Model Predictive Based Load Frequency Control of Interconnected Power Systems

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 thermal gas 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 auto tuned 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.