Hybrid Taguchi Genetic Algorithm-Based AGC Controller for Multisource Interconnected Power System

Abstract—

This article presents hybrid Taguchi-genetic algorithm (HTGA) tuned automatic generation controller for two areas interconnected multisource power system model. The control areas consist of thermal, hydro, and doubly fed induction generator-based wind power plants. The optimal tuning of AGC controller using genetic algorithm is less robust due to larger standard deviation of the fitness values. Therefore, Taguchi method which is based on modified statistical approach and has systematic reasoning ability is used to enhance the performance of genetic algorithm. The simulation study is carried out with the optimum gains of AGC controller obtained from HTGA, conventional GA and conventional techniques. The dynamic stability of the power system model is examined to analyze the performance of the HTGA technique. From investigations it is quite clear that the optimum gains of AGC system obtained from HTGA technique has better response in the dynamic stability of the interconnected multisource power system as compared to genetic algorithm and conventional technique.

Keywords:

• Hybrid Taguchi genetic algorithm
• intelligent techniques
• Taguchi method
• genetic algorithm
• multisource power system
• DFIG
• automatic generation control

Disclosure statement

Prof. Naimul Hasan declares that he has no conflict of interest. Prof. Ibraheem declares that he has no conflict of interest. Shuaib Farooq declares no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Notes on contributors

Naimul Hasan

Naimul Hasan received the B.Sc. and Ph.D. degrees in electrical engineering from Jamia Millia Islamia, New Delhi, India, in 1996 and 2007, respectively, and the M. Tech. degree in electrical engineering from the Department of Electrical, Aligarh Muslim University, Aligarh, India in 2002. He is a professor at Jamia Millia Islamia, New Delhi, India. Presently he is working in the Department of Electrical Engineering, Qassim University, KSA as a full professor. His research interests are in automatic generation control strategies, power system operation and control, deregulated and restructured power system.

Ibraheem Nasirudin

Ibraheem Nasiruddin received his B.Sc. Engg. (Hons.) M.Sc. Engg., and Ph.D. in electrical engineering from Aligarh Muslim University, Aligarh, India. He is a professor at Jamia Millia Islamia, New Delhi, India. He has also worked in the Department of Electrical Engineering, Qassim Engineering College, Qassim University, Kingdom of Saudi Arabia as full professor. He is an active researcher and has published over 50 research articles in journals of national and international repute and over 100 research articles in conferences and his research interests are power system operation and control, AGC of power systems, optimal control theory applications in power plants system control, application of intelligent control in deregulated power systems, renewable energy systems, and unmanned aerial vehicles (UAVs).

Shuaib Farooq

Shuaib Farooq received the Ph.D. degree in electrical engineering from the Department of Electrical Engineering, Jamia Millia Islamia University, India in 2017. He is currently working with Emerson Automation Solutions as Senior Simulation Engineer. His research interests are modeling and Simulation of power system applications, control system design and tuning and renewable energy.