Automatic Voltage Regulator Control Research Articles

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.

Optimizing Automatic Voltage Regulation: A Deep Reinforcement Learning Approach

This paper presents a novel approach to enhance the performance of Automatic Voltage Regulator (AVR) systems in power systems using Deep Reinforcement Learning (DRL). The AVR plays a critical role in maintaining voltage stability and ensuring reliable power delivery. However, conventional control strategies, such as PID controllers, have limitations in handling complex and nonlinear power system dynamics. In this study, the application of DRL techniques is explored, particularly the Twin-Delayed Deep Deterministic Policy Gradient (TD3) algorithm, to AVR control. This algorithm offers the advantage of handling continuous action spaces and enable the controller to learn optimal control policies directly from the system's state information. The results show that the DRL approach outperforms the traditional PID and Neural Network-based control approaches, with the shortest time response and the best voltage regulation performance. The use of DRL in AVR system control shows promising potential for improving the efficiency and accuracy of power system control. This research provides insights into the advantages of DRL for process control and highlights its potential for future applications in power system control.

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

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 the 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 the 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 an impressive performance. These results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

On the control interaction of synchronous machine and inverter-based resources during system-split situations

Motivated by the potential transient oscillation risks in inverter based resource (IBR) dominated power systems, the paper is to identify the unwanted control interactions between traditional synchronous machines (SMs) and IBRs during system-split situations. Modal impedance analysis method is applied to reveal oscillation risk and the underlying mechanism, while electromagnetic transient (EMT) simulation analysis is used to observe reliable oscillation phenomenon. Impedance models of IBRs considering both grid-following (GFL) and grid-forming (GFM) control schemes and SMs equipped with automatic voltage regulator (AVR) and power system stabilizer (PSS) are developed for grid conditions with large frequency and/or voltage deviations, and validated by EMT simulations. Potential adverse control interactions within an exemplary test system are analyzed taking into account the impacts of: 1) renewable penetration level; 2) converter control scheme (GFL or GFM); 3) converter control tuning; 4) SM control setting; 5) grid-support capabilities of converter-interfaced loads. It has been observed that oscillation instability at around several Hz can occur by high penetration of GFL controlled IBRs after system-splits, which can be mitigated by redesigning the AVR & PSS control, or retuning the power/voltage control loops and phase-locked loop (PLL) of GFL converter. However, such measures might inevitably induce other stability issues, e.g. synchronization instability. From the oscillation analysis, it has also been revealed, through replacing part of the GFL converters with GFM converter(s), the oscillation mode at several Hz can disappear, owning to the varied impedance including better damping of GFM than GFL for the frequencies between 1 and 10 Hz.

Output performance evaluation of the automatic voltage regulator system on pre-filter control technique

<p>Automatic voltage regulator (AVR) is used at each generating station or synchronous generators to maintain voltage supply at steady state or at a constant value otherwise the performance of the generator will be affected. The combination of AVR system with controllers clears fluctuation due to variation in load, speed, temperature, and power factor. This causes deviation in generator’s voltage and damage to power equipment. This work presents performance enhancement of AVR system using Proportional Integral and Derivative (PID) with pre-filter control technique. The enhanced performance was achieved by designing a nonlinear model of a synchronous generator, a PID controller and a low pass filter or pre-filter using MATLAB/Simulink model. The introduction of the proposed PID controller with LPF at load variation of 20 seconds, reduces the rise time and the peak time to 5.2975 seconds and 12.31 seconds respectively. This increases the overshoot and the settling time to 4.28 seconds and 17.60 seconds. However, the developed scheme provides a stable time response performance for various desired generator voltages considered. The performance of the proposed scheme was compared with conventional PID controlled AVR system without LPF. The proposed scheme provides more stability as indicated by the percentage overshoot, which is 4.5788% (for PID) and 4.2765% (for PID with prefilter). This has contributed to knowledge an AVR control system with better performance in terms of rise time, peak time, overshoot and settling time for stabilized generator output voltage.</p>

