Voltage Control Method Research Articles

Modelling and implementation of a photovoltaic system through improved voltage control mechanism

Renewable energy dependence is increasing daily due to the decaying of conventional energy sources. Another primary reason is the increment of pollution as well as global warming. Various alternate energy sources are being used to replace conventional ones. Among them, the prominent photovoltaic source provides clean and green energy. This research focuses on energy production through the photovoltaic source. The photovoltaic cells combination is used along with the boost converter to get the maximal power output. The maximum power point tracker was designed and implemented to obtain the optimal power from the photovoltaic cells, which do not provide the desired results. Therefore, the voltage control method is an alternative to the maximum power point tracker. Both methodologies compared at different intensities of solar light. The load is attached to the photovoltaic output to test its reliability and smooth performance. The system is designed using MATLAB simulation, and the desired results are obtained.

A Large-Scale Multi-Agent Deep Reinforcement Learning Method for Cooperative Output Voltage Control of PEMFCs

To increase the output voltage stability and improve the operating efficiency of proton exchange membrane fuel cells (PEMFCs), a data-driven cooperative method for controlling the PEMFC output voltage is proposed in this paper. The proposed method adapts centralized learning and decentralized implementation, which can nonlinearly and adaptively realize optimal coordinated control over the hydrogen valve and the DC/DC converter. Additionally, a champion multiagent double delay deep deterministic policy gradient (CMA-4DPG) algorithm is proposed in this method, the design of which incorporates the policies of the champion selection mechanism, cooperative exploration, imitation learning guidance and curriculum guidance to improve the robustness of the cooperative method. The method cooperates with multiple controller to prevent output voltage fluctuation. The experimental results show that by simultaneously regulating the hydrogen flow through the hydrogen valve and the duty ratio of the DC/DC converter, the proposed method achieves better robustness and can improve the tracking performance of the PEMFC output voltage.

Low voltage ride through control strategy of permanent magnet wind turbine based on improved virtual synchronous generator control

Aiming at the shortcomings of traditional low voltage control strategies for permanent magnet wind turbines in supporting microgrid stability and the inability of traditional virtual synchronous generator (VSG) control to ride through voltage drops, this paper proposes an improved control low voltage ride through (LVRT) strategy based on traditional low voltage control and VSG control methods. This strategy switches to reactive priority mode during the LVRT period, enabling VSG control to have LVRT function and meet the LVRT requirements standards. The simulation results demonstrate the effectiveness of the strategy.

Power electronics applied to voltage control in rural distribution networks with penetration of distributed generation

In rural distribution networks with widely dispersed loads, characterized by the utilization of long overhead lines, voltage profiles with big variations appear along the line due to the significant variations of the load between peak hours and valley hours. This paper describes the problems that the integration of distributed generation based on renewable resources could generate in that scenario, and presents solutions that are commonly used to mitigate these problems and proposes new solutions to solve them. The integration of distributed generation (DG) based on renewable resources in these networks increases the variability of the voltage, and in some cases the power flow of the network also can be bidirectional. Usually this integration of distributed generation is limited by the network operator limiting the maximum voltage variation produced by the distributed generation in the point of common coupling (PCC). In this paper different traditional methods for voltage control are described and analyzed for a widely dispersed rural network scenario. The impact of the DG in these methods of voltage control and the advantages of power electronics in this new scenario are exposed. Power Electronic devices applied to these distribution networks allow more efficient management of the network increasing the integration of distributed generation maintaining the security levels.

Fuel cell stack design and modelling with a double-stage boost converter coupled to a single-phase inverter

Abstract A comprehensive proton-exchange membrane fuel cell stack model was developed and integrated with a two-stage DC/DC boost converter. It was directly coupled to a single-phase (two levels—four pulses) inverter without a transformer. The pulse-width modulation signal was used to independently regulate every converter phase. The converter was modelled using a MATLAB®/Simulink® environment and an appropriate voltage control method. The analysis features of the suggested circuit were created and, through established experiments, the simulation results were verified. A single-phase (two levels—four pulses) inverter control circuit was tested and it produced a pure sinusoidal waveform with voltage control. It matches the voltage of the network in terms of amplitude and frequency. A sinusoidal pulse-width modulation approach was performed using a single-phase (two levels—four pulses) pulse-width modulation inverter. The results demonstrated an enhancement in the standard of the output wave and tuned the dead time with a reduction of 63 µs compared with 180 µs in conventional techniques.

