Automatic Voltage Regulator Research Articles

Investigating PID Controller Effectiveness: An Extensive Analysis and Wide-ranging Uses

This study offers an in-depth investigation of the performance of proportional-integral-derivative (PID) controllers, providing an extensive evaluation and analyzing a wide range of applications. PID controllers, essential feedback mechanisms in various domains, are recognized as foundational instruments in control systems. This study evaluates PID controllers in in scenarios such as DC motor speed regulation, power system stability, Automatic Voltage Regulator (AVR) performance optimization, time delay processes, load frequency management, DC drive control, systematic process stability, and their developments in industrial control. The purpose of the study is to highlight the adaptability and effectiveness of PID controllers in contemporary control systems, including how artificial intelligence (AI) can be integrated into PID controller tuning.

Neural network optimizer of proportional-integral-differential controller parameters

Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.

Study on fast transient overvoltage characteristics of substation under UHV disconnector operation

Abstract Due to the short duration of fast transient overvoltage in the substation, the suppression effect under the control strategy of traditional optimization equipment and switches is not good. Therefore, the characteristics of fast transient overvoltage in substation under the operation of a UHV disconnector are proposed. The fast transient condition of the substation is analyzed, the corresponding simulation method is set, and it is simulated. The elimination operation is carried out by using the reverse sequence backtracking formula, and the relevant parameters of the fast transient condition simulation of the substation are obtained. The inductance of the substation is calculated in the fast transient process, the potential in the equivalent circuit is obtained by using the capacitance and inductance, and the reactive power compensation capacity on the electromagnetic transient model of the fast transient process is comprehensively considered, so as to calculate the rapid transient overvoltage of the substation and realize the research on overvoltage characteristics. The method in this paper can ensure the rapid transient overvoltage level decline, successfully realize the automatic voltage regulation, effectively maintain the stability of voltage, and effectively restrain overvoltage to keep it within an acceptable range.

Optimizing AVR system performance via a novel cascaded RPIDD2-FOPI controller and QWGBO approach.

Maintaining stable voltage levels is essential for power systems' efficiency and reliability. Voltage fluctuations during load changes can lead to equipment damage and costly disruptions. Automatic voltage regulators (AVRs) are traditionally used to address this issue, regulating generator terminal voltage. Despite progress in control methodologies, challenges persist, including robustness and response time limitations. Therefore, this study introduces a novel approach to AVR control, aiming to enhance robustness and efficiency. A custom optimizer, the quadratic wavelet-enhanced gradient-based optimization (QWGBO) algorithm, is developed. QWGBO refines the gradient-based optimization (GBO) by introducing exploration and exploitation improvements. The algorithm integrates quadratic interpolation mutation and wavelet mutation strategy to enhance search efficiency. Extensive tests using benchmark functions demonstrate the QWGBO's effectiveness in optimization. Comparative assessments against existing optimization algorithms and recent techniques confirm QWGBO's superior performance. In AVR control, QWGBO is coupled with a cascaded real proportional-integral-derivative with second order derivative (RPIDD2) and fractional-order proportional-integral (FOPI) controller, aiming for precision, stability, and quick response. The algorithm's performance is verified through rigorous simulations, emphasizing its effectiveness in optimizing complex engineering problems. Comparative analyses highlight QWGBO's superiority over existing algorithms, positioning it as a promising solution for optimizing power system control and contributing to the advancement of robust and efficient power systems.