Metaheuristic-Assisted Advanced Control Approach for Time Delayed Unstable Automatic Voltage Regulator

This work proposes a two-degree-of-freedom factional order proportional-integral-derivative (2-DOF FOPID) controller for automatic voltage regulator (AVR) to mitigate the impact of voltage transients and set-point variations in any power system network. An inherent communication time delay is considered in the investigated AVR plant. This inherent time delay occurs due to the presence of amplifier, exciter, generator, and sensor, making the system unstable. Such an unstable AVR system is still unexplored and difficult to control. The suggested control structure of the 2-DOF FOPID is flexible enough from the perspective of tuning and provides enhanced performance of an AVR system at the cost of a large number of controller design parameters. Therefore, the proposed controller is optimized by an advanced meta-heuristic technique; squirrel search algorithm (SSA) which leads to SSA tuned 2-DOF fractional order PID (S2DFPID) controller. Moreover, selecting an appropriate meta-heuristic approach is a very tedious task for such unstable systems and advanced control architecture. Hence, a systematic statistical approach is also employed to select an optimization technique for the specified purpose, and a rigorous comparative assessment of seven state-of-the-art optimization techniques is also presented in this work. Investigation reveals the superior performance of S2DFPID controller compared to SSA-tuned fractional order PID (SFPID), and SSA-tuned traditional PID (SPID) controllers in the presence of set-point variations, external load disturbances and parametric uncertainties.

Design of Hybrid Controller for Automatic Voltage Regulator

Senkron generatörler elektrik enerjisinin üretiminde temel makina olma görevini sürdürmektedir. Senkron generatörlerin çıkış gerilimi ve frekansı uyartım akımı ve devir sayısı değiştirilerek kolayca ayarlanabilmektedir. Genellikle senkron generatörler şebekeye bağlı olarak çalıştıkları için çıkış gerilimi ve frekansının sabit olması gerekmektedir. Gerilimin ayarlanması için kullanılan Otomatik Gerilim Regülatörlerinde çeşitli denetleyici sistemler kullanılmaktadır. Bu çalışmada MATLAB/Simulink programında bulanık mantık tabanlı anahtarlamalı bir hibrit denetleyici yapısı önerilmiştir. Önerilen hibrit denetleyici, Yapay Arı Kolonisi Algoritması kullanılarak optimize edilen PID denetleyiciyle ve Ziegler-Nichols yöntemine dayalı farklı denetleyicilerden elde edilen sonuçlarla karşılaştırılmıştır. Karşılaştırma kriterleri maksimum aşım miktarı, yükselme zamanı ve oturma zamanı olarak belirlenmiştir. Karşılaştırmanın sonuçları da çok kriterli karar verme tekniklerinden biri olan TOPSIS metodu ile analiz edilerek değerlendirilmiş ve sunulmuştur.

Design and Robustness Analysis of Multiple Extended State Observer Based Controller (MESOBC) for AVR of the Power System

Automatic voltage regulator (AVR) is installed on the synchronous generators in the power system and plays a very important role in maintaining the generator output voltage besides changes in load demand, parametric uncertainties, and operating temperature. As the load is continuously varying in the system, the AVR needs controllers to track and regulate the voltage of the synchronous generator much faster. This paper shows an initial attempt to design a robust multiple extended state observer (MESO) to estimate the variation in lump disturbances (i.e., load demand and parametric uncertainties) from all the components of the AVR. MESO-based controller (MESOBC) can track such matching and mismatching of both types of irregularities and regulate the terminal voltage of the generator accordingly. MESOBC performance is matched with strong published AVR designs for a standard condition, ±30% load voltage variation and for simultaneous changes in AVR parameters with ±30% load voltage variations. Integrated square error (ISE) is chosen as an objective function to compare the output of MESOBC with other published AVR designs in view of graphical AVR responses and by calculating various numerical values for AVR responses. At last, the robustness of MESOBC is also checked through sensitivity analysis, and it is seen that MESOBC guaranteed robust performance for the AVR of the power system under diverse operating conditions.

