Voltage Sag Research Articles

Queen honey bee migration (QHBM) optimization for droop control on DC microgrid under load variation

Transmission line impedance in DC microgrids can cause voltage dips and uneven current distribution, negatively impacting droop control and voltage stability. To address this, this study proposes an optimization approach using heuristic techniques to determine the optimal droop parameters. The optimizcv ation considers reference voltage constraints and virtual impedance at various load conditions, particularly resistive. The optimization problem is addressed using two techniques: queen honey bee migration (QHBM) and particle swarm optimization (PSO). Simulation results show that QHBM reaches an error of 0.8737 at the fourth iteration. The QHBM and PSO algorithms successfully optimized the performance of the DC microgrid under diverse loads, with QHBM converging in 5 iterations with an error of about 0.8737, and PSO in 40 iterations drawn error is 0.9 while keeping the current deviation less than 1.5 A and voltage error less than 0.5 V. The deviation of current control and virtual impedance values are verified through comprehensive simulations in MATLAB/Simulink.

Study of the Crowbar's Functioning in Doubly Fed Induction Wind Generators: Towards Achieving Fault Ride Through Capability

This work examines the analysis of temporary behaviors and crowbar hardware layout for enhancing the fault ride-through capability (FRTC) in doubly fed induction wind generators (DFIWGs) A crowbar that is linked in parallel to the rotor side converter (RSC) is a feature found on the majority of DFIWGs these days to safeguard the RSC and DC-bus capacitor (DCBC). Previous studies demonstrated that the crowbar resistance has an impact on the DFIWG transient response's oscillations and peak values. In order to satisfy the FRTC criterion, the article initially methodically examines the DFIWG dynamics with and without a crowbar during a 100% voltage dip and studies the effects of two resistance values on the DCBC. It has been demonstrated that choosing a crowbar resistance greater than the permitted range may cause the DFIG FRT performance to decline. By actively addressing grid faults and improving performance, stability, and dependability, this integrated crowbar shows the potential of state-of-the-art control approaches for the dependable and efficient use of DFIWGs. MATLAB/Simulink is used to run robust simulations, and the results unambiguously show that the proposed model may significantly improve the FRTC of DFIWGs.

Honey Badger Algorithm Based DVR Controllers for Improved Power Quality‏ in a Microgrid Combined of (Wind System\ Grid\Nonlinear Load)

Power quality (PQ) is crucial in today's energy supply networks, where even little voltage fluctuations can have a big impact on how well household appliances and technologies operate. The suggested dynamic voltage regulator (DVR) approach helps to create a new generation power grid that is more dependable and effective. In this study, the honey badger optimizer (HBO) is used to optimize the controllers of the DVR for improving PQ via voltage control. The efficacy of the optimized DVR is further increased by its integration with a microgrid (MG) wind supply. The suggested technique makes use of a low-complexity control approach for voltage regulation to adjust for harmonic distortion, swells, and voltage dips in the addressed system. The technique accomplishes voltage improvement, bus stabilization, energy-efficient utilization, and harmonic distortion reduction by using the DVR in conjunction with an MG wind supply. Various voltage disturbances, such as balanced and unbalanced swell and sag, voltage imbalance, notching, various fault states, and power system harmonic distortion, are taken into consideration to show the approach's usefulness. The findings indicate PQ enhancement, demonstrating that the load voltage roughly matches the nominal value.

DYNAMIC MODELLING OF THREE-PHASE MICROGRIDS INCLUDING DQ0 CURRENT CONTROLLED PHOTOVOLTAIC GENERATION UNDER TRANSIENT CONDITIONS