Single-Phase nine-level inverter for photovoltaic application

Electrical power play a very important rule in 21th century, but non-conventional sources scale down day by day. Not only that concern for the environmental pollution around the world, so now a day’s photovoltaic (PV) power systems are getting more and more widespread with the increase in the energy demand. This paper proposed a Single-Phase nine level inverter with voltage control method using semi conductor power devices for photovoltaic systems. The proposed inverter system gives better voltage regulation, smooth results and efficiency compared to multi-level inverters. The inverter is capable of producing nine levels of output voltage levels (Vpv, 3Vpv/4,Vpv/2, Vpv/4, 0, -Vpv/4, -Vpv/2, -3Vpv/4, -Vpv). The proposed inverter was verified by using simulation of Matlab / Simulink software.

A Centralized Shifted Voltage Control Method for Accurate Power Sharing in DC Islanded Microgrids

Due to line impedance mismatch among renewable energy sources (RESs), it is hard to realize accurate power sharing in the DC microgrid system. To solve this issue, a distributed power sharing strategy for adjusting the RES output voltage is developed by adding shifted output voltage into each local controller. Thanks to the shifted voltage, the influence of voltage drop caused by the droop controller is effectively mitigated, so that the DC bus voltage is constantly balanced regardless of the load changes. The proposed method is realized with a centralized approach, and all the required control variable to determine the reference voltage is transmitted through low-bandwidth communication. The controller design and system stability are analyzed in detail with a simplified microgrid model. Small-scale DC microgrid is simulated to verify the effectiveness of the centralized shifted voltage control method.

A Communication-Free Fast Constant Current and Voltage Control Method for Dynamic Wireless Power Transfer System

A Communication-Free Fast Constant Current and Voltage Control Method for Dynamic Wireless Power Transfer System

Voltage control method for multi-energy system based on the coupling of renewable energy hydrogen production and storage

Renewable energy power generation combined with hydrogen storage, is an important way to realize the deep integration of hydrogen energy and renewable energy in multi-energy systems. In the multi-energy system of renewable energy power generation and hydrogen production in AC/DC hybrid. Due to the fluctuation of heat load and electric hydrogen production load in the system and the multi-time scale characteristics of energy flow transmission of heat storage and hydrogen storage. It will lead to the difficulty of power coordination in the whole Multi Energy System (MES). In order to solve the problem of power imbalance in MES, this paper first establishes the hybrid power flow equation of MES cluster composed of AC/DC and hydrogen energy transmission channels. The reactive voltage fluctuation characteristics of the AC/DC system under the fluctuation of energy exchange, system energy conversion, and renewable energy output of the MES cluster interconnection channel are analyzed. Secondly, a multi-energy flow model of the multi-energy system is established. The main factors affecting the voltage-reactive power of the AC system are analyzed. A reactive power model based on electro-thermal conversion, hydrogen storage, and multi-energy transmission channels is established. Then, a generation algorithm of the safe and stable boundary of pipeline pressure is proposed to maintain the pressure of hydrogen production and storage system within a safe range. The robust optimization control method is used to control the coupling of multi-energy sources. Finally, based on the actual operation data of the multi-energy power system. The simulation model of reactive power dynamic optimization control for multi-energy interconnected systems is established. The simulation results show that the control method proposed in this paper is adopted. Through the coordinated distribution of energy among multi-energy systems, the voltage stability level of the system can be effectively improved.

Трехуровневый алгоритм управления напряжением в распределенных электрических сетях с солнечными фотоэлектрическими системами

Modern energy systems are increasingly integrating renewable energy sources, presenting new challenges for voltage regulation. This study aims to model the voltage regulation process in the context of distributed electrical grids equipped with solar photovoltaic systems. A three-tier voltage control algorithm is proposed, which analyzes and integrates data on solar generation, suggests optimal actions for managing energy storage systems, calculates voltage levels, and recommends measures for controlling inverter reactive power to effectively mitigate voltage fluctuations. The study employs methods of mathematical averaging of time series and optimization based on the analysis of real data. The algorithm's performance is evaluated using an open dataset of solar energy generation. The results show a significant improvement in voltage regulation metrics, conforming to the standards established by GOST 32144-2013. This validates the effectiveness of the proposed voltage control method in electrical grids incorporating solar photovoltaic systems.

