TITLE:
Hybrid Neuro Fuzzy Controller for Automatic Generation Control of Multi Area Deregulated Power System
AUTHORS:
Baghya Shree Solaiappan, Nagappan Kamaraj
KEYWORDS:
AGC, ANFIS, ANN, Deregulated Power System, HCPSO, RCGA
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.4,
April
27,
2016
ABSTRACT: This paper is intended in investigating the Automatic Generation
Control (AGC) problem of a deregulated power system using Adaptive Neuro Fuzzy
controller. Here, three area control structure of Hydro-Thermal generation has
been considered fordifferent contracted
scenarios under diverse operating conditionswith non-linearities such asGeneration Rate Constraint (GRC) and Backlash.In each control area, the effects of the feasible contracts are treated as
a set of new input signals in a modified traditional dynamical model. The key
benefit of this strategy is its high insensitivity to large load changes and
disturbances in the presence of plant parameter discrepancy and system
nonlinearities. This newly developed scheme leads to a flexible controller with
a simple structure that is easy to realize and consequently it can be
constructive for the real world power system. The results of the proposed
controller areevaluatedwith the Hybrid Particle Swarm Optimisation (HCPSO),
Real Coded Genetic Algorithm (RCGA) and Artificial Neural Network (ANN)
controllers to illustrate its robustness.