Showing papers on "Voltage sag published in 2022"

Power Quality Enhancement and Power Flow Analysis of a PV Integrated UPQC System in a Distribution Network

Abstract: Increasing awareness for green energy and sustainable energy management has accelerated the popularity for the incorporation of distributed energy resources and distributed energy storage into the distribution network and microgrid. This has proliferated the use of power electronic-based devices giving rise to a serious issue of deteriorating power quality (PQ) in the distribution system. In this context, this article presents a photovoltaic (PV) integrated unified power quality conditioner (UPQC) operating with an adaptive compensating technique based on variable leaky least mean square (VLLMS) algorithm. It is a soft computing-oriented method that offers quicker convergence to the desired condition in an iterative approach keeping the weight of the updating parameters within the specified limit. The VLLMS-based algorithm eliminates the use of low pass or moving average filter for the extraction of fundamental components from polluted source voltage and load current to generate reference signal for the switching of shunt as well as series voltage source converters (VSC) of the UPQC. Due to the involvement of feed-forward component of PV in the compensating technique of shunt VSC, it efficiently and smoothly manages power balance between grid, load, and PV besides resolving the PQ issues of current harmonics and poor power factor at PCC. It also ensures the regulation of dc-link voltage. The series converter maintains pure sinusoidal voltage at the load terminal irrespective of sag/swell and harmonics present in the grid voltage. The effectiveness of the proposed system is verified through simulation as well as hardware implementation under different static and dynamic operating conditions.

Dual-Loop Continuous Control Set Model-Predictive Control for a Three-Phase Unity Power Factor Rectifier

Abstract: In this article, a novel cascade model-predictive control for a three-phase unity power factor rectifier is presented. Unlike the traditional control techniques for rectifiers, the proposed method uses a cascade dual-model-predictive control for the inner and outer control loops. The three-phase currents of the rectifier are controlled with the inner control loop, while the desired output voltage is achieved with the outer control loop. In this proposal, the output power is used as a feedforward to enhance the transient dynamics of the output dc voltage. Several advantages can be highlighted such as a fixed switching frequency, and output voltage variations are avoided when a sudden change in the load or a voltage sag appears. The overall control proposal has been fully integrated into a digital signal processor. Selected experimental results are introduced to validate the theoretical contributions of this article.

An Improved Corona-virus Herd Immunity Optimizer Algorithm for Network Reconfiguration based on Fuzzy Multi-criteria Approach

Abstract: Reconfiguration of the distribution network to determine its optimal configuration is a technical and low-cost method that can improve different characteristics of the network based on multi-criteria optimization. In this paper reconfiguration of unbalanced distribution networks is presented with the objective of power loss minimization, voltage unbalance minimization, voltage sag improvement, and minimizing energy not supplied by the customers based on fuzzy multi-criteria approach (FMCA) using new improved corona-virus herd immunity optimizer algorithm (ICHIOA). The voltage unbalances and voltage sag is power quality criteria and also the ENS refers to the reliability index. Conventional CHIOA is inspired based on herd immunity against COVID-19 disease via social distancing and is improved using nonlinearly decreasing inertia weight strategy for global and local exploration improvement. The methodology is implemented as single and multi-objective optimization on 33 and 69 bus IEEE standard networks. Moreover, the performance of the ICHIOA in problem-solving is compared with some well-known algorithms such as particle swarm optimization (PSO), grey wolf optimizer (GWO), moth flame optimizer (MFO), ant lion optimizer (ALO), bat algorithm (BA) and also conventional CHIOA. The simulation results based on the FMCA showed that all criteria are improved with reconfiguration due to compromising between them while in single-objective optimization, some criteria may be weakened. Also, the obtained results confirmed the superiority of the ICHIOA in comparison with the other algorithms in achieving better criteria with lower convergence tolerance and more convergence accuracy. Moreover, the results cleared that the ICHIOA based on FMCA is capable to determine the best network configuration optimally to improve the power loss, voltage sag, voltage unbalance, and ENS in different loading conditions.