Physics-Informed Graphical Representation-Enabled Deep Reinforcement Learning for Robust Distribution System Voltage Control

The anomalous measurements and inaccurate distribution system physical models cause huge challenges for distribution system optimization. This paper proposes a robust voltage control method that can deal with them by systematically integrating a representation network, the deep reinforcement learning (DRL) method, and the surrogate model. The partial observation of the distribution network is first represented as a graph with tree topology that is processed by a physics-informed global graph attention network (GGAT) and a deep auto-encoder (DAE) to achieve informative and robust representation of the real-time and pseudo-measurements. The extracted features are then fed into the soft actor-critic algorithm, during the training of which a graphical-learning-based power flow surrogate model is developed to provide a reward signal for the DRL algorithm. This allows the proposed method to reduce reliance on accurate distribution system parameters. The embedding of the structural information by the GGAT and the informative features extracted by the DAE further enhances the robustness of the proposed method against anomalous measurements. The proposed method is validated using IEEE 33-node and 119-node systems. Simulation results show the robustness of the proposed method against anomalous measurements.

OPTIMAL COORDINATED VOLTAGE CONTROL OF ELECTRICAL DISTRIBUTION NETWORKS IN THE PRESENCE OF DISTRIBUTED RENEWABLE ENERGY SOURCES

Recently, distributed generation (DG), as clean and renewable energy, has increased due to the global warming problems and depletion of fossil sources. Several DGs are installed near the end-user, with the feature that this will decrease power losses. However, without optimal control, many problems, such as voltage instability and power losses, may affect the performance and the good operation of the power system. This paper proposes an optimal coordinated voltage control (OCVC) method for the distribution networks with distributed generation sources. The method is based on a genetic algorithm (GA) approach in multi-core simulation with an open-source OpenDSS to obtain the optimal setting of voltage control devices adjusted remotely. This method takes into account time-varying load and generation based on day-ahead scheduling. To validate the performances of the proposed technique, simulations are performed in a distribution network test with DG integration.

A voltage control method for distribution networks based on TCN and MPGA under cloud edge collaborative architecture

A distribution network voltage control method based on TCN and MPGA under cloud edge collaborative architecture is proposed to address the issues of heavy computational burden and inability to balance economic efficiency in traditional decentralized and centralized voltage control methods. Firstly, under the cloud edge collaboration architecture, the power prediction model based on time convolutional networks is trained in the cloud, and the edge predicts the load demand and new energy active output in each region based on the TCN Attention power prediction model issued by the cloud. Then, considering safety and economy comprehensively, with the goal of minimizing the daily network loss and voltage regulation cost in the distribution network, the Pareto solution set for the optimal operation point of each voltage regulation equipment in the entire distribution network was solved based on an improved multi population genetic algorithm at the distribution cloud main station. Finally, the optimal distribution network voltage control scheme is obtained based on the Pareto solution set. Based on the simulation system, experimental testing was conducted on the proposed method, and the results showed that its daily voltage regulation cost and network loss were 863.4 yuan and 43.73 MW h, respectively. The average absolute percentage error of the prediction model was 4.51 %, which was superior to other comparative methods.

Switched-Capacitor-Based Hybrid Clamped Converter for Wide Power Factor Applications

The clamped multilevel converter generally adopts the zero-sequence voltage injection method to realize the voltage balancing of the DC link capacitors. However, the relationship between the reference modulation voltage and the duty ratio of phase neutral point current is often a triangle or trapezoidal function. When the power factor is low, the required optimal zero-sequence voltage will be out of bounds, which will lead the capacitor voltage ripples to become larger or even divergent. Therefore, a novel switched-capacitor-based hybrid clamped(SCB-HC) converter is proposed in this article. The new redundant switching states are obtained by introducing the boost characteristics of the switched-capacitor(SC) circuit. And a hybrid phase-shifted pulse width modulation(PS-PWM) is developed to extend its functional relationship. This ensures the peak current that flow out of the neutral points is fewer, then the capacitor voltage drift is reduced significantly. Moreover, the proposed hybrid PS-PWM method not only ensures that SC circuit switches series and parallel patter once during a carrier period, but also achieves the voltage balancing of SC and DC link midpoint capacitor naturally under ideal conditions. On top of that, the capacitor voltage balancing method is designed to ensure independent and decoupled control of all capacitor voltages. Simulations and experiments show that the proposed topology, modulation method and voltage control method are practical and feasible for wide power factor applications.

