Robustness and Stability Analysis of Automatic Voltage Regulator Using Disk-Based Stability Analysis

Gopi, Pasala; Mahdavi, Meisam; Alhelou, Hassan Haes

doi:10.1109/oajpe.2023.3344750

Cited by 4 publications

(1 citation statement)

References 35 publications

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“…In addition to these traditional approaches, internal model control (IMC), Tyreus-Luyben (TL), and Cohen-Coon (CC) methods are also employed for assessing the LFC controller settings. However, these approaches have limitations, such as exhibiting aggressive or oscillatory responses, and they may not adequately consider the nonlinearities or uncertainties of the system 4 . The intelligent and nature-inspired methods provide alternate approaches to LFC controller tuning, especially in situations where conventional methods may be time-consuming or unfeasible.…”

Section: Introductionmentioning

confidence: 99%

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Gopi,

Alluraiah,

Kumar

et al. 2024

Sci Rep

Self Cite

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Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as “Porpoising”. This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.

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Section: Introductionmentioning

confidence: 99%

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Gopi,

Alluraiah,

Kumar

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

Refined sinh cosh optimizer tuned controller design for enhanced stability of automatic voltage regulation

Izci,

Rizk-Allah,

Snášel

et al. 2024

Electr Eng

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Performance and robustness analysis of V-Tiger PID controller for automatic voltage regulator

Gopi,

Reddy,

Bajaj

et al. 2024

Sci Rep

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This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications.

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Robustness and Stability Analysis of Automatic Voltage Regulator Using Disk-Based Stability Analysis

Cited by 4 publications

References 35 publications

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability

Refined sinh cosh optimizer tuned controller design for enhanced stability of automatic voltage regulation

Performance and robustness analysis of V-Tiger PID controller for automatic voltage regulator

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