A hybrid fuzzy-PID controller based on gray wolf optimization algorithm in power system

This paper addresses a grey wolf optimizer to optimally set the PID controller with low pass filter for simulating multi area restructured power system with considered superconducting magnetic energy storage plant that works under various loading conditions and uncertainties. To make a real model, the reheat effect nonlinearity of the steam turbine and governor is considered into automatic generation control (AGC) model. The proposed AGC model is formulated as a nonlinear constrained optimization problem which is solved by an intelligent algorithm so that it shows powerful search in optimization problem especially the proposed AGC. The effectiveness of the proposed technique is demonstrated on a deregulated power system with possible contracted scenarios under large load demand and area disturbances in comparison with other method through several performance indices. Obtained results show that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers.