Hybrid Neuro Fuzzy Controller for Automatic Generation Control of Multi Area Deregulated Power System

Abstract

This paper is intended in investigating the Automatic Generation Control (AGC) problem of a de-regulated power system using Adaptive Neuro Fuzzy controller. Here, three area control structureof Hydro-Thermal generation has been considered for different contracted scenarios under di-verse operating conditions with non-linearities such as Generation Rate Constraint (GRC) andBacklash. In each control area, the effects of the feasible contracts are treated as a set of new inputsignals in a modified traditional dynamical model. The key benefit of this strategy is its high in-sensitivity to large load changes and disturbances in the presence of plant parameter discrepancyand system nonlinearities. This newly developed scheme leads to a flexible controller with a sim-ple structure that is easy to realize and consequently it can be constructive for the real worldpower system. The results of the proposed controller are evaluated with the Hybrid ParticleSwarm Optimisation (HCPSO), Real Coded Genetic Algorithm (RCGA) and Artificial Neural Network(ANN) controllers to illustrate its robustness