ABSTRACT: The photovoltaic generation can be interconnected to power systems or to insulated grids to satisfy the growing electrical demand as an alternative renewable energy source. The photovoltaic generator dynamics affects the control, protection, stability, and power quality of the electrical grid, this network dynamics requires to be examined and conveniently regulated and adjusted. The dynamic averaged model for the dq0 current controlled DC/AC inverter is applied to obtain the time-domain response to electromagnetic transients under special conditions such as electrical load fluctuations, unbalanced faults, voltage and current transients to verify e.g., the ride through capability or to adjust the protection and control devices, these transients can be present during the operation of electrical microgrids and power systems interconnected with photovoltaic generation. The system modelling includes the photovoltaic plant interconnected with the microgrid using the dq0 current controlled DC/AC inverter. The case studies are applied to analyse three-phase electrical microgrids, their time-domain response, and the obtained voltage and current waveforms can be used to verify the dynamic behaviour and stability of the electrical system interconnected with photovoltaic generation and similarly to verify the operation of the dq0 current controller for the inverter. The results can be used to control the microgrid dynamic behaviour. Keywords: current control, dq0 transform, inverter, microgrids, photovoltaic generation, power quality, protection, time-domain, transients, unbalanced faults, unbalanced voltage sags, voltage source converter

Laboratory-Based Investigation of Contactors Susceptibility to Short Duration Voltage Sags

Voltage sags pose substantial challenges in electrical systems, disrupting power supply and adversely impacting equipment. This paper outlines the issues arising from voltage sags, emphasizing their detrimental effects on electrical installations powered by relays and contactors. The study delves into the susceptibility of these critical components when faced with voltage fluctuations, exploring how sags influence their functionality. Additionally, the research presents experimental results from laboratory tests, focusing on contactors of different power exposed to voltage sags lasting less than one cycle. These assessments provide insights into the performance of contactors under short-duration voltage variations, offering valuable contributions to enhancing the reliability of electrical systems.

Distribution Expansion Planning of Electrical Networks Considering Electrical Losses and Financial Losses Due to Voltage Sags and Interruptions

Currently, distribution system planning is crucial to meet both the present and future electricity needs of customers with minimal investments. This paper introduces a novel methodology to solve the distribution expansion planning problem by employing a heuristic based on genetic algorithms (GA). The proposed GA aims to minimize investment costs, electrical losses, and financial losses due to voltage sags and power interruptions. This GA is applied in the 18-busbar network with three planning stages. The results show that the GA deals with efficiency with the multi-objective problem obtaining solutions with reduced iterations and with minimum investments considering electrical losses, and financial losses.

Smart grid data compression and reconstruction by wavelet packet transform

A smart grid is a power network from generation to consumers and provides beneficial, steady, and safe electricity. It utilizes smart meters for billing, phasor measurement units to check the system's health., etc. As a result, it contains enormous volumes of real-time data that may be shared and stored by users, control centers, and services in a smart grid. It weakens the smart grid's communication networks. The size of the data in a smart grid will grow extremely in the future. As a result, it must reduce distortion in data compression and denoise while minimizing the demand on storage and communication networks. The goal of data compression and denoising should be to maximally conserve the useful data while accurately reflecting the state of the system and providing sufficient data regeneration at the receiving end. This paper has used lower-order different wavelets to represent a design to compress and reconstruct data at level three using wavelet Packet Transform. It works on the phasor measurement unit's current magnitude and voltage sag signals.•The proposed design has a better compression ratio.•Low reconstruction error.•This design is easy to access, systematic, profitable, and not time-consuming.

IoT based monitoring system for DFIG based wind turbines under voltage dips

Due to their partial-rating power converters and dynamic performance, doubly-fed induction generators (DFIGs) are commonly used in wind turbines (WT). However, grid-connected DFIGs are vulnerable to voltage dips, which can cause power quality concerns and possible turbine damage. An Internet of Things (IoT)-based monitoring technique for field-oriented control (FOC)-based DFIG with grid-side converter (GSC) control is proposed in this paper. The proposed approach uses real-time WT voltage and current data to dynamically alter the GSC control settings, allowing for steady operation and minimizing power quality problems during voltage dips. A 2 MW variable-speed pitch-controlled DFIG with a speed limit of 900–2000 rpm is used for performance investigation under voltage dips with crowbar protection. An IoT based monitoring system sends real-time information to a cloud server for additional analysis after detecting anomalies. The ThingSpeak cloud platform sends email notifications of defects, and an MIT App Inventor application is constructed for data visualization. The proposed strategy's effectiveness is confirmed through the simulation results.

