Automatic Voltage Regulator System Research Articles

Improve the performance of automatic voltage regulator for power system using self-tuning fuzzy-PID controller

The optimal design of the automatic voltage regulators for a synchronous machine are positively reflected on the quality of voltage stability. This paper is concerned with the design of an AVR by adopting three control techniques. The first one was designed according to the traditional proportional integration-derived (PID) controller while the fuzzy logic was adopted in design the second powerful controller, finally the fuzzy PID controller for an automatic voltage regulator (AVR) based on fuzzy logic technology, selftuning fuzzy proportional integration-derived (STFPID) have been designed to tuning the gains of the PID controller (KP, KI and KD). To confirm the efficiency of the proposed control systems, a simulation was carried out, and the results showed that the designed STFPID controller achieves the best performance of the AVR system, and gives the preferable tracking low rise time, lower overshoot, least stetting time, minimal steady state error, and gives the ideal response against PID and fuzzy logic technology.

Intelligent fuzzy-based automatic voltage regulator with hybrid optimization learning method

This work focuses on enhancing the performance of an Automatic Voltage Regulator (AVR) by providing a good transient response, adaptability to changing circumstances, and robustness. Its objective is centered on utilizing the Adaptive Neuro-Fuzzy Inference System (ANFIS) to control the AVR system. The study is important because it compares the performance of the system without a controller, with the PID controller and the proposed ANFIS. This work shows a novel application of ANFIS with a hybrid learning algorithm for the AVR system. The ANFIS was designed by using the hybrid optimization learning scheme to train the Fuzzy Inference System (FIS) that is used to control the parameters of the AVR system. To generate the right dataset used for training the fuzzy inferential system, the Proportional-Integral-Derivative (PID) simulation of the entire system connected to the AVR is used setting the simulation time to about ten seconds. Simulation of the work was done in MATLAB/Simulink and enhanced performance objectives (rise time of 1.1994s, settling time of 1.8818, overshoot of 1.3206, and steady-state error of 4.269e-04) were compared to other related works.

ADAPTIVE AUTOMATIC VOLTAGE REGULATION IN THE ELECTRICAL GRID USING SINGLE-PHASE LINEAR VOLTAGE REGULATORS

Ensuring the required voltage level in rural electric grids is a necessary condition for the efficient operation of agricultural enterprises and comfort in rural life. The overstated length of rural power transmission lines leads to excessive voltage deviations at consumer inputs. The existing methods and technical means of voltage regulation do not in all cases allow to provide the necessary level of voltage in the grid. (Research purpose) The research purpose is developing a method and device for phase-by-phase automatic voltage regulation in the electrical grid using linear voltage regulators, to illustrate the possibilities of its application. (Materials and methods) Used general scientific research methods, methods: literary review, theory of automatic control, electrical engineering. We analyzed the literary sources. We have studied the methods and technical means of voltage regulation in electrical grid. (Results and discussion) A new method and device for adaptive automatic voltage regulation in the rural electrical grid with the use of a separate phase-by-phase installation of linear voltage regulators have been proposed. We considered an example of the implementation of the method in a rural electrical grid with an uneven load in phases. (Conclusions) It was revealed during the review of voltage regulation methods that adaptive automatic control methods are promising, involving control of voltage deviation at consumer inputs and determination of the regulation coefficient based on this. It was determined that the use of the proposed method and device provides a normalized voltage value at consumer inputs by means of adaptive automatic phase-by-phase voltage regulation in the electrical grid with separately phase-by-phase linear regulators controlled by an adaptive automatic voltage regulation system that generates control commands based on data processing from voltage sensors installed at control points of the grid, including at consumer inputs.