Control of DSTATCOM Using ANN-BP Algorithm for the Grid Connected Wind Energy System

Abstract: Green energy sources are implemented for the generation of power due to their substantial advantages. Wind generation is the best among renewable options for power generation. Generally, the wind system is directly connected with the power network for supplying power. In direct connection, there is an issue of managing power quality (PQ) concerns such as voltage sag, swells, flickers, harmonics, etc. In order to enhance the PQ in a power network with a wind energy conversion system (WECS), peripheral compensation is needed. In this paper, we highlight a novel control technique to improve the PQ in WECS by adopting an Artificial Neural Network (ANN)-based Distribution Static Compensator (DSTATCOM). In our proposed approach, an online learning-based ANN Back Propagation (BP) model is used to generate the gate pulses of the DSTATCOM, which mitigate the harmonics at the grid side. It is modelled using the MATLAB platform and the total harmonic distortion (THD) of the system is compared with and without DSTATCOM. The harmonics at the source side decreased to less than 5% and are within the IEEE limits. The results obtained reveal that the proposed online learning-based ANN-BP is superior in nature.

Design and performance analysis of three phase solar PV integrated UPQC

Abstract: A renewable energy resource associated with transmission line integrating Unified power quality conditioner (UPQC) accomplishes lossless power transmission. In this compensation, the series and shunt compensator are connected side by side. The solar integrated unified power quality conditioner (PV-UPQC) has gained the benefits of active power filtering and distributed generation. Avoidance of MPPT required for solar power generation to perform maximum power point tracking is replaced by shunt compensation; compensate reactive power and harmonics present at load current. The series compensation evolves voltage swell and sag problems in grid. The system is evaluated using MATLAB to synthesize combined operation, reactive power injection, voltage control, etc. A pulse amplitude controlled voltage source inverter present before transformer can perform active power filtering. A dc link capacitor supplies enough energy needed to the shunt active filter system to impart harmonics at output side. To resolves voltage control in bus by improving power factor. The source current controllability have been executed by DSTATCOM and dynamic voltage restorer (DVR).

Effect of Fault Ride Through Capability on Electric Vehicle Charging Station Under Critical Voltage Conditions

Abstract: A high-quality power supply is required for the proper functioning of the electric vehicle (EV) charging system. However, the voltage quality is one of the significant issues in the distribution grid. This article aims to examine the impacts of voltage disturbance on EV batteries and charging systems, and provides a fault ride-through capability (FRTC) to enhance the voltage quality. The charging system is constructed by the three-phase controlled rectifier and the dc–dc converter. The EV battery pack is modeled with lithium-ion batteries. The FRTC system is designed to improve the voltage quality, and it is achieved through the dynamic voltage restorer. It protects the EV batteries and charging system from the critical voltage sag levels. The performance of the proposed EV charging station (EVCS) has been investigated in 30%, 60%, and 90% voltage sag through the MATLAB/Simulink platform. Also, the real-time validation has been carried out by the software-in-the-loop test with the help of the dSPACE (DS1202) real-time system. The EVCS with an FRTC system provides better performance than the conventional EVCS.

On Real-Time Detection of Line Sags in Overhead Power Grids Using an IoT-Based Monitoring System: Theoretical Basis, System Implementation, and Long-Term Field Verification

Abstract: For overhead power grids, unexpected serious line sagging of extra-high voltage transmission lines would easily lead to major blackouts. Different direct and indirect sag measuring methods have been proposed, but they all have their own limitations. In this study, an Internet of Things (IoT)-based sag-monitoring system is proposed, which is able to perform real-time detection of line sags. The whole system has been deployed on two 161-kV lines for long-term field testing. The effectiveness of the proposed sag-monitoring system is verified through both theoretical calculation and field measurements. In this sag-monitoring system, a sag-sensing module is equipped with an embedded triaxial accelerometer to detect line sags at different spans of a single circuit. A catenary equation that takes temperature dependency into consideration is derived, so the measured accelerometer parameters can be converted to accurate line sag values. The long-term testing results show that the proposed sag-monitoring system yields an average error of 2.09%. The average differences between the sag values coming from the proposed system and a commercial sag measuring device are relatively small (between 0.57% and 4.14%), which proves that the sag values provided by the proposed system are reliable and accurate in the long-term testing. In addition, compared to the other existing sag measuring methods, the advantages of employing the proposed system are high measurement accuracy, and enabling wide field implementation, online monitoring, long-term field operation, and real-time transmission.