An Adaptive Virtual-Impedance-Based Current-Limiting Method with the Functionality of Transient Stability Enhancement for Grid-Forming Converter

Grid-forming (GFM) converters are regarded as the most promising solution for grid-connected converters of renewable energy due to their robustness against weak grids. However, attributable to their voltage source characteristics, GFM converters may experience overcurrent issues during large disturbances. The virtual impedance (VI) method is an effective method to solve this problem. Nevertheless, there exists a contradiction between the demands for VI posed by current limitations and transient stability. Firstly, the analytical equations of virtual impedance for limiting the fault steady-state current of a GFM converter with different depths of grid voltage sag are solved. On that basis, an adaptive method based on virtual impedance is proposed to limit the fault current. Moreover, the analytical equation of the output active power of the converter when using adaptive virtual impedance to limit the fault current is solved. On this basis, the effect of the virtual impedance ratio on the transient stability is investigated. Finally, an adaptive virtual-impedance-based current-limiting method with the functionality of transient stability enhancement for a grid-forming converter is innovatively proposed. The enhancement effect of the method is verified by the equal area criterion method and phase portrait method. Finally, the efficacy of the proposed method in limiting fault currents and enhancing transient stability is validated through hardware-in-the-loop (HIL) experiments.

A novel hardware implementation approach to enhanced stable island operation of hybrid distributed generation using superconducting fault current limiters

In this research study, we have explored the transformative potential of integrating Superconducting Fault Current Limiters (SFCLs) and Superconducting Magnetic Energy Storage (SMEC) systems in hybrid distributed generation setups. Through a meticulous series of experiments, simulations, and detailed analyses, we have delved into the dynamic responses of these advanced technologies amidst various grid disturbances and fault scenarios. Our investigations encompassed a spectrum of grid disturbance scenarios, including voltage sags, frequency variations, and short circuits, revealing the crucial role that SFCLs and SMEC play in maintaining stable islanded operation. The numerical results showcased in this study demonstrate the pivotal role of SFCLs and SMEC in swiftly responding to grid disturbances, effectively limiting fault impacts and ensuring a continuous and uninterrupted power supply to critical loads. For instance, SFCLs reduced fault currents by up to 60 % within 15 ms during short circuit events at Node A, while voltage sags of 20 % were mitigated within 75 ms, showcasing a fault clearing time of 45 ms. Additionally, the SMES system's energy capacity of 10 kWh played a significant role in voltage and frequency stabilization, reducing fault impacts by over 50 % during various fault scenarios. Furthermore, our detailed analyses provide valuable insights into the SFCL performance, including activation times and fault current reduction capabilities. The transient responses of the system exemplify the remarkable ability of SFCLs to expedite fault recovery and stabilize microgrids. This study presents a novel hardware implementation approach aimed at enhancing the stable island operation of hybrid distributed generation systems through the integration of SFCLs and SMEC. The research addresses the pressing need for innovative solutions to ensure grid stability and reliability amidst the increasing penetration of renewable energy sources. Through hardware simulations, the effectiveness of SFCLs in limiting fault currents and improving system stability is demonstrated. Moreover, a quantitative comparison with existing solutions highlights the superiority of the integrated SFCL-SMES system in enhancing stable island operation, with fault tolerance improvements of up to 56 % compared to traditional methods. Overall, this research contributes to advancing the field of hybrid distributed generation and fault management, offering valuable insights into the practical implementation of SFCLs and SMES for grid resilience and reliable renewable energy integration.

