Voltage Regulator System Research Articles

Optimal design of Fractional order PID controller based Automatic voltage regulator system using gradient-based optimization algorithm

Considering the superior control characteristics and increased tuning flexibility of the Fractional-Order Proportional Integral Derivative (FOPID) controller than the conventional PID regulator, this article attempts to explore its application in the optimal design of the Automatic Voltage Regulator (AVR). Since FOPID has two additional tuning parameters (µ and ʎ) than its mentioned conventional counterpart, its tuning process is comparatively difficult. To overcome the stated issue, a self-regulated off-line optimal tuning method based on the Gradient-Based Optimization (GBO) algorithm is adopted in the current study. The optimal FOPID gains are obtained by minimizing the selected Fitness Function (FF) that is chosen as Integral Time Absolute Error (ITAE) in the current study. The simulations are performed using MATLAB/SIMULINK 2018a to test and compare the performance of the proposed GBO-based optimal AVR design based on the dynamic response, stability, and robustness evaluation metrics with some of the recently published metaheuristic optimization algorithm based optimal AVR designs in the literature. The results show that the proposed AVR design provides the most optimal dynamic response and enhanced stability among the considered AVR designs, thus proves its efficacy and essence.

Maiden Application of Fuzzy-2DOFTID Controller in Unified Voltage-Frequency Control of Power System

This article presents an amalgamated pattern of automatic load frequency control (ALFC) and automatic voltage regulator (AVR) system in a three-area interconnected power system using the Fuzzy two-degree-of-freedom tilt-integral-derivative controller (F2DOFTID). The multi-area system includes single-stage reheat thermal plants and Solar Thermal Power Plant (STPP) in Area-1 and Heavy-Duty Gas Turbines (HDGT) in Area-2 and Area-3. An incipient attempt is made to incorporate the HDGT plant in amalgamated control of the power system. Relevant generation rate constraints (GRC) and Governor Dead Band (GDB) are rendered for thermal plants. In both ALFC and AVR systems of all areas, a first attempt is made to implement an F2DOFTID controller to alleviate the frequency and voltage deviations. In this investigation, an algorithm named Harris Hawks Optimization (HHO) is efficaciously used to accomplish optimal controller parameters. Concerning all time-domain behaviors, F2DOFTID controller performance is superior relative to the TID and 2DOFTID controller. The AVR effect proclaims a substantial improvement in system dynamics. In this amalgamated scenario, the aftermath of the high voltage direct current (HVDC) tie-line and the usage of energy storage devices such as ultra-capacitors (UC) are found superlative in the amelioration of system performance. Similarly, by modifying the generator parameters and synchronizing coefficients, the robustness of the proposed controller is measured, which signifies that obtained controller parameters during nominal conditions are resilient enough and not to be altered. Eventually, the system is also studied in OPAL-RT OP 4510 RT Lab hardware set-up for real-time analysis.

Adaptive Voltage Regulation Control Strategy in a Stand-Alone Islanded DC Microgrid based on distributed Wind / Photovoltaic / Diesel / Energy Storage Hybrid Energy Conversion System

An adaptive approach for optimal tuning of a SMC for an automated voltage regulator system is displayed in this study. The approach is centered on hybrid of the GA and MOPSA. In addition, unique objective functions for the controller's parameter optimization are suggested. The performance of the resulting perfect sliding mode controller is confirmed by comparing it to controllers adjusted using various techniques that have been published in the literature. The simulation outcomes indicate that controllers tuned with the projected MOPSO and GA algorithms outperform controllers tuned with existing methods. In addition, a comparison study is performed to select the best controller for use in AVR systems. The suggested algorithm's major benefit is a considerable boost in convergence speed. With step changes and step load modifications in input wind power, the system model with built-in intelligent controller is generated in MATLAB/SIMULINK. The benefits of the recommended intelligent control algorithm are confirmed by comparing the outcomes of the sliding mode controller and the projected MOPSO self-tuned controller. The findings show that the hybrid Wind/PV system's reactive power adjustment capabilities. When used in conjunction with BES, it is extremely successful in optimising the voltage profile although providing active energy to local load.

