Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 6 November 2023 / Approved: 7 November 2023 / Online: 7 November 2023 (10:28:45 CET)

A peer-reviewed article of this Preprint also exists.

Ekinci, S.; Çetin, H.; Izci, D.; Köse, E. A Novel Balanced Arithmetic Optimization Algorithm-Optimized Controller for Enhanced Voltage Regulation. Mathematics 2023, 11, 4810. Ekinci, S.; Çetin, H.; Izci, D.; Köse, E. A Novel Balanced Arithmetic Optimization Algorithm-Optimized Controller for Enhanced Voltage Regulation. Mathematics 2023, 11, 4810.

Abstract

This work introduces an innovative approach that unites a PIDND2N2 controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND2N2 controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through 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 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 impressive performance. These important 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; PIDND2N2 controller

Subject

Engineering, Electrical and Electronic Engineering

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