Performance Of Dynamic Voltage Restorer Research Articles

FRT capability improvement of a wind power system using support vector regression and deep neural network models

ABSTRACT The increasing energy demand and environmental conditions have led many countries to favor renewable energy,such as wind and solar,over conventional power plants. As per the Central Electricity Authority (CEA), India’s wind power capacity has grown substantially, reaching 45,154 MW in 2023, from 22,465 MW in 2013. However, integrating wind generators to an existing power system network can reduce transient stability during faults. To prevent wind turbine disconnection during faults, Indian grid code authorities mandate Fault Ride Through (FRT) or Low Voltage Ride Through (LVRT) capability for wind turbines. This paper proposes Dynamic Voltage Restorer (DVR) for enhancing the FRT capability of a constant speed wind turbine. Analysis and simulation are done on a fixed speed wind turbine employing Squirrel Cage Induction Generator (SCIG) under balanced and unbalanced voltage sags. Performance of DVR with two Artificial Intelligence-based controllers, Support Vector Machines(SVM) Regression Model Based Supervised Machine Learning algorithm, and Deep Neural Network (DNN) controller, is analysed and compared. The SVM Regression algorithm, achieves 100% voltage sag compensation under unbalanced voltage sags, reduces torque pulsations to 25% and maintains rotor speed at rated values, enabling the turbine to remain connected to the grid. Additionally it reduces Total Harmonic Distortion to 2%.

A Hybrid Fuzzy Predictive DVR Model for Voltage Estimation Using Intelligent Learning

A self-constructing intelligence-based learning law is proposed for the prediction of power quality mitigation through a dynamic voltage restorer (DVR). To tackle voltage-based power quality concerns in the distribution network, a fuzzy neural-based hybridization control approach using an evolving Takagi–Sugeno–Kang (e-TSK) and radial basis function (RBFN) is developed. The estimated value of fundamental weight components is achieved by the eTSK predictive model. The evaluated weight values are used to update the parameters for the generation of the reference load voltage components. The RBFN is used to achieve the desired task of dc and ac link voltage regulation. The self-tuned control algorithm is developed based on an intelligence technique that avoids the trapping of local optima, and early convergence, and reduces the voltage oscillation to obtain an optimal solution. A meta-heuristic optimization approach of grey wolf optimization (GWO) and grey wolf-cuckoo search (GWOCS) is selected to optimize the parameters of eTKS and RBFN to find the best-fitted predictive model under the dynamic state. The hybridization of the model with GWO and GWOCS is implemented for improving the training and generalization capability. The performance of VSC-based DVR is validated using the d-SPACE Micro lab box under the various power quality scenario.

Performance evaluation of dynamic voltage restorer using intelligent control algorithm

Power quality has become an important issue due to increasing applications of modern industrial and commercial sensitive equipment's. Due to high penetration of modern power electronics-based devices leads to voltage disturbances. To address the voltage disturbances the commonly employed series device called Dynamic Voltage Restorer (DVR) is used which requires an effective control technique. A control scheme namely Volterra adaptive expanded filter is developed which incorporate the higher ordered cost function. The conventional filters have like least mean square (LMS) algorithm is restricted to power error of second order. This restricts the computation of fundamental quantity from the disrupted signals and results in degradation under dynamical scenarios. The recommended approach surmount this aforesaid issue with a solution of a mixed learning of step size. This is derived from the error of second and fourth-order. The Volterra based LMS/Fourth (LMS/F) control has the merit of estimating the fundamental quantity under any power quality (PQ) scenario with less delay and low computational burden. The conventional controller like Proportional Integral (PI) has limited gain coefficients to achieve the optimized the voltage regulation. Furthermore, this is overcome by a Fractional Order PID (FOPID) with an additional coefficient of λ and γ obtain more stabilized DC and AC bus voltage by integrating with Kepler optimizer. For achieving optimal gain, an online tuning of FOPID is done with Kepler Optimizer. The Kepler is inspired by planet motion to achieve best gain values. The evaluation of FOPID is made by considering as a Fitness Function (FF) an Integral Time Square Error (ITSE). Owing to the superior performance of Kepler optimizer based FOPID under transitory state and an enhanced DVR performance is observed. The optimized FOPID has improved response in terms of less overshoot (2.9 %), undershoot (5.6 %), and fast settle time (0.104 s). To authenticate the simulating and experimental results dSPACE board is employed to validate the efficacy and accuracy of the proposed Volterra LMS/F technique.