Design and Robust Performance Analysis of Low-Order Approximation of Fractional PID Controller Based on an IABC Algorithm for an Automatic Voltage Regulator System

In this paper, a low-order approximation (LOA) of fractional order PID (FOPID) for an automatic voltage regulator (AVR) based on the modified artificial bee colony (ABC) is proposed. The improved artificial bee colony (IABC) high-order approximation (HOA)-based fractional order PID (IABC/HOA-FOPID) controller, which is distinguished by a significant order approximation and by an integer order transfer function, requires the use of a large number of parameters. To improve the AVR system’s performance in terms of transient and frequency response analysis, the memory capacity of the IABC/HOA-FOPID controller was lowered so that it could fit better in the corrective loop. The new robust controller is named the improved artificial bee colony (IABC) low-order approximation (LOA)-based fractional order PID (IABC/LOA-FOPID). The performance of the proposed IABC/LOA-FOPID controller was compared not only to the original ABC algorithm-tuned PID controller, but also to other controllers tuned by state-of-the-art meta-heuristic algorithms such as the improved whale optimization algorithm (IWOA), particle swarm optimization (PSO), cuckoo search (CS), many optimizing liaisons (MOL), genetic algorithm (GA), local unimodal sampling (LUS), and the tree seed algorithm (TSA). Step response, root locus, frequency response, robustness test, and disturbance rejection abilities are all compared. The simulation results and comparisons with the proposed IABC/LOA-FOPID controller and other existing controllers clearly show that the proposed IABC/LOA-FOPID controller outperforms the optimal PID controllers found by other algorithms in all the aforementioned performance tests.

Seamless Transition and Fault-Ride-Through by Using a Fuzzy EO PID Controller in AVR System

One of the most crucial control aspects in electric power networks is ensuring constant voltage levels throughout different circumstances. To overcome this problem, an automatic voltage regulator (AVR) is installed in the electrical power networks to preserve the voltage at its allowable range. In this paper, a fuzzy-based PID controller was used to enhance the AVR dynamic performance under several operating conditions. Moreover, an Equilibrium Optimizer (EO) algorithm was used to initialize the controller gains. The validation of the proposed controller was proven through three different systems. The first was a simple AVR system under fixed and dynamic references. The proposed fuzzy EO PID controller proved its superiority in this case through the reduction of voltage overshoot by around 3–28% compared with the reported methods in the literature. Then, the fault-ride through capability of the proposed controller was proven through the second system, which was the Kundur two-area system suffering from a 3-phase fault condition, where the overshoot with the proposed controller was reduced by 4–7% compared with the default controller and modern weighted method reported in the literature. Lastly, an IEEE 9-bus system performance was tested with the proposed controller under normal, faulty, and dynamic loading conditions. Again, the proposed controller succeeded in reducing the maximum overshoot by around 5% compared with the default controller in the system. Moreover, the proposed controller achieved a seamless transition between the islanding and grid-connected mode of operation.

A Particle Swarm Optimization Technique Tuned TID Controller for Frequency and Voltage Regulation with Penetration of Electric Vehicles and Distributed Generations

An interconnected power system requires specific restrictions to be maintained for frequency, tie-line power, and the terminal voltage of synchronized generators to avoid instability. Therefore, frequency stability and voltage regulation issues are covered individually and jointly in the current research work. Initially in test system 1, automatic generation control (AGC) investigations are done on two interconnected systems with thermal plants and electric vehicles in one area and distributed generation and electric vehicles in other area. The automatic voltage regulator (AVR) problem alone is chosen for investigation in test system 2. The third test system addresses the combined AGC and AVR issues. The performance of the fractional-order tilt-integral-derivative (TID) controller is compared with that of a widely used proportional integral derivative (PID) controller in all three test systems studies. The findings demonstrate better performance of the TID controller than PID in terms of providing superior dynamic metrics, such as low peak overshoots, undershoots, and settling time, as well as decreased oscillations amplitudes. Additionally, TID performs better than PID despite randomized load disturbance, system non-linearities, and time delays in AGC and the combined AGC and AVR problem. The PSO-tuned TID controller is insensitive to variation in load damping factor and time constants of the AVR system. Finally, the results are validated by an OPAL-RT 4510 real-time digital simulator.

Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm

Voltage regulation in automatic voltage regulator (AVR) system has been one of the most challenging engineering problem due to the uncertain load condition. Therefore, the control of AVR system by using PID based controller is one of the essential approach to maintain the performance of the AVR system. Subsequently, the application of FOPID controller in AVR system is gaining more attention recently. This is because the FOPID has additional control parameters at the derivative and integral parts than the PID controller, which has the advantage to improve the output response of AVR system while retaining the robustness and simple construction as the PID controller. Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. Moreover, the proposed MSFA based method also can solve the unstable convergence issue in the original smoothed function algorithm (SFA), thus able to provide better convergence accuracy. The simulations of step response analysis, Bode plot analysis, trajectory tracking analysis, disturbance rejection analysis, and parameter variation analysis are conducted to evaluate the effectiveness of the proposed MSFA-FOPID controller of AVR system. Consequently, the results obtained from the simulations revealed that the proposed method is highly effective and significantly improved as compared to the other existing FOPID controllers.

