Optimal design of PD-Fuzzy-PID cascaded controller for automatic generation control

Abstract

In this research paper a novel cascaded PD-Fuzzy-PID controller is recommended for a conventional hybrid-source unified power system for automatic generation control. The optimization of scaling parameters of the suggested PD-Fuzzy-PID controller is done by hybrid Grey Wolf Optimization-Teaching Learning Based Optimization (GWO-TLBO) technique. A sudden disturbance of 0.01 p.u. is considered in area 1 and ITAE is taken as the evaluative function in the recommended optimization process. The proposed work considers three different sources of generating systems namely, a hydro, a gas and a reheat thermal unit. Both AC tie-line and AC-DC tie-line is considered in analyzing the dynamic performances of the system. The robustness and sensitiveness of the proposed controller are further put to test for random load variations and nominal parameter variations. Analysis of the dynamic characteristics of the system is executed considering a number of time response specifications like settling time, peak overshoots and undershoots. During the analysis the optimum specifications obtained by the recommended technique are compared with some pre-published results in order to prove the supremacy of this novel controller over existing controllers. Further, the frequency stability of the system is improved by employing an UPFC in the system.

Keywords

• fuzzy control
• automatic generation control
• grey wolf optimization
• teaching learning based optimization
• cascaded pd-fuzzy-pid controller
• multi-source system