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http://dx.doi.org/10.1109/pecon.2006.346640

has been cited by the following article:

• 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.