Grid Voltage Research Articles

Open-loop optimization method based on the GRU and dual-grating demodulation principle for a PZT based optical voltage sensor

Distributed online monitoring of grid voltage is crucial for ensuring power quality, providing a foundational data layer for effective grid management. Piezoelectric grating optical voltage sensing presents a cost-effective solution with high bandwidth and long-distance transmission capabilities. This paper introduces an open-loop optimization approach that leverages the gate recurrent unit (GRU) and dual-grating demodulation principles to enhance the real-time response accuracy and extend the measurement range of piezoelectric-based optical voltage sensors. Experiments conducted within a 2.8 kV sensing range analyze the voltage response and spectral characteristics. After applying corrections, the sensor achieves a linearity of 99.93%, with a maximum deviation of 2.07% and a maximum hysteresis of 3.33%. This method significantly enhances real-time response accuracy and optimizes the utilization of the sensor’s nonlinear measurement range, advancing the application of optical voltage sensors in power grids.

Low-voltage DC collection grids for marine current energy converters: Design and simulations

Marine current energy represents a globally abundant yet largely untapped renewable energy source, offering greater predictability than other sources such as wind. Consequently, it has the potential to play a vital role in the green transition. A critical consideration for harnessing marine current energy is the design of the electrical grid to accommodate multiple turbines. Therefore, this paper presents a study that explores three types of DC collection grids (series, parallel, and star) for a specific marine current energy converter. A simulation model developed for the marine current energy converter is introduced and utilized to assess these topologies for grids comprising ten identical turbines subjected to varying water speeds. The designed topologies are intended for low-voltage and nearshore applications. The simulation results demonstrate that the series collection grid requires a significantly higher DC grid voltage compared to the other topologies for the turbines to operate correctly. Additionally, the study reveals that all three grid topologies can effectively transmit power to the distribution grid with similar power losses.

Improving the performance of grid‐connected inverters during asymmetrical faults and unbalanced grid voltages

AbstractThe increasing penetration of the distributed energy resources (DER) in the power grid, which, while having significant advantages, also pose significant challenges. The behaviors of DERs differ from those of synchronous generators, particularly in abnormal conditions. For this reason, the power grid enforces grid codes to ensure that DERs perform properly in different conditions. For instance, short circuit faults and unbalanced grid voltage are severe transient events that inverters need to be able to pass through without disconnecting from the grid. Furthermore, the inverters are required to support the grid voltage by regulating the active and reactive power injections. This article proposes a voltage support control scheme to support grid voltage during asymmetrical voltage drop by utilizing an optimization problem. In this optimization problem, the active and reactive powers injected into the grid will be obtained optimally by considering constraints such as instantaneous active and reactive power oscillation magnitudes and peak current limitation. To aid in this purpose, the corresponding mathematical formulations such as instantaneous active and reactive power oscillation magnitudes will be obtained by using the currents and voltages in stationary reference frame. The proposed scheme will be verified by simulating it in MATLAB/Simulink under three different scenarios and tested on a real‐time experimental Opal‐RT platform.

Multilevel Middle Point Clamped (MMPC) Converter for DC Wind Power Applications

This manuscript introduces a novel multilevel middle point clamped (MMPC) DC-DC converter and its associated switching scheme aimed at maintaining the desired medium-voltage DC (MVDC) collector grid within offshore all-DC wind farms. Building upon previous work by the authors, which proposed an all-DC structure serving as a benchmark system, this study explores the application of the MMPC DC-DC converter within this framework. Within the all-DC wind generation system, a 9-phase hybrid generator (HG) integrated into the wind turbine is linked to the MVDC collector grid through an AC-DC stage, which is a passive rectifier. This passive rectifier offers elevated voltage ratings and protection against back power flow. The conventional neutral point clamped (NPC) converter concept has been thoroughly investigated and expanded upon to develop the proposed MMPC DC-DC converter. The proposed MMPC DC-DC converter integrates boosting capabilities, facilitating the connection of the generator’s rectified voltage to the MVDC collector grid while regulating variable rectified voltage to a fixed MVDC collector grid voltage. The MVDC collector grid is further interconnected with high-voltage DC (HVDC) through a DC-DC converter situated in an offshore substation. This paper further provides a comprehensive overview of the proposed MMPC DC-DC converter, detailing its operational modes and corresponding switching schemes. Through an in-depth examination of operational modes, duty cycles for each switch and mode are defined, subsequently establishing the relationship between rectified input voltage and MVDC output voltage for the MMPC DC-DC converter. Utilizing the middle point clamped architecture, this innovative converter offers several advantages, including low ripple voltage, a modular structure, and reduced switching stress because of the multilevel voltage and the incorporation of a hard point, which also facilitates the capacitor voltage balancing. Finally, the effectiveness of the proposed converter is evaluated via simulation studies of a wind turbine conversion system utilizing two cascaded MMPC DC-DC converters operating under variable input voltage conditions. The simulations confirm its efficacy, supported by promising results, and validating its performance.