UPQC-Based Hybrid Technique to Reduce Power Quality Problems in the Photovoltaic Grid System

In addition to Power Quality (PQ) problems caused by solid state devices in the distribution side of grid connected Photo Voltaic (PV) system, quality of power also suffers in the source side by the usage of converters. Generally, PQ problems mitigation strategy has turned into a critical issue in grid-connected PV systems. This paper proposes a control topology for PQ issues mitigation scheme in grid connected PV systems. The primary goal of this study is to enhance the PQ in power distribution system through eradicating the voltage interruption, voltage swell and sag as well as voltage fluctuation. To accomplish these changes, Unified Power Quality Conditioners (UPQCs) with controllers were utilized. Then the faults are mitigated by the utilization of UPQC with Tree Seeds Algorithm (TSA) — Adaptive Neuro-Fuzzy Interference System (ANFIS). At first, the normal properties of the grid-connected PV systems are dissected. From that point forward, a few interruptions are made in the system and the abnormal characteristics are analyzed. Then the abnormal characteristics of PQ problems are diminished in the utilization of UPQC and TSA–ANFIS controllers. UPQC is one of the best filters topologies which can mitigate and control all PQ problems. The combined algorithms of TSA-ANFIS are used to keep the dc-link voltage in UPQC at consistent level. The proposed hybrid approach is executed in MATLAB/Simulink platform and the performance is studied. Further, the proposed method is compared with existing Elephant Herding Optimization (EHO) technique and also with hybrid EHO-ANFIS techniques. The comparison results showed that the proposed technique is superior to the EHO and EHO-ANFIS techniques.

Hierarchical control on EV charging stations with ancillary service functions for PV hosting capacity maximization in unbalanced distribution networks

PV hosting capacity of a practical three-phase unbalanced distribution network is expected to increase, thus increasing safe PV penetration and speeding up the decarbonization of power systems. However, power unbalances and bus voltage violations are two major obstacles limiting further increases in the PV hosting capacity. With the popularization of electric vehicles (EVs), EV charging stations (EVCSs) as controllable loads can effectively provide grid ancillary services, which helps enhance the PV hosting capacity. In this regard, this paper proposes a hierarchical control method for EVCSs in an unbalanced network, consisting of central day-ahead scheduling and local real-time dynamic control. It is novel that the local control capability of EVCSs is reserved in the central scheduling. A three-phase day-ahead EV charging scheduling optimization model is developed to reduce the power unbalance and the bus voltage violation, and in turn, improve the PV hosting capacity. Moreover, active power transfer and voltage droop control are developed as two ancillary service functions for local real-time control responding to dynamic network operating conditions. Numerical simulations verify the effectiveness of the proposed method in enhancing PV hosting capacity and providing grid ancillary services.

A new adaptive droop control strategy for improved power sharing accuracy and voltage restoration in a DC microgrid

In a DC Microgrid, accurate power sharing and voltage restoration are two primary control goals to guarantee power quality and reliable operation. Inaccurate power sharing is a significant concern due to discrepancies in feeder line resistance, faulty equipment, lack of monitoring and control, and nonlinear load. Moreover, inaccurate power sharing may lead to overloading of converters and cause a cascade of failures throughout the entire system. This study proposes a new adaptive droop control strategy to address these challenges. To enhance accurate power sharing, error current sharing is formulated by considering bus current and total rated current. This is regulated by the adaptive controller to adjust droop resistance. Additionally, the impact of droop voltage because of feeder line resistance is considered in the proposed strategy. The primary control loop regulates the output voltage of converter utilizing the proposed observer-based optimum sliding mode control (OOSMC). The controller gain of the OOSMC is optimized using a gradient-based method to enhance transient and steady state response of the converter output. In the secondary loop, the twin-delayed deep deterministic policy gradient (TD3) for voltage restoration is employed with a new reward function to optimally tune the proportional-integral (PI) controller. Finally, the superiority of the proposed strategy is evaluated through rigorous testing scenarios, including the use of constant power load (CPL) and sudden failure in the converters. Moreover, the proposed strategy is validated by simulations and laboratory-based experiments. The results show that the OOSMC outperforms GA and PSO while the TD3 has better performance than traditional PI. Furthermore, when the equivalent power-rated converters are implemented in the system, the proposed strategy can transfer identical power sharing of 4 W to the load and provide accurate current sharing of 0.167 A compared to conventional droop control while the DC bus voltage is maintained at the 24 V reference value. In the case of different power-rated converters, the proposed strategy can achieve power sharing accuracy. The first, second and third converters supply 2 W, 4 W, and 6 W, respectively, to the load and provide accurate current sharing. Meanwhile the DC bus voltage can be kept at the reference voltage of 24 V. In the scenario of various kinds of disturbances, the proposed strategy can achieve accurate power and current sharing when the system is tested under load and input voltage variations. Meanwhile the DC bus voltage always returns to the voltage reference. Moreover, the proposed strategy can share power and current accurately when the converter occurs a sudden failure.