Physics-Informed Multi-Agent deep reinforcement learning enabled distributed voltage control for active distribution network using PV inverters

With the recent rapid uptake of photovoltaic (PV) resources, the overvoltage condition during low load periods or intermittent renewable generation is one of the most critical challenges for electricity distribution networks. Traditional model-based local or centralized control methods that rely on proper system parameters are difficult to mitigate rapid changes in power systems. Utilizing model-free/data-driven multiagent deep reinforcement learning (MADRL) has been recognized as an effective solution to active voltage control. However, existing MADRL-based control approaches trained solely on data are agnostic to the underlying real-world physics principles. Therefore, this paper aims to incorporate physical knowledge of regional distribution networks into MADRL’s decision-making. The main contributions of this paper are summarized as follows. First, a novel physics-informed MADRL -based distributed voltage control method is proposed, which is still under a centralized training and distributed execution framework and only requires local measurements. Second, graph neural networks are employed to help MADRL agents learn graph knowledge (node features and topological information). Further, transformer is introduced to extract discriminative representations and ensure agents’ cooperative control. Third, we adopt a physics-guided architecture of neural networks in the actor network to stabilize the training process and improve sample efficiency. Finally, simulation results based upon modified IEEE 33-bus and 141-bus networks validate the proposed method's effectiveness, robustness and computation efficiency.

Design of fuzzy sliding mode controller for islanded AC/DC hybrid microgrid with cyber‐attacks

AbstractThis paper presents a fuzzy sliding mode control method for voltage control of islanded AC/DC hybrid microgrid. The T‐S fuzzy model is utilized to approximate initial non‐linear dynamic model of the microgrid. The fuzzy rules and membership functions are designed according to the coupling relationship between AC part and DC part. To reduce the influence of external disturbance and cyber‐attacks, an integral sliding mode controller is considered. Furthermore, a sufficient condition is proposed with attenuation performance to ensure the asymptotic stability of sliding motion. The set of gain matrices can be acquired via solving the linear matrix inequalities deduced from the Lyapunov stability analysis. The reachability to the proposed sliding mode surface can be guaranteed via switching control law based on a Lyapunov function. In addition, to eliminate chattering performance of the sliding mode control theory, the fuzzy logic controller is designed to optimize the switching region in boundary layers of saturation functions. Finally, the simulation results for the islanded AC/DC hybrid microgrid are implemented to verify the robustness and effectiveness of the designed fuzzy sliding mode control method.

Simulation and enhancement of axial temperature distribution in a reactor filled with in-situ electrically heated structured catalyst

The hydrogen production technology based on the in-situ electrically heated structured catalyst (EHSC) has the advantages of compact structure, fast response, and less CO2 emissions. However, there is still a lack of research on the temperature distribution of the reactor filled with EHSC. Based on the problem, a CFD model was established, and the temperature distribution was revealed. To further reduce the large temperature difference in axial direction, the effects of the gradient-pitch design and segmented-voltage-control design for the EHSC on the temperature distribution and methanol conversion were studied numerically. The results showed that segmented-voltage-control design can significantly reduce the maximum axial temperature difference, due to the fact that the reaction heat and corresponding Joule heat supplied at each axial section were flexibly well matched. When reaction temperature was 275 °C, the maximum temperature difference decreased from 84.7 °C to 31.1 °C. Moreover, when GHSV was 13000 ml/(g h), methanol conversion was improved by up to 10.9%. The segmented voltage control method for the EHSC provides an opportunity to design an isothermal endothermic reactor under any reaction conditions in the case of further optimization of segmented-voltage-control design.

Selected voltage control methods in LV local distribution grids with high penetration of PV

Selected voltage control methods in LV local distribution grids with high penetration of PV

Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm

Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm

A new distributed voltage control method for MVDC electric railway systems with renewable energy sources

The medium voltage DC (MVDC) electric railway system is one of the most interesting options for future high-speed rail (HSR) lines. The dc voltage control is one of the most critical challenges of MVDC electric railway systems due to various reasons such as simultaneous, continuous and considerable changes in the power and location of trains, regenerative brake energy of trains, long power lines, the application of ESS’s and RES’s. In this paper, a voltage control, i.e., the optimal-voltage voltage-power (OVVP) control method, is presented for MVDC electric railway systems. OVVP control method is a practical, reliable, automatic, and modular distributed voltage control method. The proposed voltage control method satisfies the nearest voltage to the nominal value in each node and the smoothest voltage profile in different MVDC electric railway systems. Although the analyses carried out in this paper analytically prove the significant performance of the presented voltage control method, different challenging scenarios are considered to verify OVVP control method more. In addition, the results of the proposed voltage control method are successfully validated by GAMS software.