Application Of Modern Heuristic Optimization Techniques For Load Frequency Control In Interconnected Power Systems

Abstract

This thesis mainly contributes in the area of Load Frequency Control (LFC) of interconnected power systems by the application of Artificial Intelligence (AI) techniques to ensure stable and satisfactory operation of power systems. Among the AI techniques, modern heuristic techniques such as Differential Evolution (DE), Gravitational Search Algorithm (GSA) and Teaching Learning Based Optimization (TLBO) algorithm are efficient techniques for handling optimization problems. In the present thesis, an attempt has been made to explore the application these artificial intelligence techniques for AGC of interconnected power systems. newlineDesign and performance evaluation of DE and GSA optimized PI controller for Automatic Generation Control (AGC) of an interconnected power system is presented in this thesis. Modified objective functions with appropriate weight coefficients are employed to increase the performance of the controller. The superiority of the proposed design approaches has been shown by comparing the results with some recently published modern heuristic optimization techniques. Further, robustness analysis is carried out to demonstrate the robustness of the proposed controller to wide changes in system parameters, and size and position of step load perturbation. newlineA DE optimized parallel 2- Degree of Freedom Proportional-Integral-Derivative (2-DOF PID) controller optimized for Load Frequency Control (LFC) of interconnected power system is presented in this thesis. The superiority of the proposed approach has been shown by comparing the results with a recently published approach. The proposed approach is further extended to a more realistic power system model by considering the physical constraints such as time delay, reheat turbine, GRC newline newlineand governor dead band. It is observed that when physical constraints are introduced, the variations in performance index are prominent. newlineA Gravitational Search Algorithm (GSA) optimized ideal Two Degree of Freedom Proportional-Integral-Derivative (TDOFPID) co