and analysed in the presence of nonlinear
constraints namely: generation rate constraint (GRC) and governor deadband.
Results: The simulation results establish the superiority of GA based MPC over auto-tuned MPC and
auto-tuned PID controllers, in maintaining the output power generation and minimization of the area
control error. The sensitivity analysis shows that the proposed scheme is robust and insensitive to the
variations in load disturbances and system parameters. Also, the considered control scheme is able to
effectively handle the system non-linearities.
Conclusion: The presented method is quite effective in controlling the system frequency and tie-line
power flow in the presence of system non-linearities and sudden disturbances.