Design-Oriented Transient Stability Assessment for Droop-Controlled Converter Considering Grid Voltage Phase-Angle Jump

Design-Oriented Transient Stability Assessment for Droop-Controlled Converter Considering Grid Voltage Phase-Angle Jump

Low voltage distribution intelligent control system based on distributed photovoltaic grid connection

Abstract This article mainly studied the use of distributed photovoltaic power generation technology to achieve intelligent control of low-voltage distribution networks. With the rapid development of new energy, distributed photovoltaic power generation technology has become an important means to alleviate the current energy crisis and environmental problems. This article first elaborated on the theory and research status of distributed photovoltaic power generation systems. Based on this, artificial intelligence technology was applied to distributed photovoltaic power generation systems for real-time monitoring to enhance their stable and reliable performance. When the simulated grid voltage was set to 220V, the system output voltage was also 220V, showing a deviation of 0.0%, proving that the system has excellent regulation accuracy at this voltage level. This article is an innovative research that integrates distributed photovoltaic power generation with intelligent control, opening up a practical and feasible technical path for the large-scale utilization of clean energy. Therefore, this study has significant academic value and practical significance.

Direct-Axis Current Orientation-Based Grid Voltage Sensorless Control Strategy for Vienna Rectifier Under Unbalanced and Distorted Grid Conditions

Direct-Axis Current Orientation-Based Grid Voltage Sensorless Control Strategy for Vienna Rectifier Under Unbalanced and Distorted Grid Conditions

Controlling of Solar Based Electric Vehicle Charging Station Through Intelligence Controller for G2V and V2G Modes

Abstract: Solar based electric vehicle (EV) charging station was proposed in this paper. The maximum power of a PV module varies due to changing temperature, solar radiation, and load. In order to extract the Maximum power point in this work, an MPPT system consisting of a PV module, a DC-DC converter, and a fuzzy logic controller is designed and simulated in Simulink. The EV battery SOC characteristic is observed to be fully charged within short period. In this paper single Phase grid and the PV system with the Fuzzy controller MPPT is connected to the DC link, which is connected to the EV. Also in the absence of solar PV energy, electric vehicle is charged from the grid. A battery of rating 100AH is charged with the solar PV panel using a boost converter which generates output voltage of 400V. Then the voltage is stepped down for buck operation according to 220 V battery requirement. A Bidirectional AC-DC rectifier is connected to the Grid, and the DC-DC boost converter for the MPPT and the DC-DC bidirectional Converter is connected to the EV for the Charging and Discharging of the EV. During charging and discharging modes the battery voltage and current is presented. It is clear that the grid voltage and current are in phase during charging. During discharging they are said to be out of phase indicating the reverse power flow.

Analytical distributed PV inverter reactive power support strategy for reduction of grid losses and voltage deviations

Analytical distributed PV inverter reactive power support strategy for reduction of grid losses and voltage deviations

A Virtual Synchronous Generator-Based Control Strategy and Pre-Synchronization Method for a Four-Leg Inverter under Unbalanced Loads

Virtual synchronous generator (VSG) control has positive effects on the stability of microgrids. In practical power systems, both single-phase loads and three-phase unbalanced loads are present. The four-leg inverter is an alternative solution for the power supply of unbalanced loads and grid connections. The traditional VSG control strategy still faces challenges when using a four-leg inverter to provide a symmetrical voltage and stable frequency in the load power supply and pre-synchronization. This paper proposes a VSG-based control strategy along with a pre-synchronization method for four-leg inverters. An improved VSG control strategy is put forward for four-leg inverters. The improved virtual impedance control and power calculation methods are integrated into the control loop to suppress the voltage asymmetry and frequency ripples. Building on the improved VSG control strategy, a pre-synchronization control approach is proposed to minimize the amplitude and phase angle discrepancies between the inverter output voltage and the power grid voltage. In addition, an optimized design method for control parameters is presented to improve VSG dynamic performance. A hardware prototype of the four-leg inverter is built; the results show that the voltage unbalance ratio can be reduced by 89%, and the response time can be shortened by 50%.