Context-aware voltage sag waveform decomposition method using hybrid models for complex power quality detection

To analyze the voltage sag characteristics of distribution networks, automotive companies need an accurate and efficient non-stationary signal analysis tool to extract voltage sag feature information from power quality monitors and fault recorders, which is crucial for automotive companies to analyze grid characteristics and improve localized charging strategies. We innovatively propose a hybrid decomposition method to decompose voltage sag waveforms from composite disturbance data. Subsequently, we design a context-aware mechanism to adapt the proposed decomposition method to the complex power quality data in different regions. In addition, tests were conducted on an integrated power quality simulation system to verify that this method can accurately decompose the voltage sag waveform from the composite disturbance signals. Finally, the experimental simulation results also show the better performance of the method in decomposing voltage sag waveforms with different causes in different composite disturbance signals compared with other mainstream methods.

Mitigation of voltage sag and voltage swell by using dynamic voltage restorer

Recent power quality (PQ) research shows that the most common types of power quality disturbances are voltage sags and swells in medium and low-voltage distribution grids. This paper shows how to improve two significant power quality disturbances: sags and swells voltage. To find out what effect these two PQ issues have in real life, a study case based on real nonlinear loads data from large induction motors at Beshai Company in Sadat City in Egypt is investigated. The dynamic voltage restorer (DVR) has been suggested as a solution to the voltage swell and voltage sag issues. The point of common coupling (PCC) is linked with the dynamic voltage restorer to mitigate the PQ problems that have been found. The power network, loads, and DVR may all be modeled using the MATLAB/Simulink platform. The jellyfish search optimizer (JFS) is used to get the gain settings of the proportional and integral (PI) controller for the proposed DVR. MATLAB/Simulink's results show that the proposed device is effective, reliable, and has low latency.

Assessment of Power Quality Enhancement in a Grid-tied PV Network via ANN-based UPQC

Background: Microgrid is the recent decade terminology that surpasses the long-run issues associated with the public and utility grids. Among the renewable energy sources, solar PV units have gained greater importance owing to their huge potential availability and laidback operating characteristics on technological grounds. Conversely, it offers pollution-free electricity and perhaps the dependability is volatile in most situations. The literature study accumulates the foresaid setback and presents the fluctuation-less and controlled standard quality of power outputs. Objective: The aim of this particular research is to propose an assessment of Power Quality enhancement in a Grid-tied photovoltaic (PV) network via ANN-based UPQC. The novel idea behind this proposed approach is the UPQC component which deliberately regulates and controls the power system to achieve higher levels of power quality, ultimately meeting the recent IEEE standards. Method: This particular research enhances the performances of UPQC employed in the microgrid unit by replacing the traditional PI controller with a multi-layered feed-forward-type ANN controller for the current regulation of the series active filter. Additionally, a training algorithm for the ANN controller is built, trained and simulated via MATLAB/Simulink platform. The ANN-based UPQC is proposed to alleviate the power quality challenges like sag and swell in voltage, harmonic distortion, the time required for voltage compensation, and power factor. Therefore, UPQC is equipped to enrich the standard of power transfer at the point of common coupling inside the power frameworks, respectively. Result: Finally, the simulation results are presented to validate the operation of the grid-tied PV network via an ANN-based UPQC system. To show the enriched performance of the proposed topology, a comparative analysis is made with PI controller-based UPQC, and outcomes infer to be in agreement with the theoretical discussions. Also, the ANN-based proposed approach reduces the restoration time and THD as well under both sag and swell conditions, respectively. Conclusion: In this articulated work, a PV power system network with a DC-DC converter and three-phase inverter is employed for grid integration. The peak power extraction is ensured via a DC-DC converter with an incremental conductance algorithm. Both UPQCs are analysed and experimented via MATLAB/Simulink platform with inconstant nonlinear loads to investigate the indices mentioned above and corroborate the same within the operating regions.