Augmenting the Stability of Automatic Voltage Regulators through Sophisticated Fractional-Order Controllers

The transition from traditional to renewable energy sources is a critical issue in current energy-generation systems, which aims to address climate change and the increased demand for energy. This shift, however, imposes additional burdens on control systems to maintain power system stability and quality within predefined limits. Addressing these challenges, this paper proposes an innovative Modified Hybrid Fractional-Order (MHFO) automatic voltage regulator (AVR) equipped with a fractional-order tilt integral and proportional derivative with a filter plus a second-order derivative with a filter FOTI-PDND2N2 controller. This advanced controller combines the benefits of a (FOTI) controller, known for enhancing dynamic performance and steady-state response, with a (PDND2N2) controller to improve system robustness and adaptability. The proposed MHFO controller stands out with its nine tunable parameters, providing more extensive control options than the conventional three-parameter PID controller and the five-parameter FOPID controller. Furthermore, a recent optimization approach using a growth optimizer (GO) has been formulated and applied to optimally adjust the MHFO controller’s parameters simultaneously. The performance of the proposed AVR based on the MHFO-GO controller is scrutinized by contrasting it with various established and developed optimization algorithms. The comparative study shows that the AVR based on the MHFO-GO controller surpasses other AVR controllers from the stability, robustness, and dynamic response speed points of view.

Experimental test results of an automatic voltage regulator with independent phase voltage controller

The growing number of distributed renewable energy sources and dynamic constant-power loads (e.g. electric vehicle charging stations) pose new challenges for network operators. These changes result in alterations to network load profiles and load flows, leading to greater voltage volatility. One effective solution to these problems can be the use of automatic voltage regulators (AVRs), which stabilize and symmetrize voltage output, whether at distribution transformers (DTs) or elsewhere in the distribution network. The device developed by the authors consists of two bidirectional power converters and three single-phase transformers connected in series to the low-voltage grid as a stabilizer. The proposed control system provides accurate and fast regulation of the AVR’s output voltage (within the range of ±10% of the nominal grid voltage), with each phase being independently adjusted, regardless of the type of power load. The article includes test results demonstrating selected functionalities of the developed AVR. The physical model of the device discussed in the article is a research component of the LINTE2 laboratory of the Gdansk University of Technology.

An adaptive fractional controller design for automatic voltage regulator system: sigmoid-based fractional-order PID controller

The primary objective of a power system is to provide safe and reliable electrical energy to consumers. This objective is achieved by maintaining the stability of the power system, a multifaceted concept that can be divided into three distinct classes. The focus of this study is on one of these classes, voltage stability. A critical component in maintaining voltage stability is the automatic voltage regulator (AVR) system of synchronous generators. In this paper, a novel control method, the sigmoid-based fractional-order PID (SFOPID), is introduced with the aim of improving the dynamic response and the robustness of the AVR system. The dandelion optimizer (DO), a successful optimization algorithm, is used to optimize the parameters of the proposed SFOPID control strategy. The optimization process for the DO-SFOPID control strategy includes a variety of objective functions, including error-based metrics such as integral of absolute error, integral of squared error, integral of time absolute error, and integral of time squared error, in addition to the user-defined Zwee Lee Gaing’s metric. The effectiveness of the DO-SFOPID control technique on the AVR system has been rigorously investigated through a series of tests and analyses, including aspects such as time domain, robustness, frequency domain, and evaluation of nonlinearity effects. The simulation results are compared between the proposed DO-SFOPID control technique and the fractional-order PID (FOPID) and sigmoid-based PID (SPID) control techniques, both of which have been tuned using different metaheuristic algorithms that have gained significant recognition in recent years. As a result of these comparative analyses, the superiority of the DO-SFOPID control technique is confirmed as it shows an improved performance with respect to the other control techniques. Furthermore, the performance of the proposed DO-SFOPID control technique is validated within an experimental setup for the AVR system. The simulation results show that the proposed DO-SFOPID control technique is highly successful in terms of stability and robustness. In summary, this study provides comprehensive evidence supporting the effectiveness and superiority of the DO-SFOPID control technique on the AVR system through both simulation and experimental results.