Comparative Study of AVR Control Systems Considering a Novel Optimized PID-Based Model Reference Fractional Adaptive Controller

Voltage regulation is a crucial task for electrical grids in the presence of high penetration levels of renewable energies. The regulation of generator excitation improves the stability of the power system. An essential tool for controlling the excitation of generators is the automatic voltage regulator (AVR). It is advised to use a controller to increase the reliability of an AVR. A survey about different types of controllers is proposed in this paper. Then, a novel optimized PID-Based model reference fractional adaptive controller is proposed, with detailed mathematical modeling. The novel controller was compared to the controllers in the survey. The novel proposed controller proved its superiority over the other controllers through its fast response and low rising and settling times. Moreover, the proposed controller smoothly and instantaneously tracked dynamic reference changes.

Optimized PIDD2 controller for AVR systems regarding robustness

The novel method for tuning proportional-integral-derivative controller with second order derivative term (PIDD2) for the automatic voltage regulator (AVR) of synchronous generator is presented. The design method minimizes load disturbance response regarding constraints on sensitivity functions: maximum sensitivity Ms, maximum complementary sensitivity Mp and measurement noise sensitivity Mn. Simple solution is obtained by shifting PIDD2 controller in a new parameter space and by employing an iterative procedure. In each iteration the five controller parameters are obtained by solving the constrained optimization problem concerning sensitivities Ms and Mn for the fixed value of controller zeros damping factor ξ. The robustness index Mp is calculated subsequently. In that manner, maximum of complementary sensitivity Mp is met by means of auxiliary parameter ξ. The performance improvements are achieved in comparison with traditional PID controller, while robustness is retained. Further, the comparison is made with an optimization method using amplitude optimum principle that also minimizes load disturbance response with different optimality criterion. Experiments are carried out on a small lab synchronous generator setup in order to demonstrate practical potential in real noisy environment of the proposed method and to justify the increased order of AVR controller.

Intelligent Coordinated Control of PID-SMES and AVR based on Hybrid PSO-DE for Small Signal Stability Enhancement

Dynamic disturbances in the electric power system occur due to changes in the load that can change important parameter values, this results in loss of synchronization in multi-machine power systems, so a controller in the power system is needed to maintain a stable condition during dynamic disturbances. In this final project, a Proportional Integral Differential (PID)-Superconducting Magnetic Energy Storage (SMES) controller is useful for supplying or absorbing active power when there is a load change so that the frequency can be maintained continuously, and an Automatic Voltage Regulator (AVR) is in charge of regulating the voltage on the system. The PID controller in SMES is useful for setting the output parameters of SMES. Hybrid Differential Evolution - Particle Swarm Optimization (DE-PSO) optimization method is used to optimize the oscillation damping process. The results indicate that the use of PID SMES and AVR optimized using the DE-PSO hybrid algorithm has a better response. In the Suralaya generator unit, the overshoot is -0.0001395 pu, and the settling time is 12.4 seconds by using the optimal controller. Meanwhile, when it is not using the additional controller, the overshoot is -0.0004228 pu, and the settling time is more than 16 seconds.

Performance Analysis of Diverse Energy Storage on Combined ALFC and AVR Control of Multiarea Multiunit System with AC/HVDC interconnection

This paper discusses the significance of various energy storage devices like redox flow battery (RFB), capacitive energy storage (CES), superconducting magnetic energy storage (SMES), and flywheel energy storage system (FESS) impact on the combined control of automatic load frequency control (ALFC) and automatic voltage regulator (AVR) of three areas interconnected power systems having thermal, hydro, gas, and geothermal plants in presence of HVDC link. A novel PD with filter coefficient (PDN) controller cascade with fractional-order PID with filter coefficient (FOPIDN), CPDN-FOPIDN is proposed as a secondary controller for combined ALFC-AVR loop. An artificial flora algorithm is utilized to obtain the various controller parameters under numerous system conditions. The proposed CPDN-FOPIDN controller provides less settling time, overshoots, undershoots, and reduces oscillation compare to the FOPIDN controller. The study also reveals that the RFB provides better system performance than SMES, CES, and FESS. Integration of HVDC link improves the system dynamic response. Furthermore, the sturdiness of the proposed CPDN-FOPIDN controller is tested against the changes in system loading conditions via sensitivity analysis.