Simulation based of DC-DC Converter for AVR System and PID Controller with Tree Seed Algorithm based AVR System for Synchronous Generator

The voltage is supervised by AVR an automatic voltage regulator. It transforms the varying voltage into a constant voltage. The most prevalent cause of voltage fluctuation is changes in load on the supply system. An excitation system is a system that provides the necessary field current to the synchronous machine's rotor winding. The most important characteristics of an excitation system are dependability under all operating circumstances, ease of control, and ease of maintenance, stability, and quick transient response. In the literature, several control systems, such as in the literature, PID controllers, adaptive control methods, and intelligent control methods have all been suggested. On the one hand to get an accurate and quick generator terminal voltage control, the usage of a step down chopper in the exciter circuit is suggested in this study. DC-DC converters are also called as Choppers. The Step down chopper, It changes a given DC input voltage into a determined DC output voltage The input voltage source is tie up with governable solid state device that acts as a switch. Switches can be made using metal oxide semiconductor field effect transistors (MOSFETs) or insulated gate bipolar transistors (IGBT). The field circuit of the generator is associated to the chopper and a Praportional-Intigral controller deviates the converter duty cycle to vary the generator's terminal voltage. to regulate the generator field voltage. On the other hand, Tree-Seed Algorithm (TSA) algorithm based PID controller is put forward for automatic voltage regulator system. The suggested approach calculates PID coefficients to the best of its ability. The execution of this TSA-based optimum PID controller is compared to that of various PID controllers produced in the literature utilizing different meta-hermetic optimization techniques. Comparative research in for the suggested schemes has a superior transient response and is more resistant to fluctuations in Generator load and DC input voltage.

Analisa Peralihan Tanggapan Tegangan Sistem Automatic Voltage Regulator (AVR) Tipe Arus Searah Dengan Pengendali 2 Derjat Kebebasan

This journal discusses the design and analysis of the transfer response of the direct cuurent type of Automatic Voltage Regulator (AVR) system with 2 degrees of freedom controller. Direct current type of the AVR system is represented in the form of transfer function. For 2 degrees of freedom controllers are designed using a parallel architecture with the help of Matlab software using predefined design criteria. The types of controllers used consist of Proportional Differential (PD), Proportional Integral (PI), Proportional Integral Differential (PID), Proportional Differential with First Order Filters in the Differential Section (PDF) and Proportional Intregral Differential with First Order Filters in the Differential Section (PIDF). For the transition analysis, the observed parameters consist of rise time, peak time, steady state time, maximum pass value and peak value. The results of the analysis show that the controller that meets the design criteria is a Proportional Differential (PD) controller with an uptime parameter value of 0.2808 seconds, a peak time of 1.3354 seconds, a steady state time of 0.7017 seconds, a maximum pass of 0% and a peak value of 0.9512. For the Proportional Differential controller with First Order Filter in the Differential Section (PDF) with an increase time parameter value of 0.4177 seconds, a peak time of 1.4684 seconds, a steady state time of 0.8453 seconds, a maximum pass of 0% and a peak value of 0.9502.

Fractional-variable-order digital controller design tuned with the chaotic yellow saddle goatfish algorithm for the AVR system

In this paper, an optimisation method utilising the yellow saddle goatfish algorithm (YSGA) with a new fitness function is proposed to design two types of fractional-variable-order PID (FVOPID) digital controllers for the automatic voltage regulator (AVR) system. Simulations and comparisons of the results are presented, showing that variable-order control can perform better than the existing solutions for the AVR system. Additionally, we include a stability analysis of a closed-loop system by utilisation of the Nyquist stability criterion.

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Equilibrium optimizer tuned novel <scp>FOPID‐DN</scp> controller for automatic voltage regulator system

An Optimal Robust State Feedback Controller for the AVR System-Based Harris Hawks Optimization Algorithm

This paper presents a robust tracking controller for the automatic voltage regulator (AVR) system, where both system uncertainties and external disturbances are taken into account. The proposed control scheme combines optimal feedback control with robust control. The parameter gains of the proposed controller have been selected based on Lyapunov theorem to ensure the stability of the closed-loop control system. Moreover, the parameters of the feedback control term are optimized using the Harris Hawks Optimization (HHO) algorithm. The performance of the proposed controller is compared with several Proportional Integral Derivative (PID) controllers optimized with different optimization algorithms. In addition, the fractional order PID (FOPID) controller is used for comparison. The validity of the proposed control scheme is illustrated through the simulation of the AVR system with three cases of simulation have been discussed.