Comparative Performance Study of DVR Using Adaptive LMS Filtering-Based Algorithms

In the distribution system, voltage sags and swell have adverse effects on sensitive and critical loads. Dynamic Voltage Restorer (DVR) play a vital role to mitigate voltage sags and swell through its organized control when connected in series with the system. Various conventional control schemes have been reported for the control of DVR. The performance of DVR with these schemes has been successful in the mitigation of voltage sags/swell, but drawbacks, such as undershoot, and overshoot during sag dynamics are observed in the regulated load terminal voltage. These drawbacks may cause malfunctioning of the equipment connected and hence their elimination is indispensable. With this inspiration, a novel Adaline filter-based adaptive control scheme using learning-rate parameter-based Least-Mean-Square algorithm has been proposed. This scheme has the capability to overcome the drawbacks with the conventional control schemes thus improving the performance of DVR. In this paper, the performance of DVR using proposed algorithm is compared with that using synchronous reference frame (SRF)-based conventional control scheme. The performance is studied and validated through simulation results under different voltage sag and swell conditions in MATLAB software using Sim Power System toolboxes.

Improved Control Method for Voltage Regulation and Harmonic Mitigation Using Dynamic Voltage Restorer

The increasing concerns of sensitive industrial customers and electrical utility corporationsregarding Power Quality (PQ) issues have driven the development of innovative solutions. This paperintroduces an enhanced control method based on Smooth Approximation Super Twisting Algorithm(SASTA) for the Dynamic Voltage Restorer (DVR) to achieve effective regulation of the critical load (CL)voltage to its nominal value while compensating for harmonics induced by the grid. The findings highlightthe significance of the improved control method in enhancing the DVR's performance for voltage regulationand harmonic distortion compensation. By implementing this control system, the DVR successfullymitigates deviations in voltage amplitude and reduces harmonic distortions in the CL voltage, therebyimproving power quality. To evaluate the performance of the proposed control method, extensivesimulations are conducted using the MATLAB/Simulink SimPower System toolbox. The resultsdemonstrate that the SAST-SMC for the DVR can accurately regulate the voltage in less than 2.3milliseconds (ms) and harmonics mitigation under 5% as per IEEE standards.

A fast switching strategy for DVR based on current control algorithm

Dynamic voltage restorer (DVR) needs to turn off the anti-parallel bypass thyristor (SCR) at the output terminal when dealing with voltage sag phenomenon. When applying traditional methods to force the thyristor off, it is essential to determine the direction of thyristor current according to the sensor sampling information, which has the risk of misjudgment under actual conditions. A novel fast switching strategy (FSS) for DVR is proposed in this paper. DVR-FSS uses the current control algorithm to force off the bypass SCR, which can realize the smooth transition from bypass state to compensation state. Firstly, the basic working principle of the DVR-FSS is introduced based on which the FSS operating modes are analyzed in detail. And the mathematical model of DVR-FSS in key modes is established to analyze the influence of FSS control algorithm parameters on the dynamic or steady performance of DVR. Secondly, the modeling and quantitative analysis of the fundamental voltage drop introduced by DVR in the steady-state mode are used to explain that the impact of FSS on the primary side load supply voltage is within the acceptable range. Finally, the correctness and feasibility of the proposed FSS are fully verified by experiments, which indicate that FSS has strong robustness at the same time.