Artificial Electric Field Algorithm-Pattern Search for Many-Criteria Networks Reconfiguration Considering Power Quality and Energy Not Supplied

Abstract: Considering different objectives and using powerful optimization methods in the distribution networks reconfiguration by accurately achieving the best network configuration can further improve network performance. In this paper, reconfiguration of radial distribution networks is performed to minimize the power loss, voltage sag, voltage unbalance, and energy not supplied (ENS) of customers using a new intelligent artificial electric field algorithm-pattern search (AEFAPS) method based on the many-criteria optimization approach. The voltage sag and voltage unbalance are defined as power quality indices and the ENS is the reliability index. In this study, the pattern search (PS) algorithm enhances the artificial electric field algorithm’s (AEFA) flexibility search both globally and locally. AEFAPS is applied to determine the decision variables as open switches of the networks considering the objective function and operational constraints. The proposed methodology based on AEFAPS is performed on an unbalanced 33-bus IEEE standard network and a real unbalanced 13-bus network. The reconfiguration problem is implemented in single-criterion and many-criteria optimization approaches to evaluate the proposed methodology’s effectiveness using different algorithms. The single-criterion results demonstrated that some power quality indices might be out of range, while all indices are within the permitted range in the many-criteria optimization approach, proving the effectiveness of the proposed many-criteria reconfiguration with logical compromise between different objectives. The results show that AEFAPS identified the network configuration optimally and different objectives are improved considerably compared to the base network. The results confirmed the superior capability of AEFAPS to obtain better objective values and lower values of losses, voltage sag, voltage unbalance, and ENS compared with conventional AEFA, particle swarm optimization (PSO), and grey wolf optimizer (GWO). Moreover, the better performance of AEFAPS is proved in solving the reconfiguration problem compared with previous studies.

Superconducting Magnetic Energy Storage Based DC Unified Power Quality Conditioner with Advanced Dual Control for DC-DFIG

Abstract: The development of DC custom power protection devices is still in infancy that confines the sensitive loads integrated into medium-voltage (MV) and low-voltage (LV) DC networks. Considering the DC doubly-fed induction generator (DC-DFIG) based wind energy conversion system (WECS), this paper proposes a dual active bridge (DAB) based DC unified power quality conditioner (DC-UPQC) with the integration of super-conducting magnetic energy storage (SMES) to maintain the terminal voltage of DC-DFIG and regulate the current flow. The principle of the proposed DC-UPQC has three parts, i.e., parallel-side DAB (PDAB), series-side DAB (SDAB), and SMES, used for the voltage compensation, current and power regulation, and energy storage, respectively. The circuit principle of the PDAB and SDAB and the modeling of SMES are analyzed in this paper. A DC dual control strategy is also proposed to deal with the DC voltage oscillation generated by the AC-side asymmetrical fault. A case study of DC-DFIG interfaced with DC power grid is carried out, integrated with the proposed SMES-based DC-UPQC to verify the high-power applications of the proposed structure. Finally, an experiment is implemented, and the results demonstrate the correctness of the theoretical analysis and the feasibility of the proposed structure.

