A Novel Balanced Arithmetic Optimization Algorithm-Optimized Controller for Enhanced Voltage Regulation

Serdar Ekinci, Haluk Çetin, Davut Izci and Ercan Köse ()
Additional contact information
Serdar Ekinci: Department of Computer Engineering, Batman University, 72100 Batman, Turkey
Haluk Çetin: Institute of Postgraduate Studies, Batman University, 72100 Batman, Turkey
Davut Izci: Department of Computer Engineering, Batman University, 72100 Batman, Turkey
Ercan Köse: Electrical-Electronics Engineering Department, Tarsus University, 33400 Tarsus, Turkey

Mathematics, 2023, vol. 11, issue 23, 1-28

Abstract: This work introduces an innovative approach that unites a PIDND 2 N 2 controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND 2 N 2 controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through the integration of pattern search and elite opposition-based learning strategies into the arithmetic optimization algorithm. This integration optimizes the controller parameters and the AVR system’s response, harmonizing exploration and exploitation. Extensive assessments, including evaluations on 23 classical benchmark functions, demonstrate the efficacy of the b-AOA. It consistently achieves accurate solutions, exhibits robustness in addressing a wide range of optimization problems, and stands out as a promising choice for various applications. In terms of the AVR system, comparative analyses highlight the superiority of the proposed approach in transient response characteristics, with the shortest rise and settling times and zero overshoot. Additionally, the b-AOA approach excels in frequency response, ensuring robust stability and a broader bandwidth. Furthermore, the proposed approach is compared with various state-of-the-art control methods for the AVR system, showcasing an impressive performance. These results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

Keywords: arithmetic optimization algorithm; elite opposition-based learning; pattern search; PIDND 2 N 2 controller (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/23/4810/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/23/4810/ (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:jmathe:v:11:y:2023:i:23:p:4810-:d:1289848

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

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