Voltage Control Method Research Articles

DEVELOPMENT OF A LITHIUM-ION BATTERY CHARGING SYSTEM UNDER CONSTANT CURRENT AND VOLTAGE CONDITIONS USING STM-32 BASED ON FUZZY LOGIC CONTROL

Lithium-ion batteries are electrical energy storage devices often found in portable electronic equipment. Overcharging and discharging the battery will reduce its life and cause severe damage. Constant current and voltage control methods and control algorithms, such as fuzzy logic control, need to be added to avoid this. This research aims to develop a lithium-ion battery charging system using a constant current and voltage method based on fuzzy logic control. A constant current-constant voltage (cc-cv) charging system helps control the charging voltage and current by conditioning the initial charging to use a constant current so as not to overcharge. Constant current uses a buck converter circuit, while constant voltage uses a voltage regulator circuit. The charging system is equipped with a voltage sensor and a current sensor. System control uses fuzzy logic control methods with input variables as errors and delta errors while the output is a duty cycle. The overall system design was carried out at the Measurement, Reliability, Risk, and Safety Laboratory, ITS for 4 months. The test results show that charging the battery produces a voltage of 12.6 Volts and a current of 2.5 Amperes. The battery will be fully charged, and the charging system will stop when the flowing current decreases and the current is cut off at 100 mA.

A Decentralized Demanded Power Tracking and Voltage Control Method for Wind Farms Based on Data-Driven Sensitivities

A Decentralized Demanded Power Tracking and Voltage Control Method for Wind Farms Based on Data-Driven Sensitivities

Adaptive Approach for Power Oscillation Damping using STATCOM

In this paper we had described the designing of a Power Oscillation Damping (POD) controller for a Static Synchronous Compensator (STATCOM) equipped with Energy Storage System (ESS). Various adaptive techniques like fuzzy logic controller, PID controller, algorithm, etc. can be employed to achieve this allowing a fast and adaptive approximation of the low-frequency electromechanical oscillations from locally measured signals during power system disturbances. We developed an approach using variable DC voltage control and constant modulation index method; which are effective in increasing the damping of the system at the concerned frequencies and in case of system parameter uncertainties. A control policy that optimizes active and reactive power inoculation at various connection points of the STATCOM is derived using the simplified model in MATLAB Simulink using impower system toolbox. Signal analysis of the dynamic performance of the proposed control strategy is carried out. To verify the effectiveness of the proposed control method, we carried out simulations and found that the approach provides oscillation damping irrespective of the connection point of the device and also in the presence of system parameter uncertainties.

Neutral-point voltage control method of multi-phase three-level neutral-point clamped H-bridge inverters based on space vector modulation

Neutral-point voltage control method of multi-phase three-level neutral-point clamped H-bridge inverters based on space vector modulation

Modeling and Active Vibration Control of Flexible Robotic Arm and Its Application in Agricultural Water Conservancy Field

In order to improve the modeling and active vibration control effectiveness of flexible manipulators, this paper combines big data technology to study the modeling and active control of flexible manipulators. In addition, this article decouples the dynamic model of the flexible joint manipulator based on voltage control method, redefines the control input of the system as the voltage of the joint motor, and uses a nonlinear state observer to control the flexible link manipulator. The control strategy proposed in this article is based on a nonlinear state observer, combined with input-output control, to achieve tracking of joint angular displacement in a flexible linkage manipulator. Through experimental research, it can be seen that the big data based modeling and active vibration control research system for flexible robotic arms proposed in this paper can effectively improve the motion control effect of flexible robotic arms.

A zoning-based distributed control method for medium-low voltage AC/DC distribution networks

Abstract With the increasing percentage of renewable energy sources and new types of power equipment, the medium-low voltage AC/DC distribution network structure improves the source-load carrying capacity and is considered a prevailing trend. Traditional centralized voltage optimization and control methods face challenges due to computational inefficiencies arising from the numerous control devices involved. In this paper, a distributed optimal control strategy based on distribution network zoning is proposed. Firstly, a network decoupling and multi-agent deployment method based on zoning is introduced. Secondly, a distributed optimal control model for medium-low voltage AC/DC distribution networks is developed to minimize network losses within the region. Subsequently, the optimization model is transformed into a Markov process, and the multi-agent proximal policy optimization (MAPPO) algorithm is used to solve this Markov process, facilitating the distributed control of medium-low voltage AC/DC distribution network based on zoning. Simulation examples are analyzed to prove the effectiveness of the proposed method.

Multi-Agent Deep Reinforcement Learning-Based Distributed Voltage Control of Flexible Distribution Networks with Soft Open Points

The increasing number of distributed generators (DGs) leads to the frequent occurrence of voltage violations in distribution networks. The soft open point (SOP) can adjust the transmission power between feeders, leading to the evolution of traditional distribution networks into flexible distribution networks (FDN). The problem of voltage violations can be effectively tackled with the flexible control of SOPs. However, the centralized control method for SOP may make it difficult to achieve real-time control due to the limitations of communication. In this paper, a distributed voltage control method is proposed for FDN with SOPs based on the multi-agent deep reinforcement learning (MADRL) method. Firstly, a distributed voltage control framework is proposed, in which the updating algorithm of the intelligent agent of MADRL is expounded considering experience sharing. Then, a Markov decision process for multi-area SOP coordinated voltage control is proposed, where the control areas are divided based on electrical distance. Finally, an IEEE 33-node test system and a practical system in Taiwan are used to verify the effectiveness of the proposed method. It shows that the proposed multi-area SOP coordinated control method can achieve real-time control while ensuring a better control effect.