HHO-based Model Predictive Controller for Combined Voltage and Frequency Control Problem Including SMES

This paper discusses the modelling and control of a combined load frequency control (LFC) and automatic voltage regulator (AVR) system for a multi-area power system network with each generating area includes thermal, diesel, and solar thermal power plant. Superconducting magnetic energy storage is incorporated with the LFC loop to provide auxiliary control against instantaneous changes in active power demand. Model Predictive Controller (MPC) has been employed in this study to improve the performance of AVR and LFC loops, and controller weights are fine-tuned with the help of Harris Hawks Optimization (HHO) approach. The effectiveness of the proposed MPC-HHO algorithm has been examined by comparing its transient performance indices with that of conventional MPC, PID, FOPID, fuzzy PID, integral double derivative with derivative filter controller as well as Particle Swarm Optimization and Sine Cosine Algorithm based Model Predictive Controllers. The proposed MPC-HHO controller gives superior results than the above-mentioned controllers.

Distributed voltage regulation using permissioned blockchains and extended contract net protocol

Distributed voltage regulation schemes within active distribution networks (ADNs) are receiving plenty of attention because they reduce latency bottlenecks. However, previous schemes often employ a trusted moderator to govern agent communication, thereby exposing potential trust issues that may affect agent performance. Blockchain technology can avoid the need for intermediaries, since it is a fully decentralized network that is governed by agents using distributed consensus mechanisms. Thus, this paper proposes a blockchain-based system for voltage regulation in ADNs that provides a competitive marketplace wherein agents can rationally bid for voltage regulation services. The proposed system utilizes a smart contract that i) enables asynchronous negotiation between agents to mitigate multiple violations simultaneously using the extended contract net protocol (ECNP), and ii) maintains a credit score that reflects the trustworthiness of an agent in resolving voltage violations. The proposed system also develops a bidding and pricing scheme for voltage regulation services that considers both active and reactive power contributions. A permissioned blockchain implementation is used to ensure that only known agents are permitted to access the system. The proposed system is implemented on the Hyperledger Fabric platform, where simulations executed on a 69 bus system demonstrate the system’s ability to mitigate multiple voltage violations simultaneously. As demonstrated by the simulation results, the highlight of the main contribution of the paper is the ability of the proposed system to mitigate multiple voltage violations simultaneously via the ECNP, thereby utilizing less bidding cycles to resolve voltage violations as compared to the original contract net protocol.

Impact of the hybrid reactive power compensator on the power grid used a fuzzy PI regulator

The work presented in this article is a contribution to the problem of controlling reactive powers and voltages in an electrical network. Among these control tools, the static reactive power compensator (SVC) was chosen because of its simplicity of control. SVC is one of the Alternative Flexible Current Transmission Systems (FACTS) devices which help to solve the problems encountered in the operation of electrical networks, either on the distribution side or on the transport side. To increase its compensation efficiency in the face of harmonic currents which cause voltage distortion, we have introduced a three-phase harmonic filter. This new hybrid SVC is used to control the reactive power, the voltage and in addition to reduce the voltage distortion and the correction of the power factor in the electrical energy transport network. In order to improve its efficiency, two voltage regulation systems have been chosen in the control system for this compensator, the fuzzy PI regulator and the PIP regulator.

An Analysis of the Application of Energy Storage Technology in Power Systems

With the rapid development of China’s economy, the coverage area of China’s power grid is expanding, and users have higher requirements for the quality and reliability of electrical energy. And the development of energy storage technology has improved the stability of power system operation, voltage and frequency regulation, load compensation, and also injected new development ideas into the planning and design of power systems, manufacturing control, etc. Energy storage technology occupies a very important position in the power system, the needs of its power system so as to enhance the availability of renewable energy and ensure that the power system can operate safely and stably. This paper provides further analysis and discussion on the application of energy storage technology in power systems.

Chaotic-based particle swarm optimization algorithm for optimal PID tuning in automatic voltage regulator systems

