Intelligent Fault Recovery Controller for Power Generator at Perdawd CCGS in Kurdistan-Iraq

Wassan Adnan Hashim; Faiz Al Alawy

doi:10.25212/lfu.qzj.2.2.34

Authors

Wassan Adnan Hashim Computer Science, Information Technology, Bayan University - Iraq
Faiz Al Alawy College of Technology, Kent State University – U.S.A

DOI:

https://doi.org/10.25212/lfu.qzj.2.2.34

Keywords:

ANFIS, CCGS, KRPS, Genetic algorithm, Power System Stabilizer, objective function.

Abstract

Different Artificial Intelligent (AI) tools are becoming commonly used to design different intelligent controllers. The objective of this work is to investigate the performance of a suggested intelligent controller of a specific power generation system during and after sadden faults. Two types of AI tools, genetic algorithms and adaptive neuro-fuzzy inference system, have been used in this work to design a control unit for the power station mentioned above as a case study. Simulated models were designed to optimize the control parameters to enhance the performance. A wide range of training data pairs was used to train the controllers and then to test the system performance. A comparison between the performance of the intelligent and conventional controllers has been introduced. The simulation results show a clear prove that the intelligent controller is outperform the classical one especially during the fault recovery time. Damping performance, oscillation, the system stability and the dynamic performance of electrical power system have been studied.

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