Automatic generation control of power system in deregulated environment using hybrid TLBO and pattern search technique

In the present work, a hybrid Teaching Learning Based Optimization and Pattern Search (hTLBO-PS) technique with Tilted Integral Derivative (TID) controller is suggested for Automatic Generation Control (AGC) under deregulated environment. In the beginning, a two-area four units thermal-gas system is assumed and Tilted Integral Derivative (TID) controller is employed. The superiority of hTLBO-PS based TID is illustrated by comparing the published results with Genetic Algorithm (GA) and Differential Evolution (DE) tuned I/PI/PID controllers for the identical test scheme. After that the suggested methodology is extended to 2-area with 6-units power system by considering the non-linearities parameters. Additionally, to improve the performance of the system, a Thyristor Controlled Phase Shifter (TCPS) is connected in the tie-line and Superconducting Magnetic Energy Storage (SMES) devices are considered in each area. Finally, the sensitivity analysis of proposed method with perturbation in plant parameters has been analyzed.