Optimal Dynamic Voltage Restorer Using Water Cycle Optimization Algorithm

This paper proposes a low complexity control scheme for voltage control of a dynamic voltage restorer (DVR) in a three-phase system. The control scheme employs the fractional order, proportional-integral-derivative (FOPID) controller to improve on the DVR performance in order to enhance the power quality in terms of the response time, steady-state error and total harmonic distortion (THD). The result obtained was compared with fractional order, proportional-integral (FOPI), proportional-integral-derivative (PID) and proportional-integral (PI) controllers in order to show the effectiveness of the proposed DVR control scheme. A water cycle optimization algorithm (WCA) was utilized to find the optimal set for all the controller gains. They were used to solve four power quality issues; balanced voltage sag, balanced voltage swell, unbalanced voltage sag, and unbalanced voltage swell. It showed that one set of controller gain obtained from the WCA could solve all the power quality issues while the others in the literature needed an individual set of optimal gain for each power quality problem. To prove the concept, the proposed DVR algorithm was simulated in the MATLAB/Simulink software and the results revealed that the four optimal controllers can compensate for all the power quality problems. A comparative analysis of the results in various aspects of their dynamic response and %THD was discussed and analyzed. It was found that PID controller yields the most rapid performance in terms of average response time while FOPID controller yields the best performance in term of average % steady-state error. FOPI controller was found to provide the lowest THD percentage in the average %THD. FOPID did not differ much in average response from the PID and average %THD from FOPI; however, FOPID provided the most outstanding average steady-state error. According to the CBMA curve, the dynamic responses of all controllers fall in the acceptable power quality area. The total harmonic distortion (THD) of the compensated load voltage from all the controllers were within the 8% limit in accordance to the IEEE std. 519-2014.

Comparative Performance of DVR and STATCOM for Voltage Regulation in Radial Microgrid with High Penetration of RES

In recent years, the penetration of renewable energy sources (RES) in microgrids and distribution system feeders has increased manifold. Moreover, the advancement of power electronics-based devices in the distribution system has significantly increased the number of sensitive loads. Variations in the voltage under intermittent RES create functional problems with sensitive loads, necessitating voltage regulators (VR) installation. In this paper, two custom power devices: dynamic voltage restorer (DVR) and static synchronous compensator (STATCOM), used for voltage regulation in a microgrid, are investigated under different operating conditions. The efficacy of DVR and STATCOM for voltage regulation in an 11-node radial microgrid with high penetration of RES is simulated under a MATLAB Simulink environment. Furthermore, the simulated microgrid voltage profile results are analyzed to evaluate the efficacy of both voltage regulators.

Performance evaluation of GRNN and ANFIS controlled DVR using machine learning in distribution network

AbstractA machine learning based generalized neural network estimator (GRNNE) and Takagi‐Sugeno (T‐S) fuzzy control system is implemented to accelerate the functional performance indices of dynamic voltage restorer (DVR). The GRNNE predictive model is recommended for the fast estimation of the reference load voltage under the distorted power supply. The fruit fly optimization learning strategy is employed to optimize the weights and smoothing parameters for the extraction of the reference voltage signals as well as unit vectors, resulting in the required sinusoidal load component. The dynamics in the DC‐link voltage are optimized by the metaheuristic‐based gray wolf optimization algorithm. The coefficients of the adaptive controller are updated automatically to achieve the best fitted adaptive neuro‐fuzzy inference system predictive model with the least tracking voltage deviation error even in the presence of voltage disturbances. In comparison to classical techniques, the recommended neural‐based approach offers a faster convergence speed with fewer parameters to tune, shorter training time, and lower risks of local entrapment. The performance metrics such as mean square error, root mean square error, mean absolute error, mean absolute percent error, coefficients of correlational and determination (R and R2) are used to evaluate the efficacy of the proposed controller and hence enhance the DVR performance. Finally, the simulation results of the hybrid approach confirm that the NN‐based DVR estimator has proven its ability to alleviate voltage sensible issues at critical loads and outperform others in reducing power quality issues.

