Application of Hybrid Optimization Techniques in Power System Frequency Controllers

Abstract

This dissertation mainly contributes in the area of power system stability improvements by the application of Artificial Intelligence (AI) and discusses the various technical issues associated with Automatic Generation Control (AGC) for secure, reliable and well balanced action of modern power system. An attempt has been made in the present work for the application of various soft computing techniques to improve the stability of a complex power system. In this regard, improved soft computing techniques and hybridization of these soft computing techniques as well as new controller structures are proposed for performance enhancement of power structure. Among the soft computing techniques, meta-heuristic approaches like Differential Evolution(DE),Modified Differential Evolution (MDE), Pattern Search(PS) Algorithm, hybrid Modified Differential Evolution and Pattern Search (hMDE PS)Algorithm, Adaptive Differential Evolution (ADE),hybrid Adaptive Differential Evolution and Pattern Search(hADE PS) Algorithm, Harris Hawks Optimization(HHO) and Chaotic Harris Hawks Optimization(CHHO) are efficient techniques for handling optimization problems and hence applied for AGC of interconnected power system. With increasing complications of the modern power framework, prevailing intelligent control structure is also crucial. So, control structures like conventional (Proportional-Integral-Derivative (PID) and its variants), Proportional Integral Derivative accompanied by derivative Filter (PIDF),Fuzzy PID, Fractional order Fuzzy PID(FOFPID),Type-2 Fractional order Fuzzy PID (T2FOFPID) controller and self-tuning techniques based on fuzzy logic i.e. Fuzzy Logic Controller (FLC) have been proposed for AGC. newline