Implementation of a Photovoltaic Inverter with Modified Automatic Voltage Regulator Control Designed to Mitigate Momentary Voltage Dip

The main objective of this research is to propose an active and reactive power injection control in order to mitigate voltage sags. The proposed control strategy works in conjunction with a modified version of an automatic voltage regulator (AVR), where it will act on the active and reactive powers injected by the inverter to reduce the effects of voltage sags. In this way, the control will avoid possible shutdowns and damage to the equipment connected to the grid. The voltage improvement can be perceived for consumers connected to the power system. Modifications in AVR model and parameters are performed to speed up its performance, thus identifying the short-duration voltage variations (SDVV) and, consequently, the control acts to alter the powers, decreasing the active power injection and increasing the reactive power based on inverter capacity during the momentary voltage dip (MVD). Finally, when the fault is cleared, all values return to the pre-fault condition, so that the inverter only operates with active power. A 75 kW three-phase grid-connected photovoltaic system (GCPVS) equipped with the proposed control was inserted in a distribution grid of the city of Palmas, state of Tocantins, Brazil, and all of the computer simulations were performed on the Matlab/Simulink®.

Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems

This study deals with the controlling the speed of a direct current (DC) motor via a fractional order proportional–integral–derivative (FOPID) controller and maintaining the terminal voltage level of an automatic voltage regulator (AVR) via a proportional–integral–derivative plus second order derivative (PIDD2) controller. To adjust the parameters of those controllers, a novel improved slime mould algorithm (ISMA) is proposed. The latter is a novel metaheuristic algorithm developed in this work. The proposed algorithm aims to improve the original SMA in terms of exploration with the aid of a modified opposition-based learning scheme and in terms of exploitation with the aid of the Nelder–Mead simplex search method. A time domain objective function, which includes time response specifications of steady state error and maximum overshoot along with rise and settling times, is used as a performance index to design the FOPID controller-based DC motor system and PIDD2 controller-based AVR system. The performance of the proposed novel approaches for both systems are assessed through time and frequency domain simulations along with statistical tests which show the greater performance of the improved algorithm. Further to this, the efficacy of the proposed approaches for both systems is compared with other available and effective approaches in the literature. The extensive comparative results demonstrate the proposed method to be superior to those state-of-the-art approaches for both DC motor speed and AVR control systems.

Voltage stability assessment of isolated hybrid dish-stirling solar thermal-diesel microgrid with STATCOM using mine blast algorithm

This paper presents the voltage control of an isolated hybrid diesel-dish-Stirling solar thermal system (DSP) based power system. As DSP is employed with an induction generator (IG), it needs reactive power for magnetic field. Though synchronous generator (SG) is coupled with the diesel generator, SG alone unable to supply sufficient reactive power to cater the reactive power requirement of the consumers load and the IG. Under such circumstances, static synchronous compensator (STATCOM) is used to meet the reactive power demand. The parameters of the controllers employed with the STATCOM as well as automatic voltage regulator (AVR) of the SG are tuned simultaneously applying recently developed mine blast algorithm (MBA). Performance of the MBA based controllers are compared with that of the cuckoo search algorithm (CS), and particle swarm optimization (PSO) based counterpart on the proposed model. Application of STATCOM and MBA based control strategy in diesel-dish-Stirling solar thermal system-based hybrid system for reactive power regulation is a maiden attempt. Extensive simulations of the model for dynamic responses of voltage deviations and reactive deviations under several uncertain conditions, such as step disturbance in reactive power load of the consumers and IG without/ with STATCOM, realistic variations of power output of DSP and reactive load have been carried out. Results analyses indicate that MBA based control strategy is the best amongst all the control strategies attempted here in the terms of maximum overshoot and the settling time. Further, meager values of the maximum overshoot and the settling time under several uncertain conditions justify the coordinated control of AVR and STATCOM to maintain the voltage stability of the isolated hybrid system.