Introduction. In an electrical power system, the output of the synchronous generators varies due to disturbances or sudden load changes. These variations in output severely affect power system stability and power quality. The synchronous generator is equipped with an automatic voltage regulator to maintain its terminal voltage at rated voltage. Several control techniques utilized to improve the response of the automatic voltage regulator system, however, proportional integral derivative (PID) controller is the most frequently used controller but its parameters require optimization. Novelty. In this paper, the chaotic sequence based on the logistic map is hybridized with particle swarm optimization to find the optimal parameters of the PID for the automatic voltage regulator system. The logistic map chaotic sequence-based initialization and global best selection enable the algorithm to escape from local minima stagnation and improve its convergence rate resulting in best optimal parameters. Purpose. The main objective of the proposed approach is to improve the transient response of the automatic voltage regulator system by minimizing the maximum overshoot, settling time, rise time, and peak time values of the terminal voltage, and eliminating the steady-state error. Methods. In the process of parameter tuning, the Chaotic particle swarm optimization technique was run several times through the proposed hybrid objective function, which accommodates the advantages of the two most commonly used objective functions with a minimum number of iterations, and an optimal PID gain value was found. The proposed algorithm is compared with current metaheuristic algorithms including conventional particle swarm optimization, improved kidney algorithm, and others. Results. For performance evaluation, the characteristics of the integral of time multiplied squared error and Zwe-Lee Gaing objective functions are combined. Furthermore, the time-domain analysis, frequency-domain analysis, and robustness analysis are carried out to show the better performance of the proposed algorithm. The result shows that automatic voltage regulator tuned with the chaotic particle swarm optimization based PID yield improvement in overshoot, settling time, and function value of 14.41 %, 37.91 %, 1.73 % over recently proposed IKA, and 43.55 %, 44.5 %, 16.67 % over conventional particle swarm optimization algorithms. The improvement in transient response further improves the automatic voltage regulator system stability for electrical power systems.

Voltage and frequency control in conventional and PV integrated power systems by a particle swarm optimized Ziegler\u2013Nichols based PID controller

Variations of load demands, expansion of power system by interconnections among different areas and integration of renewable energy sources bring new challenges for stable, reliable and uninterrupted operations of power systems. In this paper, a control technique is proposed to control and optimize the performances of the three models having importance in the present and future energy systems. These are the output variations of an automatic voltage regulation (AVR) system, frequency variations in a load frequency control (LFC) system of a thermal power plant and frequency variations of a PV integrated thermal power plant. The proposed controller is a particle swarm optimized Ziegler–Nichols (ZN) method based proportional-integral-derivative (PID) controller. A particle swarm optimization (PSO) method suffers from the unavailability of prior knowledge of initial values of parameters. Whereas, the classical ZN method leaves the scope for performance improvements of a system. A rejuvenation to the classical ZN method is proposed by integrating PSO. The combined effect optimizes the voltage and the frequency performances, while ensuring system stability. Additionally, different objective functions inspired from energy industry requirements are considered to demonstrate performance improvements of the systems (e.g. maximum overshoot, steady-state error, settling time). The robustness of the proposed method is demonstrated by considering parametric uncertainty in the system. The proposed method is compared with performances of different controllers (e.g. PI, fuzzy PI, fuzzy PID), different iterative soft computing methods (e.g. pattern search, artificial bee colony, different variants of PSO) and classical optimization method (e.g. linear matrix inequality) considering different objective functions and different load disturbances for the aforementioned models. It is also observed that better performances are obtained using a significantly less number of iterations.

Design of an Optimal Controller in a Voltage Regulation System When Powering Submersible Electromechanical Equipment

The paper addresses the issue of designing an optimal controller using the measured state variables of a nonlinear multi-dimensional object with transient disturbances – power supply of submersible electromechanical equipment with AC transmission via a cable power line. We present an approach to the design of an adjustable PI-controller enabling to determine its closed-form parameters with the linearized model of a complex control object. A numerical example for simulation of a power supply highlighting capability of the design algorithm for the optimal controller with the quadratic criteria is provided. The obtained results can be used to tackle problems of adaptive control of remotely powered electromechanical objects without sensors.

A novel fuzzy based weighted aggregation based multi objective function for AVR optimization

Today optimization algorithms are widely used in every application to increase quality, quantity and efficiency of making products as well as to minimize the production cost. Most of the techniques applied on different applications try to satisfy more than one parameter of interest in the design problem. In doing so, an objective function based on weighted aggregation has been designed to fulfill multi-objective optimization (MOO). A lot of computational time and energy is wasted in tuning the value of weighting factor in terms of number of trials each having hundreds of iterations to achieve the optimum solution. To reduce such tedious practice of adjustment of weighting factor with multiple iterations, Fuzzy technique is proposed for auto-tuning of weighting factor in this paper that will benefit the researchers who are working upon optimization of their designed objectives using artificial intelligence techniques. This paper proposes MOO settlement method that does not require complex mathematical equations in order to simplify the weight finding problem of weighted aggregation objective function (WAOF). The results have been compared in terms of time and space efficiency to show the importance of Fuzzy-WAOF (F-WAOF). Further the results taken on Automatic Voltage Regulator (AVR) system for set point tracking, load disturbance, controller effort and modelling errors, prove the superior performance of the proposed method as compared to state of the art techniques.

