Improved Whale Optimization Algorithm for Transient Response, Robustness, and Stability Enhancement of an Automatic Voltage Regulator System

Salman Habib, Ghulam Abbas, Touqeer A. Jumani, Aqeel Ahmed Bhutto, Sohrab Mirsaeidi and Emad M. Ahmed
Additional contact information
Salman Habib: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Ghulam Abbas: School of Electrical Engineering, Southeast University, Nanjing 210096, China
Touqeer A. Jumani: Department of Electrical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs 66020, Pakistan
Aqeel Ahmed Bhutto: Department of Mechanical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs 66020, Pakistan
Sohrab Mirsaeidi: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Emad M. Ahmed: Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia

Energies, 2022, vol. 15, issue 14, 1-18

Abstract: The proportional integral derivative (PID) controller is one of the most robust and simplest configuration controllers used for industrial applications. However, its performance purely depends on the tuning of its proportional (K P ), integral (K I ) and derivative (K D ) gains. Therefore, a proper combination of these gains is primarily required to achieve an optimal performance of the PID controllers. The conventional methods of PID tuning such as Cohen-Coon (CC) and Ziegler–Nichols (ZN) generate unwanted overshoots and long-lasting oscillations in the system. Owing to the mentioned problems, this paper attempts to achieve an optimized combination of PID controller gains by exploiting the intelligence of the whale optimization algorithm (WOA) and one of its recently introduced modified versions called improved whale optimization algorithm (IWOA) in an automatic voltage regulator (AVR) system. The stability of the IWOA-AVR system was studied by assessing its root-locus, bode maps, and pole/zero plots. The performance superiority of the presented IWOA-AVR design over eight of the recently explored AI-based approaches was validated through a comprehensive comparative analysis based on the most important transient response and stability metrics. Finally, to assess the robustness of the optimized AVR system, robustness analysis was conducted by analyzing the system response during the variation in the time constants of the generator, exciter, and amplifier from −50% to 50% range. The results of the study prove the superiority of the proposed IWOA-based AVR system in terms of transient response and stability metrics.

Keywords: whale optimization algorithm; improved whale optimization algorithm; automatic voltage regulator; stability; dynamic response enhancement (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/14/5037/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/14/5037/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:14:p:5037-:d:859560

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().