Nonlinear Enhanced Control for Wind Energy Generation System-Based Permanent Magnet Synchronous Generator

This paper proposes a Nonlinear Backstepping Approach (NBA) to improve the control performance of a Permanent Magnet Synchronous Generator (PMSG)-based Wind Energy Generation System (WEGS) under parameter uncertainties and short circuits with fluctuations in the grid voltage. Both the rectifier and the three-phase inverter are controlled using the NBA scheme; this method ensures Maximum Power Point Tracking (MPPT), which is a very appealing control objective with unpredictable scenarios of wind speed, and regulates the active and reactive power flows to the electrical network under varying wind speeds. Also, an inverter was employed to control voltage of the DC bus and the powers. The regulator’s stability is achieving using the Lyapunov approach. Simulation results with Matlab/Simulink confirm the efficiency of the presented scheme. The comparative analysis of the NBA with conventional Vector Controllers (VCs), under parameter deviations and for low voltage drop conditions, demonstrates the efficiency of the studied method.

DC-Link Voltage Fluctuation Suppression Method for Modular Multilevel Converter Based on Common-Mode Voltage and Circulating Current Coupling Injection under Unbalanced Grid Voltage

Grid voltage imbalance conditions often occur. Modular multilevel rectifiers (MMCs) have high DC-link voltage fluctuation under an unbalanced grid, which affects the normal operation of DC-side equipment. To suppress voltage fluctuation under an unbalanced grid, a coupling injection strategy composed of third zero-sequence common-mode voltage (TZCV) and secondary circulating current (SCC) was designed in this paper. In this paper, we calculated the coupling time-domain expression of the TZCV and SCC under an unbalanced grid voltage. Then, the influence of an SCC and TZCV coupling injection on DC-link voltage fluctuation was analyzed. The converter power flow of different system control objectives under an unbalanced grid was calculated, and the overall control method of the converter based on the arm current was proposed. The advantage of the method proposed in this paper is that it can realize online control under different grid voltages and input power conditions in real time and effectively suppress DC-link voltage fluctuation. The simulation was carried out on the MATLAB/Simulink platform, and a hardware-in-the-loop experimental platform was built; the results verify the effectiveness of the proposed strategy.

Reduced Order Generalized Integrator Based Modular Multilevel Converter Loop Current Suppression Strategy under Unbalanced Conditions in Distribution Networks

Under the condition of grid voltage imbalance, the circulation of the bridge arm inside the modular multilevel converter (MMC) increases significantly, which leads to the aggravation of the distortion of the bridge arm current, and, thus, increases the system loss and reduces the power quality. To address this problem, this paper analyzes the mechanism of circulating current generation and proposes a circulating current suppression strategy based on a reduced-order generalized integrator (ROGI), which firstly uses the ROGI system to separate the second-harmonic positive- and negative-sequence components in the circulating current from the DC, and then converts the rotating coordinates of the circulating current’s second octave component into the DC to be fed into the proportional–integral quasi-resonance (PIR) controller for suppression. A simulation model of a 23-level MMC inverter is built in MATLAB/Simulink, and the control strategy proposed in this paper is compared with the classical proportional–integral (PI) control in simulation experiments. The simulation results show that the amplitude of the circulating current fluctuation of the classical PI control is reduced from 90 A to 22 A, and the harmonic distortion rate of the bridge arm current is reduced from 32.56% to 5.57%; the amplitude of the circulating current fluctuation of the control strategy proposed in this paper is reduced from 90 A to 5.7 A, and the harmonic distortion rate of the bridge arm current is reduced from 20.2% to 1.13%, which verifies the effectiveness of the pro-posed control strategy.

Decentralized optimal voltage control for wind farm with deep learning-based data-driven modeling

The random fluctuations of wind energy and external grid voltage disturbances can both lead to serious voltage fluctuations and voltage deviations in the wind farm (WF). Voltage/reactive power control is an effective way to improve the voltage stability of WF. The existing research is based on complex physical models with prior parameter information, and the accuracy and calculation speed of the WF model are difficult to guarantee. To address this issue, this paper explores a decentralized optimal voltage control method for WF with deep learning-based (DL) data-driven modeling (DL-DOVC). A hybrid convolutional neural network (CNN)-Transformer architecture is proposed to establish the data-driven model of WF, leveraging its enhanced capabilities for extracting time series correlation, to learn complex patterns and dynamics from time series data. Then, we develop a fully decentralized voltage control method for WF to regulate the terminal bus voltage of wind turbines (WTs) within a feasible range. A DL-based data-driven predictive controller is specially designed to solve the established data-driven voltage optimization problem, it eliminates the necessity for frequent manual model maintenance and is suitable for real-time application. Additionally, the difficulty of WF decentralized optimal voltage control arises from the inability of local controllers to fully consider the impact of all non-local WTs on the local WT states. By designing the DL-based auxiliary state-feedback controller, the effects of non-local WTs are implicitly considered in the auxiliary feedback control law. A WF with 32*6.25 MW WTs is used to test the proposed DL-DOVC method. Simulation results show that the proposed DL-based model can efficiently learn and predict the WF dynamics under different operating scenarios. The near-global optimal voltage control performance is achieved only with local measurements by employing the DL-DOVC method.