Tuning of Novel Fractional Order Fuzzy PID Controller for Automatic Voltage Regulator using Grasshopper Optimization Algorithm

One of the most important equipment in the power system is the Automatic Voltage Regulator (AVR) or synchronous generator excitation. The goal of the system is to maintain the terminal voltage of the synchronous generator in the desired level. AVR is inherently uncertain. Hence, the proposed controller should be able to handle the problem. In this paper, Fractional Order Fuzzy PID (FOFPID) controller has been employed to control the system. In order to enhance the performance of the controller, Grasshopper Optimization Algorithm (GOA) is used to tune the parameters of the controller. Unlike other methods, the gains of FOFPID controller are not constant and alter in different operating conditions. The robustness of the controller has been investigated and the comparative results show that the proposed controller has a better performance against other methods.Automatic Voltage Regulator (AVR), Synchronous generator excitation, Fractional-order fuzzy PID (FOFPID) controller, Grasshopper Optimization Algorithm (GOA), Uncertainty

Heuristic optimization based dynamic weighted state feedback approach for 2DOF PI-controller in automatic voltage regulator

The intelligent, robust and reliable control of Automatic Voltage Regulator is essential to maintain a constant voltage level of synchronous generator working under different operating conditions. The heuristic optimization based 2DOF state-feedback PI-controller which regulates voltage output of synchronous generators markedly towards severe and continuous disturbances by using amplifier output as an additional feedback is a recent and powerful AVR strategy. In this study, to provide elasticity of dynamic response of this AVR scheme against relatively severe and continuous disturbances, its state-feedbacks are dynamically weighted by the flexible coefficients. Indeed, when the curves of the weight coefficients versus step disturbance are investigated, it is observed that while the disturbance increases, the weight coefficients also rise the effect of amplifier feedback automatically in order to regulate the voltage output of the AVR. The novel dynamic weighting approach increases the system performance between 9.48% and 19.65% for different working conditions. After robustness and stability analyses, a suggestion for real implementation scheme is presented and interpreted.

Slime Mold Algorithm Based Hybridized Artificial Neural Network Model for Efficient Automatic Voltage Regulation Control

Slime Mold Algorithm Based Hybridized Artificial Neural Network Model for Efficient Automatic Voltage Regulation Control

Compatible Decentralized Control of AVR and PSS for Improving Power System Stability

Automatic voltage regulator (AVR) and power system stabilizer (PSS) as the most common excitation controllers have implemented incompatible decentralized control (IDC) due to the asynchronous sampling by the voltage/current transformer. However, IDC results in the incompatibility of decentralized AVR and PSS in regulating generator dynamics, which seriously reduces the capability of AVR and PSS in improving the power system stability. In this article, the concept of compatible decentralized control (CDC) based on synchronous local measurements is first proposed for the decentralized AVR and PSS to improve the power system stability. The mathematical models on IDC and CDC are, respectively, modeled to represent the compatible characteristics of CDC. The distinguishing feature of the proposed CDC is that the decentralized AVR and PSS can be compatible with one another in regulating generator dynamics. Simulation results on four IEEE benchmark systems show the advantages of CDC in improving power system stability compared with IDC.

Evolutionary algorithms based tuning of PID controller for an AVR system

In this paper, an evolutionary algorithm based optimization algorithm is proposed with new objective function to design a PID controller for the automatic voltage regulator (AVR) system. The new objective function is proposed to improve the transient response of the AVR control system and to obtain the optimal values of controller gain. In this paper, particle swarm optimization (PSO) and cuckoo search (CS) algorithms are proposed to tune the parameters of a PID controller for the control of AVR system. Simulation results are capable and illustrate the effectiveness of the proposed method. Numerical and simulation results based on the proposed tuning approach on PID control of an AVR system for servo and regulatory control show the excellent performance of PSO and CS optimization algorithms.