Passive Harmonic Filter Design Considering Voltage Sag Performance - Applicable to Large Industries

Abstract: Nowadays, nonlinear loads such as load commutated inverter (LCI) drives are being used by industrial sector throughout the world. However, despite the LCI drive uses low-cost thyristors and their corresponding controllers, which have high efficiency and low manufacturing cost, there are concerns regarding the use of LCI drives which are two-fold: (i) they generate harmonics and (ii) they are sensitive to voltage sags occurring at their PCC. In the literature, passive harmonic filters have been suggested to address the former concern and therefore various filter designing techniques have been introduced. However, the need to elaborate a cost-effective filter to address both concerns regarding LCI drive operation has been neglected. Therefore, this paper presents an innovative approach for designing passive filters which can decrease the harmonic distortions generated by LCI drives while ensuring more reliable annual operation of these equipment. Besides, other aspects of passive filter designing, such as eliminating detuning effects, resonance elimination and harmonic loading of capacitors, have been taken into account to provide a general and practical filter designing approach for real industrial applications. In order to evaluate the innovative proposed approach, a passive filter is designed for LCI drive used in an Iranian large copper mine company.

Overhead Transmission Lines Sag and Voltage Monitoring Method Based on Electrostatic Inverse Calculation

Abstract: Transmission line sag and voltage are key information to reflect the real-time operation state of power grid. Contactless measurement method has great advantages of no electrical contact, flexibility and mobility, but it is also vulnerable to environmental changes. In this article, a novel overhead transmission line contactless sag and voltage monitoring method is proposed, which only needs a simple potential measurement array and can apply to dynamic conductor measurement. The electrostatic coupling model between the transmission lines and the measuring points is established. The sag and voltage inversion calculation model is proposed and the ill-posed problem is solved. The measurement array and the data acquisition method are designed. The equivalent measurement area (EMA) is determined considering the difference between 3-D model and 2-D model of overhead line. Finally, the effectiveness of the proposed method is verified by single-circuit transmission line simulation and scale-down experiment.

Power quality improvement in distribution system based on dynamic voltage restorer using PI tuned fuzzy logic controller

Abstract: Purpose. This article proposes a new control strategy for Dynamic Voltage Restorer (DVR) in utility grid for distribution system. The proposed DVR using PI tuned fuzzy logic scheme is based on replacement of conventional DVR and voltage sag compensation in distribution system network. The novelty of the proposed work consists in presenting an enhanced PI tuned fuzzy logic algorithm to control efficiently the dynamic voltage restorer when voltage sag is suddenly occurred. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for power quality problems. Our strategy is based on tuned fuzzy control of reactive powers and also closed loop for harmonic reduction in distribution system. The proposed control technique strategy is validated using MATLAB / Simulink software to analysis the working performances. Results. The results obtained clearly show that DVR using PI tuned fuzzy logic have good performances (sag compensation, harmonic reduction) compared to conventional DVR. Originality. Compensation of voltage sag/ swell in distribution for reactive power and current harmonic reduction by using DVR based PI tuned fuzzy logic controller. Practical value. The work concerns the comparative study and the application of DVR based on PI tuned fuzzy techniques to achieve a good performance control system of the distribution system. This article presents a comparative study between the conventional DVR control and PI tuned fuzzy DVR control. The strategy based on the use of a PI tuned fuzzy controller algorithm for the control of the continuous voltage sag and harmonic for the distribution network-linear as well as non-linear loads in efficient manner. The study is validated by the simulation results based on MATLAB / Simulink software.

Delay-Based Phase-Locked Loop Parameters Design Based on Stability Region of Grid-Connected Single-Phase Inverter Under Grid Voltage Sags

Abstract: For the grid-connected inverter, grid voltage sag can be a typical phenomenon. From the prospective of safe and robust operation, the inverter should be stable when the grid voltage sag (or large disturbance) occurs. Although the inverter stability in this case has attracted considerable attentions, few studies have given suggestions on the system stability boundary and parameter design. To fill this gap, this article deeply discusses the large-signal stability of the system under different situations and reveals the quantified impact of the phase-locked loop (PLL) on the large-signal stability of the system based on the fundamental current-source model. The large-signal stability criterion and boundaries for grid voltage sags are established, which are instructive to the design of PLL parameters. Besides, a novel design guideline for the PLL parameters is proposed to ensure the robust operation of the system both under the steady-state and grid voltage sags, as well as to achieve good dynamic performance after large disturbance occurs. The theoretical, simulation, and experimental results show that the proposed stability boundary has certain accuracy and the PLL parameters design guideline can ensure the system stability both under steady-state and grid voltage sag conditions.