A method of voltage sag detection based on strong tracking SVD-UKF

Abstract Addressing issues of the traditional strong tracking unscented Kalman filtering (STUKF) algorithm in the process of voltage sag detection, such as inadequate precision, large computational complexity, and unstable iterative procedures, a method of voltage sag detection based on strong tracking SVD-UKF is proposed. Only one unscented transformation (UT) is used per iteration by establishing the linear state equation based on the voltage signal model, which simplifies the calculation procedure. Substituting singular value decomposition (SVD) for Cholesky decomposition averts the challenge of non-positive-definite error covariance matrix, ensuring stable execution of the algorithm. The action position of the fading factor is improved to further enhance detection precision. Through simulation experiments, we validate that the proposed method could effectively detect voltage sag characteristics, including amplitude, phase, and duration time.

Research on Low Voltage Ride-through Characteristics of 300 MW VSPSH Based on BPA

Abstract With the development of new energy, the power grid scale is constantly expanding, which also brings new challenges to the stability of the grid. When some faults occur in the power grid, it leads to a voltage dip; if most of the devices are removed from the power system, it is easy to cause problems of stability and losses. Therefore, it is necessary to investigate the low voltage ride-through (LVRT) characteristics of power electronic equipment with large capacity before grid connection. Different from constant-speed pumped-storage hydropower plants (CSPSH), variable-speed pumped-storage hydropower (VSPSH) units have broad prospects for development in China due to their characteristics of frequency and voltage regulation, energy saving, and high efficiency. In this paper, the three-machine-nine-node model of 300 MW VSPSH is built based on BPA, and the large voltage dip caused by a three-phase short-circuit fault at the grid side is designed to test the LVRT capability of 300 MW doubly fed VSPSH.

Improve the voltage profile of the grid-integrated induction motor with a fuzzy-based voltage source converter

This article suggests installing a series compensator on grid-connected induction motors that allows for the ride-through of unbalanced voltage sag. Fuzzy logic controls the motor voltages in a standard three-phase voltage source inverter or voltage source inverter (VSI). An open-ended three-phase machine and the grid form a series connection for the VSI. The proposed system is well suited for uses where frequency variation is unnecessary, such as with large pumps or fans. There is no requirement for a direct current (DC) source or injection transformer when conducting an electric mutual coupling The severity of the sag in the grid voltage that will prevent EMC from shutting down is proportional to the load on the motors. An increase in the voltage of the DC link may be necessary if the voltage is not balanced. A 1.5 hp four-pole induction motor was used alongside grid voltage disturbances to test the proposed compensator's ride-through capability. Grid's current analysis demonstrates that the proposed system does not require the addition of a passive filter to achieve low levels of total harmonic distortion (THD). Additionally, the control strategy, component ratings, and analysis of the converter's output voltage operating principle and pulse width modulation technique are covered. The system's viability is shown via simulation and experimental results.

Investigation of self-excited induction generator for supporting domestic loads and its extension to a microgrid

This study provides a technical and financial analysis for the incorporation of a microgrid structure with a wind energy conversion system for producing electricity. This study’s primary aim is to provide solutions for issues that arise when isolated induction generators are employed with microgrids. A closed-loop smart electronic load controller is used to regulate the loads in the system that are supplied by the generator. A switched variable capacitor bank is used to supply reactive power initially during a voltage dip at varying winds and loads to sustain the voltage profile. Additionally, a simple voltage control loop-based controller for the generator-side converter maintains the voltage at a steady level. Using HOMER software, an economic study of the suggested wind-based microgrid structure is also presented. A laboratory experimental setup is used to support the MATLAB/Simulink study of the proposed method and its control. The findings support the feasibility of implementing the suggested plan in grid-isolated regions for supplying critical loads.