Optimal Control of Automatic Voltage Regulator System with Coronavirus Herd Immunity Optimizer Algorithm-Based PID plus Second Order Derivative Controller

Optimal control of the Automatic Voltage Regulator (AVR) system can improve the system behavior with the optimal parameters obtained based on optimization. The design of proposed Proportional Integral Derivative (PID) and Proportional Integral Derivative Plus Second Order Derivative (PIDD2) controllers are stated as an optimization problem including objective and constraint. The optimization problem is solved by using Coronavirus herd immunity optimizer (CHIO) algorithm to find the best controller parameters. In this paper, optimal design of PID and PIDD2 controllers for AVR system are presented with different objectives. The optimal design of controllers modeled as an optimization problem is solved with the help of the CHIO Algorithm. CHIO is inspired herd immunity against COVID-19 disease by social distancing. The performances of CHIO-based controllers in AVR system are compared with some well-known algorithms. Also, the obtained results demonstrate that the CHIO algorithm yields the least objective value in comparison with the other algorithms. When the results of the proposed approach are compared to those of some modern heuristic optimization algorithms, such as the Particle Swarm Optimization (PSO) algorithm, Differential Evolution (DE) algorithm, Artificial Bee Colony (ABC) algorithm etc. and the superiority of the proposed approach is demonstrated.

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.

The LQR Based On Optimized Tuning PD Controller For AVR System

This study presents a Linear Quadratic Regulator (LQR) based on an optimizing PD controller to improve the dynamic performance of an automatic voltage regulation (AVR) system. Biogeography-based optimization (BBO) is used to adjust the controller gains, and the Mean Absolute Percentage Error (MAPE) cost function is used to ensure effective performance. To demonstrate the advantages of the suggested controller, a transient study was conducted and compared to a standard PD, LQR, and then used PD-LQR in terms of (Rising time, Settling time, Max Overshoot, and Peak time). Finally, simulations demonstrated that the PD-LQR gives satisfactory outcomes and a quicker reaction, which was evidently represented in the recommended controller's strong and steady performance in enhancing the transient analysis of the AVR system.

Cooperation search algorithm for tuning automatic voltage regulator system

<p>The cooperation search algorithm (CSA) duplicates teamwork in every part of the company. This paper presents an approach to setting automatic voltage regulator (AVR) with proportional-integral-derivative (PID) control based on CSA. To get the performance of the proposed method, this paper uses the maximum overshoot, rise time, settling time, and error. This paper uses the whale optimization algorithm (WOA), grasshopper optimization algorithm (GOA), particle swarm optimization (PSO), and sine-cosine algorithm (SCA) methods as a comparison in measuring the performance of the CSA method which is used as the optimization of PID parameters on the AVR. From the simulation, the application of the CSA method to get the optimal PID parameter value has an average result that can reduce the maximum overshoot by 10.97% compared to the GOA, PSO and SCA methods.</p>

Rao algorithm based optimal Multi‐term FOPID controller for automatic voltage regulator system

AbstractThis article presents a novel application of an optimal Multi‐term Fractional‐Order PID (MFOPID) controller for improving the performance of the automatic voltage regulator (AVR) system. A recently developed Rao algorithm has been used to optimize the proposed Multi‐term FOPID controller. The effectiveness of the Rao algorithm tuned Multi‐term FOPID controller for the AVR system has been proved by performing transient response, robustness, and performance analyses. Statistical analysis of the proposed Multi‐term FOPID controlled AVR system has been carried out to explore the most effective performance index among ITAE, ITSE, ISE, and IAE. The external disturbance rejection capability of the Rao algorithm‐tuned MFOPID controller has been examined by injecting external disturbances into the AVR system of different capacities at different times. The superiority of the proposed Multi‐term FOPID controller is validated by comparing the simulation results with recently employed various PID, PID‐Acceleration (PIDA), and FOPID controllers tuned by different metaheuristic algorithms. In addition, the behavior of the proposed Multi‐term FOPID controller has been examined in a real synchronous generator that is connected to a 10,000 MVA, 230 kV electric power network via a 210 MVA transformer using a MATLAB/Simulink environment. From the various simulation results, it has been concluded that the proposed Rao algorithm tuned optimal and robust Multi‐term FOPID controller has significantly improved the performance, robustness and stability of the AVR system.