ЭКОНОМИЧЕСКАЯ ЭФФЕКТИВНОСТЬ БЕСКОНТАКТНОГО АВТОМАТИЧЕСКОГО РЕГУЛИРОВАНИЯ НАПРЯЖЕНИЯ ТИРИСТОРНО-РЕАКТОРНЫМ ПЕРЕКЛЮЧАЮЩИМ УСТРОЙСТВОМ В СИСТЕМЕ ТЯГОВОГО ЭЛЕКТРОСНАБЖЕНИЯ ПОСТОЯННОГО ТОКА

The paper presents results of analysis of disadvantages of contactless automatic voltage regulation (CAVR) system with a reactor switching device (RSD) that is used on direct current electrified railways. It also shows direction of its improvement. The authors have considered a functional scheme of the closed CAVR system of a converter unit with a thyristor-reactor switching device (TRSD) and a TRSNP-12500/10 converter transformer. They have also carried out an engineering and economical comparison of two modes of traction power supply system (TPSS) operation: without application of voltage regulation devices on traction substations with no-load voltage of 3500 V and with application of voltage regulation devices by the CAVR system at stabilization of voltage on levels of 3500, 3600 and 3700 V with various variants of switching devices. As a result, the authors have determined that the use of the CAVR system with the TRSD is economically efficient.

Modelling of a GSA-based framework of an agent-based system within parameter boundaries: applications to robotics and automatic voltage regulator systems

The enormous potential of the agent-based nature-inspired algorithm named the gravitational search algorithm (GSA) remains untapped, so it is the subject of this work. Existing GSA has provided ways to select the super-agents or prune the poor-performing agents. Here, a holistic framework is proposed by introducing a survival boost which re-establishes self-significance of a poor-performing agent and liberates all agents from an infinity trap for acceleration. It restricts the agents within the search space whose violation produces infeasible solutions. The analysis is extended to solve a number of benchmark test functions, an inverse kinematic problem of a 7 DOF robot manipulator, and a voltage regulation problem of an automatic voltage regulator system. The results and comparative studies show better performances in than some of the popular methods from existing literature (e.g., existing GSA, chaotic GSA, different variants of particle swarm optimisation, artificial bee colony, differential evolution, Jaya algorithm).

Modelling of a GSA-based framework of an agent based system within parameter boundaries: applications to robotics and automatic voltage regulator systems

The enormous potential of the agent-based nature-inspired algorithm named the gravitational search algorithm (GSA) remains untapped, so it is the subject of this work. Existing GSA has provided ways to select the super-agents or prune the poor-performing agents. Here, a holistic framework is proposed by introducing a survival boost which re-establishes self-significance of a poor-performing agent and liberates all agents from an infinity trap for acceleration. It restricts the agents within the search space whose violation produces infeasible solutions. The analysis is extended to solve a number of benchmark test functions, an inverse kinematic problem of a 7 DOF robot manipulator, and a voltage regulation problem of an automatic voltage regulator system. The results and comparative studies show better performances in than some of the popular methods from existing literature (e.g., existing GSA, chaotic GSA, different variants of particle swarm optimisation, artificial bee colony, differential evolution, Jaya algorithm).

Optimization of PSVR parameters of condenser based on MATLAB/Simulink simulation

Installing a power system voltage regulator (PSVR) on the condenser can enhance the dynamic voltage control capability of the local high-voltage bus voltage, but there are still few studies on the optimization of PSVR parameters. The dynamic model of the condenser is built to determine the analytical expression between the system voltage disturbance and the change of the control target, and the influence trend of PSVR on the dynamic voltage characteristics of the condenser is analyzed. Furthermore, in the MATLAB/Simulink environment, a PSVR-containing condenser model is built, and a quantitative index for evaluating the phase-frequency characteristics of the condenser is proposed. Based on this index, the PSVR time constant is optimized through the simulation of the dynamic voltage characteristics of the condenser, and using eigenvalue root locus method combined with dynamic simulation to coordinate PSVR gain coefficient, achieve PSVR parameter optimization. The simulation results under the single-machine and three-machine systems show that after the PSVR parameter optimization, the voltage oscillation mode of the condenser is effectively improved.