A fast and robust sliding mode controller for automatic voltage regulators in electrical power systems

In this paper, a fast and robust sliding mode controller (SMC) based on a novel multi-variable sliding function is proposed for Automatic Voltage Regulators (AVRs) in electrical power systems. Lyapunov stability theorem is used to guarantee the asymptotic stability of the proposed controller. As the proposed controller is multi-variable, there may be different optimum controller parameter sets that result in performance close to each other. Hence, two optimum sets of parameters are explored by two well-known algorithms, namely, Sine Cosine Algorithm and Grey Wolf Optimization. A new objective function is considered for the optimizations, including an overshoot constraint. The performance of the proposed controller with the optimum parameter sets is evaluated for five different parameter uncertainties and load disturbance scenarios, and the resulting time domain measurements are compared with the results of recently published SMCs. A 38.36 % improvement in settling time was observed compared to the most recent study using the same realistic AVR model. In addition, the proposed controller suppressed different load disturbances, including parasitic ones, and quickly recovered the AVR output. All results revealed that the proposed controller achieved the best performance in terms of speed and robustness compared to existing controllers, despite the controller and exciter limitations.

A New Hybrid Intelligent Fractional Order Proportional Double Derivative + Integral (FOPDD+I) Controller with ANFIS Simulated on Automatic Voltage Regulator System

In the dynamic realm of Automatic Voltage Regulation (AVR), the pursuit of robust transient response, adaptability, and stability drives researchers to explore novel avenues. This study introduces a groundbreaking approach—the Hybrid Intelligent Fractional Order Proportional Derivative2+Integral (FOPDD+I) controller—leveraging the power of the Adaptive Neuro-Fuzzy Inference System (ANFIS). The novelty lies in the comparative analysis of three scenarios: the AVR system without a controller, with a traditional PID controller, and with the proposed FOPDD+I-based ANFIS. By fusing ANFIS with a hybrid controller, we forge a unique path toward optimized AVR performance. The hybrid controller, based on FOPID (Fractional Order Proportional Integral Derivative) principles, synergizes individual integral factors with ANFIS, augmenting them with a doubled derivative factor. The ANFIS design employs a hybrid optimization learning scheme to fine-tune the Fuzzy Inference System (FIS) parameters governing the AVR system. To train the fuzzy inference system, we utilize a Proportional-Integral-Derivative (PID) simulation of the entire AVR system, capturing essential data over approximately seven seconds. Our simulations, conducted in MATLAB/Simulink, reveal impressive performance metrics for the FOPDD+I-ANFIS approach: Rise time: 1.1162 seconds, settling time: 0.5531 seconds, Overshoot: 0%, Steady-state error: 0.00272, These results position our novel approach favorably against existing works, underscoring the transformative potential of intelligent creation in AVR control.

Fractional High-Order Differential Feedback Controller Based on Meta-Heuristic Algorithms for Automatic Voltage Regulator

In this study, optimally parameter tuning of fractional high-order differential feedback controller (FHODFC) for an automatic voltage regulator (AVR) system regulating the terminal voltage of the synchronous generator is presented. Recently developed meta-heuristic optimization techniques named honey badger algorithm (HBA) and gorilla troops optimizer (GTO) have been employed for the first time in order to optimally determine ten different parameters of the FHODFC. The performance of the proposed controllers, that is, HBA-FHODFC and GTO-FHODFC, is analyzed in terms of transient and steady state responses, and robustness against uncertainties and external disturbances. In addition, their performance is compared to a FHODFC of which parameters were tuned by using particle swarm optimization algorithm in a previous study. The results indicate that the proposed HBA-FHODFC and GTO-FHODFC controllers provide zero overshoot and better results in terms of settling time and objective function then the PSO tuned FHODFC. Therefore, the proposed controllers can be used as an effective method in the AVR system.