ANN-Based Reference Voltage Generation Scheme for Control of Dynamic Voltage Restorer

Dynamic voltage restorer (DVR) is usually employed to mitigate sag/swell in supply voltages so that load voltage is regulated at nominal value. This paper proposes artificial neural network (ANN) based reference voltage generation (RVG) scheme for the control of 3-phase DVR. ANN replaces the traditional control of DVR, which involves abc-dq0 and dq0-abc transformations, estimation of d-q axes voltage errors and proportional-integral (PI) controllers along with their tuning. In proposed control scheme, the feedforward ANN utilizes present and previous samples of supply voltage and peak magnitude of load voltage for RVG, which when impressed across the injection transformer results in sag/swell mitigation. It is important to note that the proposed scheme is free from transformations and controller tuning. The performance of 3-phase DVR with the proposed ANN based RVG scheme results in standard IEEE-519 compliant operation with load voltage regulated at nominal value even under sag/swell in supply voltage. This is verified through MATLAB/SIMULINK based simulaiton studies.

Online management and assessment of power quality issues through smart metering in smart grid architecture

With the growing Smart Grid concept, it has become very important to formulate and device the ways of intelligent control and supervision of electrical power distribution systems. As the distribution part is a major area among generation, transmission, and distribution, so without complete automation of the distribution system, a complete smart grid concept cannot be achieved. Therefore, a smart distribution system concept has been developed in this paper, where a vital role plays in the operation of smart meters having communication capabilities. This paper proposed two-level control architecture. MATLAB/SIMULINK model has been developed. The model studied consists of two low voltage (LV) distribution networks falling under one substation, thus two local controllers and one main controller have been modeled. To simulate the functionalities of controllers, different case scenarios such as overcurrent protection, power theft, no shutdown of essential loads (like hospitals, VIPs), available power loss, and phase unbalancing for 60 houses together in two areas have been studied and were compared with the real-time system through OPAL-RT. Performance of Dynamic Voltage Restorer (DVR) in case of voltage sag/swell and harmonics have been shown for enhancing power quality in distribution systems.

Novel MAF-Fuzzy Based IR-SRF Controller for DVR to Improve PQ Under Dynamic Weak Grid Conditions

This paper presents the development of advanced adaptive controller for dynamic voltage restorer (DVR) to regulate the power quality connected to a distribution system. Various voltage quality issues have been generated as distorted grid conditions are responsible for abnormal operation of the consumer electronics and domestic household appliances. Therefore dynamic voltage restorer (DVR) is employed for elimination of voltage quality issues in the distribution lines. To improve the performance and efficiency of DVR, an improved robust SRF (IR-SRF) controller has been developed in this paper for the mitigation of voltage quality issues under weak grid conditions. In the developed IR-SRF controller, moving average filter (MAF) has been utilized for better extraction of ripples from the sensed voltage. For better grid voltage signal synchronization with the proposed controller under highly dynamic condition, an enhanced Phase Locked Loop (PLL) scheme has been utilized instead of conventional PLL. For the regulation of DC link voltage under dynamic environmental conditions, MAF based fuzzy tuned PI controller has been utilized with the ability to adapt the situation. The developed controller has been simulated and results for various grid voltage conditions have been analyzed. The obtained simulation results are compared with conventional control algorithm to validate the efficacy. The efficiency of the proposed controller has been validated using the experimental results.