Squirrel cage induction generator based micro grid voltage assessment with STATCOM using different metaheuristic approaches

Squirrel Cage Induction Generators are the most common machine to operate wind-based power plants. Microgrids are small-scale electrical systems that provide power to a local area, and optimization methods for microgrids aim to ensure that these systems operate in a way that is both efficient and cost-effective. In such applications, STATCOM is used as reactive power provider and It is necessary to use advanced controllers like the Genetic Algorithm (GA), Firefly Algorithm (FA), and Adaptive Neuro Fuzzy Inference System (ANFIS) as the usual approaches for setting gain factors of STATCOM controller which does not perform well in the case of sudden voltage level changes due to disturbances. The firefly algorithm is primarily required to estimate the gain factors of the STATCOM controller which is used in hybrid micro grid with SG and SCIG for controlling the output voltage in the occurrence of large probabilistic ambiguity. The effectiveness of firefly controlled STATCOM controller for voltage-reactive power control in hybrid microgrid is further examined and validated by comparing the results with other GA, ANN and ANFIS tuning techniques. The need for reactive power is accomplished by STATCOM to minimize the time required to control voltage transient response. The main contribution of this paper includes: an assessment of STATCOM performance with step variations in the input wind energy and reactive power load requirement under conditions of severe probabilistic uncertainty, system analyses conducted under dynamic conditions rather than using a composite load model. Additionally, a comparison of reactive power and voltage control by STATCOM is presented, and employing FA techniques to improve, a comparative of STATCOM reactive power and voltage control. Results comparing all tuning techniques shows that utilizing the Integral of Square of Errors (ISE) criterion, sophisticated tuning techniques can maintain excellent performances under a variety of disruptions.

Studying the Intelligent Power Distribution and Consumption of the Power Grid and its Cost Structure Using Big Data Analysis

Based on the analysis of big data, this paper studies the impact of user behavior response on the cost structure of the microgrid system in the power grid system. The article first conducts in-depth research on distributed power generation and energy storage systems, focusing on the principles and output characteristics of smart power distribution and utilization in power grids, researches smart power distribution and utilization systems in power grids, and makes a more comprehensive discussion of the current situation. Secondly, a big data analysis platform was built, and distributed storage and computing were studied. The platform was used to perform distributed storage and regulation of electricity consumption data, and the electricity consumption information data was divided into the important load, controllable load and transferable load, constructed a microgrid system model based on electricity consumption behavior response, and analyzed a calculation example. After that, a micro-grid system was simulated based on HOMER software, and the optimal capacity configuration of the system was performed. Under this configuration, the micro-grid system has the highest economic efficiency. At the same time, a demand-side load control system was built. Introduced distributed power as a controllable load, integrated new energy access and load control technology, coordinated the contradiction between the power grid and distributed power, and completed a cost-benefit analysis. Finally, for demand-side management electricity price response, peak-valley time-of-use price, the most important implementation method, according to the cost structure theory, the peak-valley period is divided according to the membership function in fuzzy mathematics, and the user's response model to peak-valley time-of-use price is established. The experiment uses the original data to simulate, find the user response model parameters based on the load transfer rate, and complete the comparative analysis of the effect under the peak-valley time-of-use electricity price, which is of great significance to the implementation and improvement of the peak-valley time-of-use electricity price project. The analysis results of the calculation examples show that the method constructed in this paper can effectively realize the power quality analysis of the distribution network in the big data environment. The research results provide technical support for the management of the rural grid voltage deviation of the power company, and lay the foundation for improving the safe operation and management of the power grid.

Real time implementation of scaled droop control in hybrid microgrid with hydrogen storage for regulation of voltage and frequency.

