ASSESSMENT OF PID CONTROLLER TUNING USING HYBRID MPC-PSO FOR INTERCONNECTED POWER PLANT FREQUENCY CONTROL

Abstract

This paper entails designing a Peripheral Integral Differential (PID) controller for a two area power system network using particle swarm optimization (PSO) technique which is a swarm based intelligence method. The load frequency for power system networks usually experience drop or fluctuations whenever there is a sudden engagement or disengagement of load. This is known as load disturbance. This research work aims to solve this problem by employing a PID controller to assist the governor control of the power system network. The effect of application of the PID controller is a stable load frequency operation even if there is a disturbance in the load. Also, the PID controller is usually tuned manually using the Zeigler-Nichols method. In the research work, however, the controller will be tuned with the help of the PSO algorithm. At the end of this research work, it will be shown that the two area power system network will maintain a steady load frequency even in the presence of disturbance. The LFC result will also be compared that of the manual tuning (referred to as base case) and that of the PSO tuning and an MPC-PSO tuned PID. The result will reveal that all methods are capable of stabilizing the load frequency but that the MPC tuned PID (MPC-PSO) will give a superior result in terms of faster settling time.