Designing Heuristic-Based Tuners for Fractional-Order PID Controllers in Automatic Voltage Regulator Systems Using a Hyper-Heuristic Approach

This work introduces an alternative approach for developing a customized Metaheuristic (MH) tailored for tuning a Fractional-Order Proportional-Integral-Derivative (FOPID) controller within an Automatic Voltage Regulator (AVR) system. Leveraging an Automated Algorithm Design (AAD) methodology, our strategy generates MHs by utilizing a population-based Search Operator (SO) domain, thus minimizing human-induced bias. This approach eliminates the need for manual coding or the daunting task of selecting an optimal algorithm from a vast collection of the current literature. The devised MH consists of two distinct SOs: a dynamic swarm perturbator succeeded by a Metropolis-type selector and a genetic crossover perturbator, followed by another Metropolis-type selector. This MH fine-tunes the FOPID controller’s parameters, aiming to enhance control performance by reducing overshoot, rise time, and settling time. Our research includes a comparative analysis with similar studies, revealing that our tailored MH significantly improves the FOPID controller’s speed by 1.69 times while virtually eliminating overshoot. Plus, we assess the tuned FOPID controller’s resilience against internal disturbances within AVR subsystems. The study also explores two facets of control performance: the impact of fractional orders on conventional PID controller efficiency and the delineating of a confidence region for stable and satisfactory AVR operation. This work’s main contributions are introducing an innovative method for deriving efficient MHs in electrical engineering and control systems and demonstrating the substantial benefits of precise controller tuning, as evidenced by the superior performance of our customized MH compared to existing solutions.

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

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

Artificial rabbits optimization algorithm based tuning of PID controller parameters for improving voltage profile in AVR system using IoT

The power system is mainly affected by transient situations caused by switching heavy loads. The system may become unstable when transient situations occur. The power system should be able to perform continuous operation to maintain its voltage within acceptable limits. To achieve more stability and increase its speed of response, an Automatic Voltage Regulator (AVR) system requires the inclusion of a controller. The AVR system in the generating station uses the PID controller to adjust the abnormal voltage caused by transient conditions. To maintain the nominal voltage level under all the load conditions in the system, a bio-inspired meta-heuristic algorithm called Artificial Rabbit Optimization (ARO) algorithm is proposed to tune the PID controller gain parameters and obtain the optimal gain, thereby the AVR system adjusts the generator terminal voltage to nominal levels. The ARO algorithm inspires natural survival techniques to improve the AVR performance by reducing errors. To maintain a stable voltage profile in a power system, this research mathematically models survival techniques using the Internet of Things (IoT) to obtain an optimal solution. As a result, all devices connected to the power network receive a stable voltage that ensures their voltage reliability. The effectiveness of the proposed algorithm for the AVR system is verified with the MATLAB R2022a model, and the statistics functions are implemented in the module of Pandas, Scipy and mathematical investigations done in Numpy. The proposed ARO algorithm achieves a better voltage profile with less than 12.63% maximum peak overshoot during the system's transient response. The proposed algorithm provides the fastest response and highest stability comparable to other optimisation algorithms.

On the assessment of meta-heuristic algorithms for automatic voltage regulator system controller design: a standardization process

On the assessment of meta-heuristic algorithms for automatic voltage regulator system controller design: a standardization process

Load frequency and voltage control of two area interconnected power system using covariance matrix adaptation evolution strategy based Aquila optimization optimized fast fuzzy-fractional order tilt integral derivative controller

In this paper, an optimal tuning method is given for a Fast Fuzzy-Fractional Order Tilt Integral Derivative Controller (HFF-FOTIDC) used in the Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) systems of a two-area interconnected power system. LFC is in charge of managing the frequency and real power flows in the system. AVR is in charge of maintaining the voltage profile and managing the flow of reactive power. In Area 1, a step disturbance is used to study how the system works in a dynamic way. By looking at the system's voltage, power flow through the tie lines, and frequency, the experts can figure out how the system will react. The proposed control techniques combine two well established control logic, which are fast fuzzy control logic and fractional order tilt integral derivative control logic. The main goal is to decrease voltage and frequency changes caused by step disturbances and return them to their normal values. The simulation results show how good the suggested system is by comparing it to systems that use traditional proportional integral controllers and traditional Integral controllers. By using the finest tuning method for the fast fuzzy-fractional order tilt integral derivative controller, the designed system has better performance than standard controllers at reducing fluctuations and getting the desired frequency and voltage responses. The parameters of the proposed controller are optimized by using Covariance Matrix Adaptation Evolution Strategy based Aquila Optimization (CMAESAO) optimization technique.