Performance Validation of PV System Incorporated ZSI-Dynamic Voltage Restorer for Long-Lasting Power Quality Improvement

Abstract A power distribution system’s main challenge is to provide consistent, reliable electricity to fulfill high demand. The incorporation of renewable energy sources into the utility grid system can be accomplished. However, renewable sources are intermittent in nature, and the loads work dynamically and cause imbalances to the system voltage within an immediate time frame. Intermittent renewable sources affect the voltage of the power grid system. Photovoltaic (PV) power generation with Z-source inverter (ZSI)–based dynamic voltage restorer (DVR) is used to avoid negative effects on the voltage. For step-up low direct current (dc) voltage to require alternating current voltage for the compensation of the voltage disturbance, ZSI with an energy storage impedance network is used. dc-dc converters connect the PV cell and the battery storage to the impedance source network. This article also incorporates an improved second-order generalized integrator (I-SOGI) control system for the generation of reference voltage signals. The I-SOGI control reference voltage generation approach greatly improves system performance and decreases the harmonic voltage. The voltage-related problems in the system connected to the utility grid are mitigated with DVR. In different load and source conditions, the PV generation with DVR performance is verified by the experimental prototype.

Comparative Analysis of PI controller, Fuzzy controller and Interval Type-2 Fuzzy based Performance of Dynamic Voltage Restorer for Compensation of Voltage Sag and Swell

In today’s scenario, the power quality issues like voltage sag and swell are major concerns in power systems. On the distribution, side to overcome this issue a custom power device DVR(Dynamic Voltage Restorer) is proven to be a more effective solution that is lower in cost, smaller in size, and offers a faster dynamic response for the protection of sensitive load. DVR is a series compensating device which operates as a voltage booster. The application of DVR is entitled to be a flawless compensating device for the compensation of voltage sag and swell. This paper presents the modeling and simulation using various controller topologies like PI controller based on synchronous reference frame algorithm, fuzzy controller, and interval type 2 fuzzy controller. The results are then verified using a Matlab-Simulink environment.

Reparation of voltage disturbance using PR controller-based DVR in Modern power systems

Abstract The Smart Grid environment gives more benefits for the consumers, whereas the power quality is one of the challenging factors in the smart grid environment. To protect the system equipment and increase the reliability, different filter technologies are used. Even though, consumers’ expectations towards the power quality are not fulfilled. To overcome these drawbacks and enhance the system reliability, a new Custom Power Devices (CPD) are introduced in the system. Among different CPDs, the Dynamic Voltage Restorer (DVR) is one of the voltage compensating devices that is used to improve the power quality during distortions. When the distortions such as voltage swell and sag occur in the distribution system, the control strategy in the DVR plays a significant role. In this article, the DVR performance using Proportional Integral (PI), Proportional Resonant (PR) controllers are analyzed. A robust optimization algorithm called Self Balanced Differential Evolution (SBDE) is used to find the optimal gain values of the controllers in order to reach the target of global minimum error and obtain fast response. Then, a comparative analysis is performed between different controllers and verified that the performance of PR controller is superior than the other controllers. It has been found that the proposed PR controller strategy reduces the Total Harmonic Distortion (THD) values for all types of faults. The proposed SBDE optimized DVR with PR controller reduces the THD value less than 4% under voltage distoration condition. The DVR topology is validated in MATLAB/SIMULINK in order to detect the disturbance and inject the voltage to compensate the load voltage.

Performance of DVR Using Optimized PI Controller Based Gradient Adaptive Variable Step LMS Control Algorithm

A custom power device known as dynamic voltage restorer (DVR) has been investigated to operate a distribution system at its desired performance. The distribution system with voltage-related power quality issues in the supply side has been addressed through this article using DVR. Four different grid disturbances, such as voltage sag, swell, unbalances, and distortions, have been taken into account while testing the DVR capability. DVR has been controlled using optimized proportional and integral (PI) gains integrated with gradient adaptive variable learning rate least mean square control algorithm. Adaptiveness of variable step-size in LMS makes the control robust in case of dynamics in the system, which assures better performance. Also, the other major contribution of this article is the implementation of optimization-based self-tuning PI gains in the proposed control. The evaluation of optimizer in estimating the PI gains is presented in terms of the response of dc-link voltage DVR. The simulation work of proposed control algorithms on DVR has been done and satisfactory results are found. For the experimental validation, d-SPACE made Micro Lab Box is used as control processor, and both dynamic and steady-state results are discussed for its effectiveness.