An End-to-End Deep Learning Method for Voltage Sag Classification

Abstract: Power quality disturbances (PQD) have a negative impact on power quality-sensitive equipment, often resulting in great financial losses. To prevent these losses, besides detecting a PQD on time, it is important to classify it, so that appropriate recovery procedures are employed. The majority of research employs machine learning model PQD classifiers on manually extracted features from simulated or real-world signals. This paper presents an end-to-end approach that circumvents the manual feature extraction and uses signals generated from mathematical voltage sag type formulas. We developed a configurable voltage sag generator that was used to form training and validation datasets. Based on the synthetic three-phase voltage signals, we trained several end-to-end LSTM classifiers that classify voltage sags according to ABC classification. The best-performing model achieved an accuracy of over 90% in the real-world dataset.

Dynamic Voltage Restorer (DVR) with a novel robust control strategy

Abstract: With the advancement of technology, electric equipment and loads have become more sensitive to problems related to power quality, such as voltage sag, swell, imbalances, and harmonics. To detect faults and to protect sensitive loads from these voltage distortions, a Dynamic Voltage Restorer (DVR) series compensator is among the best available cost-effective solutions. One of the main goals of the DVR is to achieve a control structure that is robust, stable, and can handle properly the disturbances (e.g., grid voltage issues, load current, and fluctuations at the DC link voltage) and model uncertainties (e.g., inverters and filter parameters). In this work, a novel framework control strategy based on Uncertainty and Disturbance Estimator (UDE) is proposed to improve the response of the DVR to properly compensate the load voltage under a variety of power quality issues, particularly the ones associated with the grid voltage disturbances. Additionally, the stability of the proposed control system is analyzed and validated using the Lyapunov stability theory. The advantages of the new control system are robustness, simplified design, good harmonic rejection, low tracking error, fast response, and sinusoidal reference tracking without the need for voltage transformations or specific frequency tuning (e.g., abc-dq0 and Proportional-Resonant). This research uses the MATLAB/Simulink software to validate the effectiveness of the proposed scheme under a diverse set of conditions with no control limitations. Moreover, the designed controller is tested under real conditions using Hardware-In-the-Loop (HIL) validation with OPAL-RT real-time simulator coupled with a TI Launchpad microcontroller. The results demonstrate a good performance of the proposed control strategy for a quick transient response and a great harmonic rejection when subject to grid voltage distortions.

Design and Control of Modular Multilevel Converter for Voltage Sag Mitigation

Abstract: Voltage sag in a power system is an unavoidable power quality issue, and it is also an urgent concern of sensitive industrial users. To ensure the power quality demand and economical operation of the power system, voltage sag management has always drawn great attention from researchers around the world. The latest research that realizes the power quality conditioning has used dynamic voltage restorers (DVRs), static VAR compensator (SVCs), adaptive neuro-fuzzy inference systems (ANFISs), and fuzzy logic controllers based on DVR to mitigate voltage sag. These devices, methods, and control strategies that have been recently used for voltage sag mitigation have some limitations, including high cost, increased complexity, and lower performance. This article proposes a novel, efficient, reliable, and cost-effective voltage sag mitigation scheme based on a modular multilevel converter (MMC) that ensures effective power delivery at nominal power under transient voltage conditions. The proposed method, the MMC, compensates for the energy loss caused by voltage sags using its internal energy storage of the submodules, and ensures reliable power delivery to the load distribution system. Furthermore, control strategies are developed for the MMC to control DC voltage, AC voltage, active power, and circulating current. Detailed system mathematical models of controllers are developed in the dual synchronous reference frame (DSRF). Validation of the results of back-to-back MMC for dynamic load distribution system is analyzed which proves the effectiveness of the proposed scheme for voltage sag mitigation.