Improved Whale Optimization Algorithm for Transient Response, Robustness, and Stability Enhancement of an Automatic Voltage Regulator System

The proportional integral derivative (PID) controller is one of the most robust and simplest configuration controllers used for industrial applications. However, its performance purely depends on the tuning of its proportional (KP), integral (KI) and derivative (KD) gains. Therefore, a proper combination of these gains is primarily required to achieve an optimal performance of the PID controllers. The conventional methods of PID tuning such as Cohen-Coon (CC) and Ziegler–Nichols (ZN) generate unwanted overshoots and long-lasting oscillations in the system. Owing to the mentioned problems, this paper attempts to achieve an optimized combination of PID controller gains by exploiting the intelligence of the whale optimization algorithm (WOA) and one of its recently introduced modified versions called improved whale optimization algorithm (IWOA) in an automatic voltage regulator (AVR) system. The stability of the IWOA-AVR system was studied by assessing its root-locus, bode maps, and pole/zero plots. The performance superiority of the presented IWOA-AVR design over eight of the recently explored AI-based approaches was validated through a comprehensive comparative analysis based on the most important transient response and stability metrics. Finally, to assess the robustness of the optimized AVR system, robustness analysis was conducted by analyzing the system response during the variation in the time constants of the generator, exciter, and amplifier from −50% to 50% range. The results of the study prove the superiority of the proposed IWOA-based AVR system in terms of transient response and stability metrics.

Robust Fuzzy Control for Uncertain Nonlinear Power Systems

This paper presents a new control technique based on uncertain fuzzy models for handling uncertainties in nonlinear dynamic systems. This approach is applied for the stabilization of a multimachine power system subject to disturbances. In this case, a state-feedback controller based on parallel distributed compensation (PDC) is applied for the stabilization of the fuzzy system, where the design of control laws is based on the Lyapunov function method and the stability conditions are solved using a linear matrix inequalities (LMI)-based framework. Due to the high number of system nonlinearities, two steps are followed to reduce the number of fuzzy rules. Firstly, the power network is subdivided into sub-systems using Thevenin’s theorem. Actually, each sub-system corresponds to a generator which is in series with the Thevenin equivalent as seen from this generator. This means that the number of sub-systems is equal to the number of system generators. Secondly, the significances of the nonlinearities of the sub-systems are ranked based on their limits and range of variation. Then, nonlinearities with non-significant variations are assumed to be uncertainties. The proposed strategy is tested on the Western systems coordinating council (WSCC) integrated with a wind turbine. The disturbances are assumed to be sudden variations in wind power output. The effectiveness of the suggested fuzzy controller is compared with conventional regulators, such as an automatic voltage regulator (AVR) and power system stabilizers (PSS).

Optimizing the PID Controller by Using the Genetic Algorithm

This paper aims to develop a Proportional Integral Derivative (PID) controller for the Automatic Voltage Regulator (AVR) of the Synchronous Generator, Automatic Voltage Regulator is responsible for keeping the output voltage of the Generator constant and stable. The Automatic Voltage Regulator system can be represented by a fourth order Transfer Function. The parameters of the controller are evaluated by using the Genetic Algorithm tuning method, for this method the Genetic Algorithm Optimization toolbox in MATLAB is used. A PID controller and a PID Filter controller are developed in order to come up with the optimum controller design for the system. The performance of the Genetic Algorithm based controller has been compared with the classical Ziegler-Nichols based controller. The results show that the Genetic Algorithm based controller outperforms the Ziegler-Nichols based controller, the optimum controller design is achieved by the GA based PID filter controller.

