Automatic generation controller for multi area multisource regulated power system using grasshopper optimization algorithm with fuzzy predictivePIDcontroller

This paper presents a fuzzy predictive-proportional integral derivative (FP-PID) controller approach for automatic generation controller (AGC). This new AGC approach aims to balance the total generating system without any power losses and load changes in keeping constant system frequency per tie-lie power flow. But, a sudden load variation in multi-area Interconnected power system (MIPS) creates nonlinearities (frequency deviation & tie-line) in all control areas. Because, penetrating of renewable sources to the power system, the sluggish control action may cause inefficiency in migrating frequency and tie-line power flow. Hence, an accurate and fast-acting controller is required to maintain the nominal value also the quality and stability of power system, because traditional AGC is not feasible for further process. Here, we propose an FP-PID controller in MIPS for controlling large parametric uncertainties. Modeling error is taken into account to reduce the maximum deviation and time of oscillation. The main purpose of FP-PID based AGC is to ensure stable and reliable power system operation. A grasshopper optimization algorithm (GOA) is used to tune the parameters of FP-PID controller with Integral of time multiplied squared error (ITSE) as the objective function. The proposed method is compared with conventional two-area and three-area system, the result are built-in Simulink/MATLAB show that the proposed method has a good dynamic response, fast operation reduced magnitude error and minimized frequency transients for three power areas. The robustness of the controller is, it need not be retuned for wide variations in system parameters and random step load power.