Abstract
This paper proposes a novel Improved Artificial Electric Field Algorithm (IAEF)-based AGC in a multi-area power system to minimize the area control error and to obtain an optimal solution. Here, four area AGC systems equipped with the PID controller are examined for the study processes. Also, an optimal gain value for the PID controller is obtained by employing an IAEFA; thus minimizing the area control error (ACE). In addition to this, nine different test functions are employed to evaluate the performances of the proposed IAEF-based AGC of a multi-area power system and are compared with several optimization approaches such as AEF algorithm, BBO Algorithm, PSO Algorithm as well as DE Algorithm. Also, the performance evaluation based on three different simulation strategies such as simulation based on time domain, Random disturbances of the AGC system as well as System Dynamics for maximum frequency deviation and Percentage Improvement for a four area power system. Here, the maximum frequency deviations for four areas are −0.0132, −0.0145, −0.0122 and −0.0120, respectively. Moreover, the percentage improvements with respect to the IAEF with respect to the PID controllers are 67.32%, 57.21%, 47.26% and 55.47%, respectively. The experimental analysis reveals that the proposed approach provides very less tie-line control error and better optimal tuning of the PID controller when compared with all other approaches.
Additional information
Notes on contributors
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Ajitha Priyadarsini Sobhanam
Ajitha Priyadarsini Sobhanam obtained her BTech in electrical & electronics engineering from Government College of Engineering, Thrissur. Then, she obtained her ME in power systems engineering from Anna University, Chennai. She obtained her PhD from Anna University, Chennai in 2017. She is currently working as a faculty in the Department of Electrical and Electronics Engineering at Narayanaguru College of Engineering. Her specializations include power systems and soft computing techniques.
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Paulraj Melba Mary
Paulraj Melba Mary is the director at RECT Polytechnic College, Tirunelveli. She received her BE in electrical and electronics engineering from Government College of Engineering, Tirunelveli, her ME in control and instrumentation from Anna University, Chennai, in 1990 and 1995, respectively. She has obtained her PhD from Anna University, Chennai, in 2009. Her main research interests include hybrid control system theory, industrial process control, robotics and various intelligent techniques used in the design of controllers. She presented papers in various conferences and published many papers in national and international journals. She is a member in various professional bodies like ISTE, IEEE and IET. Email: [email protected]
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Willjuice Iruthayarajan Mariasiluvairaj
Willjuice Iruthayarajan Mariasiluvairaj is a professor and head, Department of Electrical and Electronics Engineering, National Engineering College, Kovilpatti. He obtained his BE in EEE from Government College of Engineering, Tirunelveli and ME in control and instrumentation from College of Engineering, Anna University and PhD from Anna University, Chennai, India. Dr M Willjuice Iruthayarajan specializes in soft computing and evolutionary optimization algorithms. He has published more than 80 research publications in journals and conferences. He is a Senior Member of Institute of Electrical and Electronics Engineers, Fellow member in Institution Engineers (India), Life Member in Instrument Society India, Systems Society India, Indian Society Technology Education and Soft Computing Research Society. Email: [email protected]
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Rajeev Davy Wilson
Rajeev Davy Wilson is a professor, at Department of Mechanical Engineering, MarEphraem College of Engineering and Technology, Marthandam. He obtained his BE in mechanical engineering from Bharathiyar University and ME in CAD from University of Madras and PhD from Hindustan Institute of Technology and Science. He has more than twenty years of teaching experience specializing in computer aided design and soft computing-based condition monitoring. Email: [email protected]