Comparative performance of dynamic voltage restorer using adaptive control algorithms with optimized error regulator gains

Comparative performance of dynamic voltage restorer using adaptive control algorithms with optimized error regulator gains

An Efficient Pseudo-Derivative-Feedback-Based Voltage Controller for DVR Under Distorted Grid Conditions

Grid integration of distributed energy resources has become a technical challenge in the distribution network operation due to the intermittent nature of renewable energy sources and their impact on grid voltage stability. Thus, a dynamic voltage restorer (DVR) is installed in the distribution network system to reduce such grid voltage impact on sensitive loads. In this article, a pseudo-derivative-feedback (PDF)-based voltage controller is implemented for the effective operation of DVR under voltage disturbances. Response of DVR primarily depends upon its controller action. This article addresses the issues in conventional P and PI multiloop controller with and without feedforward path then proposes PDF control strategy for DVR. Using the proposed controller, dynamic performance of DVR is improved. The efficacy of the proposed controller is illustrated by a comparative study with conventional P and PI controller using time response and relative stability analysis. Finally, PSCAD simulation studies for a 10 kV medium voltage DVR and experimental results using a low voltage laboratory prototype DVR are presented to prove the robustness of proposed controller for DVR under symmetric and asymmetric voltage sags.

Harmonics Reduction of Adjustable Speed Drive Using Transistor Clamped H-Bridge Inverter Based DVR With Enhanced Capacitor Voltage Balancing

Harmonics generated by nonlinear critical loads are major anxiety for the industries. A control technique for dynamic voltage restorer (DVR) is described to limit voltage harmonics introduced by adjustable speed drive (ASD) in the utility. Moreover, this control technique maintains constant dc-link voltage of ASD during any disturbances occurring at point of common coupling. Mathematical description to limit ASD voltage harmonics and to generate reference dc-link voltage of ASD is illustrated in the dq0 frame. Transistor clamped H-bridge (TCHB) multilevel inverter (MLI) is used as a voltage source inverter of DVR. An enhanced capacitor voltage balancing (ECVB) method for TCHB MLI for the fast dynamic performance of DVR is also discussed. The proposed control technique of DVR to limit ASD voltage harmonics is simulated using MATLAB software. Furthermore, a simulation for DVR protecting ASD during source harmonics, unbalance, sag, and swell is carried out and results of ASD performances are demonstrated. The working of the proposed controller of DVR with ECVB strategy based TCHB is reverified using experimental results. ASD voltage harmonics mitigation and fast dynamic response of ECVB based TCHB are the highlights of this article. The performance of the proposed strategy shows satisfactory results with a less complex control system.

Implementation of solar PV system unified ZSI-based dynamic voltage restorer with U-SOGI control scheme for power quality improvement

The main challenge in today's power system is to supply continuous, reliable power and satisfy the high demand. The incorporation of renewable energy sources into the utility grid system can be accomplished. However, the renewable sources are intermittent in nature and the loads work dynamically and cause imbalances to the system voltage within an immediate time. Intermittent renewable sources affect the voltage of the power grid system. Photovoltaic (PV) power generation with Z-source inverter (ZSI)-based dynamic voltage restorer (DVR) is used to avoid that. For step-up low DC voltage to required AC voltage for the compensation of the voltage disturbance, ZSI with the energy storage impedance network is used. DC-DC converters connect the PV cell and the battery storage to the impedance source network. This article also incorporates an upgraded second-order generalized integrator (U-SOGI) control system for the generation of reference voltage signals. The U-SOGI control reference voltage generation approach greatly improves system performance and decreases the harmonic voltage. The voltage-related problems in the system connected to the utility grid are mitigated with DVR. In different load and source conditions, the PV generation with DVR performance is verified by the digital simulation and experimental prototype.