Development of AVR controller performance using exponential distribution and transit search optimization techniques

This paper attempts to obtain the optimal solution to enhance the performance of the Automatic Voltage Regulator (AVR) Controller, as it is an essential tool to control the synchronous generator output voltage. The controller improves AVR system stability and response time; moreover, it is demonstrated that the Proportional Integral Derivative (PID) controller achieves the goal by applying two artificial intelligence techniques to design the optimal values of the Automatic Voltage Regulator (AVR) PID controller for a single area model. The first is the Exponential Distribution Optimization Algorithm (EDO), and the second is the Transit Search Optimization Algorithm (TS). EDO and TS are used to determine the best PID controller parameters and have also recently been developed in the breadth of optimization problems and associated computational complexities field. The objective function, Integrated Square Error (ISE), minimizes the error voltage for improved stability and response. The outcomes are compared to various optimization techniques to prove the validation of the two proposed methods. The results show that the EDO and TS proved their superiority through their stability level to the AVR system and their steady-state error improvement. Moreover, the dominant effect of damping frequency decreases the oscillation and the reduced maximum overshoot that protects the loads from being subjected to non-permissible over-voltage levels. Finally, a robustness test is applied to the two proposed optimization methods to prove their reliability and effectiveness.

Jellyfish Search Optimized Gated Recurrent Unit Based FOPID/PID for Enhanced Automatic Voltage Regulator

The most essential mechanism for regulation in power systems is the Automatic Voltage Regulator (AVR) device, which maintains generator terminal voltage within predefined parameters. This research paper introduces an innovative approach to enhance AVR system performance through the ideal setting for a fractional-order PID (FOPID) controller that leverages Bidirectional Gate Recurrent Unit (BiGRU)-based deep learning techniques in conjunction with the Jellyfish Search Optimization (JSO) algorithm. To enhance flexibility and precision in control, the conventional proportional integral derivative (PID) controller is replaced with a FOPID controller, whose parameters are optimized by means of the JSO algorithm. The effectiveness of the proposed Jellyfish Search Optimization-based most advanced controllers (JSO-FOPID/PID) is compared with the existing FOPID controller implemented using the Seagull Optimization Algorithm (SOA-FOPID). Comprehensive analyses, including transient time, robustness, stability, and convergence analysis, are conducted subject to applying both stable and alternating load situations to validate the proposed approach. Experimental validation is performed using the MATLAB R2022a application with FOMCON tools and a laboratory prototype for testing. The simulations and experiments demonstrate that the projected AVR consistently delivers optimum dynamic responses and enhances overall stability when compared to existing methods, underscoring its efficacy in voltage regulation and power system control.

Achieving improved stability for automatic voltage regulation with fractional-order PID plus double-derivative controller and mountain gazelle optimizer

Achieving improved stability for automatic voltage regulation with fractional-order PID plus double-derivative controller and mountain gazelle optimizer

Dynamic Voltage Stability of an Electric Power Network with Double Fed Induction Wind Power Generators

In recent years, the large penetration of wind power poses new challenges for the voltage stability analysis of an electric power network. In this paper is studied the effect of large scale integration of wind power in the dynamic voltage stability of a power network under a fault condition. The automatic voltage regulators of the generating units, the turbine speed governors and the double fed induction generator were modeled. Different load models were used and the under load tap changers were also taken into account. The simulation results were obtained using the EUROSTAG software package. Finally, some conclusions that provide a better understanding of the dynamic voltage stability in a system with a large amount of wind power generation are pointed out.

Optimal design of controller for automatic voltage regulator performance enhancement: a survey

Optimal design of controller for automatic voltage regulator performance enhancement: a survey