Improved Lévy flight distribution algorithm with FDB-based guiding mechanism for AVR system optimal design

This paper presents the improved version of the Lévy Flight Distribution (LFD) algorithm for solving real-valued numerical optimization problems. In the proposed algorithm, the Fitness-Distance Balance (FDB) selection method was used to determine the search agents that well know the migration routes and guide the herd. Thus, the FDB-LFD algorithm, which has a much stronger search performance, was developed. The performance of the proposed algorithm was tested and verified on CEC17 and CEC20 benchmark problems for low-, middle- and high-dimensional search spaces. Results of the FDB-LFD was compared to the performance of 11 other powerful and up-to-date metaheuristic search algorithms. According to Friedman statistical test results, the proposed FDB-LFD algorithm ranked first, whereas the LFD was ranked eleventh. This result demonstrated that the changes in the design of the LFD algorithm had been successful. Moreover, using the proposed algorithm, optimum solutions were found for one of the popular industrial engineering applications: the automatic voltage regulator (AVR) system design. The simulation results revealed that the FDB-LFD is an effective algorithm for solving both unconstrained benchmark and constrained industrial engineering design problems.

Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase the robustness of the AVR. Fuzzy PID controller parameters are determined by a genetic algorithm (GA)-based optimization method using a novel multi-objective function. The multi-objective function, which is important for tuning the controller parameters, obtains the optimal solution using the Integrated Time multiplied Absolute Error (ITAE) criterion and the peak value of the output response. The proposed method is tested on two AVR models with different parameters and compared with studies in the literature. It is observed that the proposed method improves the AVR transient response properties and is also robust to parameter changes.

An improved RUN optimizer based real PID plus second-order derivative controller design as a novel method to enhance transient response and robustness of an automatic voltage regulator

It is crucial to maintain the terminal voltage of a power network in order to reach a desired power quality. In this regard, a system called automatic voltage regulator (AVR) holds a significant role as it allows the adjustment of the terminal voltage. However, an AVR system requires an efficient control technique in order to provide stability. Considering this requirement, a new method is presented in this paper for transient response enhancement and robustness of the automatic voltage regulator (AVR) system. In that sense, the structure of a recently developed metaheuristic algorithm named Runge Kutta optimizer (RUN) is improved. The improved RUN (iRUN) optimizer is obtained by integrating the pattern search (PS) method into the original form of the RUN optimizer. The constructed iRUN optimizer is proposed as an efficient tool to tune a real proportional-integral-derivative (PID) plus second-order derivative (PIDD2) controller employed in an AVR system. In the proposed control mechanism, a performance index known as ZLG is used as an objective function. The proposed iRUN optimizer based real PIDD2 controller is comparatively demonstrated to be superior in terms of transient response and robustness against other available and recently reported methods based on PID, PID with filter (PID-F), PID acceleration (PIDA), fractional order PID (FOPID) and PID plus second-order derivative (PIDD2) controllers that are respectively tuned with metaheuristic optimizers of stochastic fractal search algorithm, Archimedes optimization algorithm, whale optimization algorithm, Henry gas solubility optimization and particle swarm optimization. The proposed method is shown to achieve no overshot and less rise and settling times compared to listed methods. It is also shown to be sufficiently robust in case of potential variations that may occur in the parameters of the system. The superiority is further demonstrated using thirty good performing and recently reported different methods that adopt different controllers and metaheuristic optimizers, as well. All comparative analyses confirm the excellent capability of the proposed iRUN optimizer based real PIDD2 controller for the AVR system control.

Optimised implementation of AVR system using particle swarm optimisation

Several techniques have been developed to improve the control quality and deliver optimised products in many industrial process domains. This work aims to propose an optimised automatic voltage regulator (AVR) system implementation by applying a nature-inspired algorithm called particle swarm optimisation (PSO) to design a proportional integral derivative (PID) controller for the AVR system. The proposed system consists of two controllers to deal with both the transient state and the time response. Different parallelisation and optimisation techniques such as loop unrolling, loop pipelining, dataflow, and loop flattening were adopted and applied to investigate the opportunities of creating a much more effective design. The proposed system achieves better results for the settling time and the overshoot which makes the proposed system a suitable choice for zero overshoot industry applications.

A Novel Fast Optimized Sliding Mode Controller for Automatic Voltage Regulator System

A Novel Fast Optimized Sliding Mode Controller for Automatic Voltage Regulator System