The incorporation of renewable energy resources (RERs) into smart city through hybrid microgrid (HMG) offers a sustainable solution for clean energy. The HMG architecture also involves linking the AC-microgrid and DC-microgrid through bidirectional interconnection converters (ICC). This HMG combines AC sources like wind-DFIG with DC sources such as solar PV and solid oxide fuel cell (SOFC), supported by battery energy storage systems (BESS) and hydrogen storage units (HSU). The HSU can generate and store hydrogen during RER surplus. This stored hydrogen can be further employed for production of electrical power along with numerous other applications. The HSU is emerged as a competent tool which can be utilised alone/in combination with BESS to enhance the system reliability. Harvesting power from clean and green sources requires its optimal operation and control while feeding to the existing grid. The existing strategies of controlling ICC are complex and not efficient; hence, a novel intelligent scaled droop control structure (SDCS) is proposed, utilizing frequency, DC voltage, and active power. The SDCS regulate voltage and frequency in both islanded mode (IM) and grid connected mode (GCM) of HMG. Experimental validation demonstrates its simplicity and effectiveness, making it suitable for smart city environments, ensuring uninterrupted power for critical loads with improved air quality.

Integration of Distributed Generations and electric vehicles in the distribution system

Power quality challenges are a major problem these days because of the significant increase in load demand and the existence of various reasons for disruptions in the distribution system. A voltage sag or a decrease in the magnitude of the line voltage can be brought on by rapid fluctuations in load or distribution system issues. Enhancing the grid current profile, reducing grid voltage sag, and improving other performances can all be achieved through the combination of electric vehicles with distribution generation systems. In this paper, the integration of Distributed Generation with Electric Vehicles in the distribution system has been done to enhance system performances such as true power loss index, imaginary power loss index, voltage deviation index, short circuit current index, cost function, and environmental impact reduction index for 16 bus distribution system in constant impedance, constant current, and constant power load models, or ZIP load models through proper location, sizing, coordinated controlling, and types of Distributed Generation and Electric Vehicle pairs for both charging and discharging modes by adopting Hybrid Genetic Algorithm - Monte Carlo Simulation optimization methodologies. This study's primary goal is to determine the optimal distribution generation and electric vehicle pairing to improve the aforementioned parameters, which will assist researchers in their future planning. Researchers, industry professionals, scientists, and individuals working with Distributed Generation and Electric vehicles in the smart grid will find this statement to be of great use.

Abnormal behavior of the plasma potential in an inductively coupled plasma with a DC-biased grid

Abstract The formation of the plasma potential and the generation mechanism of very low electron temperature plasma are investigated in an inductively coupled plasma with a DC biased grid. The electron temperature is controlled from 2.4 eV to 0.2 eV according to the grid voltage (10 V to −40 V). Interestingly, when the grid voltage is negatively biased, the electron temperature decreases and the plasma potential decreases with the grid voltage, but then increases below −10 V which is abnormal. This behavior of the plasma potential is abnormal since the plasma potential is generally proportional to the electron temperature. The main reason for the abnormal increase of the plasma potential is the difference in the flux of electrons and ions below the grid. As the grid is negatively biased, the electron flux is greatly reduced compared to the ion flux, leading to an increase in plasma potential. After −20 V, the plasma potential saturates, because although the number of electrons entering the grid decreases, the electron flux is maintained by secondary electrons generated in the grid mesh. This abnormal increase in plasma potential decreases with pressure. An increase in plasma potential with gas species is also observed. The same behavior is observed for Ar, He, and N2 gases. The abnormal behavior of the plasma potential is explained with the current continuity.

An Improved digital multi-resonant controller for 3 [formula omitted] grid-tied and standalone PV system under balanced and unbalanced conditions

With the exponential penetration of Photovoltaic (PV) plants into the power grid, advanced current controllers should be employed in grid-tied power converters in order to efficiently inject high quality current synchronized with the grid voltage. This research presents the modeling and design of a digital multi-resonant controller to feed-in high quality current. The novelty lies in designing the control in a superior manner to conventional techniques. As an outcome, practical engineers discover an easy, fast, robust, and accurate control method. The proposed 5-kVA PV system can inject active and reactive power effectively while staying resilient to imbalance scenarios. Synchronization is accomplished via a synchronous reference frame (SRF) based phase locked loop (PLL) that performs effectively even with distorted and nonideal grids. The practicality and efficacy of the developed controller is verified both in simulation (PSIM and code composer studio) and Hardware in Loop (HIL) via Typhoon 402 and TMS32F28335 experiments. The devised controller is evaluated in both grid-connected and standalone modes under a wide range of disturbances, distortions, and non-ideal conditions. The simulation and HIL results validate the robustness, fastness, resilience, and effectiveness of the proposed controller compared with a well-tuned conventional proportional resonant (PR) controller.