Automatic Generation Control of Multi-area Power System with Generating Rate Constraints Using Computational Intelligence Techniques

Abstract

— In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (DF) and tie line error (DP tie ) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functions .