Voltage stability improvement of an Egyptian power grid‐based wind energy system using STATCOM

Abstract: The increase in electricity demand places its focus on renewable energies as sustainable energy resources. Wind energy is one of the most important green energy sources. The doubly fed induction generator (DFIG)-based wind farm has now gained prominence due to its many advantages, such as variable speed operation and autonomous control of active and reactive power. When the DFIG stator windings are directly connected to the power grid, when a grid fault occurs, some unwanted high current may be produced in the rotor windings, and the protection system will prevent the rotor side converter (RSC) from operating. Therefore, voltage stability is a significant factor in maintaining the DFIG-based wind farm in operation during grid faults and disturbances. This paper applies a static synchronous compensator (STATCOM) to restore the voltage levels of the Egyptian power grid connected to Al Zafarana-5th stage wind farm, which is made of 100 Gamesa G52/850 kW DFIG machines. In this paper, the STATCOM is controlled by a proportional integral (PI) and is compared with a STATCOM controlled by fuzzy logic control (FLC). For simulation, the MATLAB/SIMULINK environment is used. Moreover, the simulation results show that STATCOM devices with fuzzy logic controllers improve the effects of grid faults and disturbances such as a single line to ground fault, a line to line fault, voltage sag, and voltage swell as compared with STATCOM with PI controllers. Also, STATCOM devices based on FLC improve the stability and power quality of the system and the power system restoration procedures for the existing and future-planned wind farms.

Comparative Analysis of Control Strategies for Dynamic Voltage Restorer

Abstract: Power quality problem is a very big problem in power system, some equipment is installed in the power system to solve it, among them dynamic voltage restaurateur is one of the best equipment. Many types of control techniques can be installed in dynamic voltage restaurateurs. Three types of control methods have been adopted in this research work. Various types of the control techniques such as PI control technique, PR control technique, and hysteresis control technology has been investigated. In this study, two major effects of power quality have been taken, which include voltage sag and voltage swell. These two power quality problems are included up to 30 percent, which is solved through all three methods. Based on the analysis of control technology, the “PI control” method is the best method for Dynamic Voltage Restorer. In this study, Designed control strategies using PI PR Hysteresis controller, with comparative analysis for the implemented for the DVR. PI PR control strategies are designed for medium-level voltage and Hysteresis control strategy design for low-level voltage.

Multi‐functional control strategy for power quality improvement of three‐phase grid using solar PV fed unified power quality conditioner

Abstract: This article presents a generalised integrator with a band-pass filter frequency locked loop (GI-BPF-FLL) control algorithm for the solar photovoltaic (SPV)-integrated unified power quality conditioner (SPVUPQC) system. This control algorithm extracts fundamental components (FC) of the distorted and deformed input signals, and it has the competence of eliminating DC-offset. The key objective is to decrease the number of sensors used in the control algorithm of the SPVUPQC system while enabling the power quality enhancement features in the distribution grid. The effectiveness of the presented GI-BPF-FLL control algorithm and its performance comparison with the conventional control algorithm are discussed in both the time domain as well as frequency domain analysis. The SPVUPQC system consisting of a distribution static compensator (DSTATCOM) and a dynamic voltage restorer (DVR), to compensate simultaneously both the voltage distortions, sag/swell etc. as well as current harmonics, reactive power and load currents unbalances etc. The model of the SPVUPQC system is developed in the MATLAB/Simulink environment, and its results are presented to demonstrate its capabilities. The system's validation is also done on the hardware prototype, and it performs effectively for the voltage and current power quality enhancement simultaneously. The load side voltages magnitudes, grid side voltages and the grid currents total harmonic distortions are found within the boundaries specified in the IEEE standard 1159 and the IEEE standard 519.