Evaluation of Automatic Voltage Regulator's PID Controller coefficients using Python

Gopi, Pasala; Ramesh, M.; Lalitha, M. Padma

doi:10.1109/mascon51689.2021.9563458

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…This method is a widely used empirical methodology for adjusting PID controllers. It offers a simple method for determining the proportional, integral, and derivative gains and is based on the system's response to step changes 33 . The following steps are used to optimize the PID coefficients 13 .…”

Section: Tuning Of Lfc Controllermentioning

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

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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: Tuning Of Lfc Controllermentioning

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

View full text Add to dashboard Cite

show abstract

“…Tis can be mitigated by incorporating an AVR into the power grid. Te key role of the AVR is to keep the grid terminal voltage as constant, but the AVR does not perform this task alone and requires a PI/PID controller for efective control of the grid terminal voltage [3,4].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Behavior and Stability Analysis of Automatic Voltage Regulator with Parameter Uncertainty

Gopi¹,

Varma

Kalyan³

et al. 2023

International Transactions on Electrical Energy Systems

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This research article describes a novel optimization technique called simulink design optimization (SDO) to compute the optimal PID coefficients for an automatic voltage regulator (AVR). The time-domain performance of the proposed controller was analyzed using MATLAB/Simulation, and its performance was compared with that of water cycle algorithm, genetic algorithm, and local unimodal sampling algorithm-based PID controllers. The robustness of the proposed controller was verified by applying the disturbances to the generator field voltage and the amplifier parameter uncertainty. The studies presented in literature were discussed the AVR loop stability using the Bode plot which will not give the minimum stability margins. This study proposes a novel stability analysis called disk-based stability analysis to authenticate the stability of the AVR loop which is obtained by the classical analysis. This stability was compared with the proposed stability analysis. The MATLAB results reveal that the SDO-PID controller regulates the terminal voltage of the generator precisely, is more robust to parameter uncertainty, and is more stable than the other controllers. The maximum allowable parameter uncertainty of the amplifier model was identified as 102% of its nominal parameters. The stability margins are recognized as DGM = 10.40 dB and DPM = 56.50° for the AVR stability.

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“…HE voltage profile in a power system is closely related to some important factors such as reliability, control, and power quality [1], and when it deviates from its desired level, it can result in various changes in the system dynamics and lifespan of electrical equipment connected to the grid [2], [3]. Some equipment such as sensitive electronic devices may be particularly vulnerable to voltage fluctuations.…”

Section: Introductionmentioning

confidence: 99%

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

Gopi,

Mahdavi,

Alhelou

2023

IEEE Open J. Power Energy

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In this paper, the authors propose a novel design approach for the PID controller in the automatic voltage regulator (AVR) system using the Naked Mole Rat Algorithm (NMRA). The proposed algorithm has been extensively tested through MATLAB simulation studies. These studies have confirmed the effectiveness of the NMRA tuning method in achieving improved AVR system performance compared to the other tuning methods in the literature. In addition to performance evaluation, this article also investigates the robustness of the AVR system with an NMRA-tuned PID controller. This was achieved by conducting a disk-based stability analysis under model uncertainty. Also, the proposed NMRA-PID controller has a higher gain change tolerance than the TSA-PID controller for the given perturbations in the feedback loop of the AVR system for the specified values of disk size and skew. By studying the performance and robustness of the AVR system with an NMRA-tuned PID controller and comparing it with other techniques, this study provides insights into the benefits and capabilities of the proposed approach.

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Evaluation of Automatic Voltage Regulator's PID Controller coefficients using Python

Cited by 5 publications

References 10 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

Dynamic Behavior and Stability Analysis of Automatic Voltage Regulator with Parameter Uncertainty

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

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