Multi-physics Analysis of Interior Permanent Magnet Synchronous Motor with Torque Ripple Reduction Using Voltage Control Method

Multi-physics Analysis of Interior Permanent Magnet Synchronous Motor with Torque Ripple Reduction Using Voltage Control Method

Real-time voltage control of centralized and distributed coordination in active distribution network under multiple coupling

Abstract At present, the “source-load interaction” distribution network operation mode has gradually replaced the “source-load operation” mode. The uncertainty and volatility of the distribution system have been enhanced, the controllability has been weakened, the voltage fluctuations have been frequent, and the power quality has been decreased. Voltage regulation is crucial to fully absorbing new energy generation and improving the operation safety of the active distribution network. To solve the problem of real-time control of distribution networks, this paper proposes a distributed voltage control method of active distribution networks with global sensitivity, establishes a distributed communication mechanism, and builds a distributed forward push-back communication rule to transfer power and voltage information between nodes. The global sensitivity of voltage, active power, and reactive power is used for real-time, independent, and effective control of multiple devices at each node, and the distributed control process is simulated according to actual production conditions. Furthermore, the centralized and decentralized real-time voltage control methods are proposed, and the centralized and distributed methods are implemented in medium voltage primary distribution network (MVPN) and low voltage secondary distribution network (LVSN), respectively, to play the advantages of high computing efficiency and fast control response. Based on model predictive control (MPC), intra-day rolling time scale voltage regulation is constructed, and second-level control is used to adapt the MPC results, finally promoting the optimal scheduling and rapid response of various controllable flexible resources in the multi-level active distribution network.

Short-term high-efficiency decision-making method for tertiary voltage control considering short-term power fluctuations

Abstract With the continuous increase in grid-connected new energy sources and new types of intermittent loads, the short-term fluctuation amplitude of source-load power is continuously increasing, which increasingly affects the effectiveness of tertiary voltage control decisions. To address this issue, this paper proposes a short-term efficient decision-making method for tertiary voltage control considering short-term power fluctuations. Firstly, the decision-making cycle of tertiary voltage control is shortened, effectively enhancing its adaptability to short-term source-load power fluctuations. Secondly, to address the computational burden brought by the shortened decision cycle, this paper fully considers the temporal characteristics of short-term load fluctuations in practical power grid nodes and proposes two linearization methods for tertiary voltage control. Specifically, these methods include a three-point linear estimation method for small fluctuation periods and a sensitivity linearization optimization method for large fluctuation periods. By shortening the decision cycle and linearizing decision calculations, the efficiency of tertiary voltage control decision-making is greatly improved. Based on actual data from a provincial-level power grid in the northwest region of China, the effectiveness of the proposed methods is verified through simulation analysis.

Operator-Based Triboelectric Nanogenerator Power Management and Output Voltage Control.

In this paper, an operator-based voltage control method for TENGs is investigated, achieving output voltage tracking without compensators and uncertainty suppression using robust right coprime factorization. Initially, a comprehensive simulation-capable circuit model for TENGs is developed, integrating their open-circuit voltage and variable capacitance characteristics. This model is implemented to simulate the behavior of TENGs with a rectifier bridge and capacitive load. To address the high-voltage, low-current pulsating nature of TENG outputs, a storage capacitor switching model is designed to effectively transfer the pulsating energy. This switching model is directly connected to a buck converter and operates under a unified control strategy. A complete TENG power management system was established based on this model, incorporating an operator theory-based control strategy. This strategy ensures steady output voltage under varying load conditions without using compensators, thereby reducing disturbances. Simulation results validate the feasibility of the proposed TENG system and the efficacy of the control strategy, providing a robust framework for optimizing TENG energy harvesting and management systems with significant potential for practical applications.

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.

Practical Method for Voltage Control in Active Distribution Network Based on Sensitivity

Abstract The access of a large number of distributed photovoltaic power stations makes the voltage problem of the distribution network more prominent, but also provides controllable resources for the distribution network. In order to exploit the regulation potential of distributed photovoltaic power stations in active distribution networks, a practical method for voltage control based on sensitivity is proposed. The adjustment nodes and adjustment amounts are determined according to sensitivity. Based on the power flow equation, the voltage sensitivity calculation is appropriately simplified to reduce the amount of calculation. By combining forecast data and network topology, a control architecture for parallel calculation of sensitivity analysis, reactive power regulation capacity analysis, and real-time voltage control is proposed. This architecture decouples sensitivity calculation from real-time regulation and control, improving the processing speed and reliability of real-time voltage regulation and control. A case study based on a 10kV distribution network in a certain area shows that although the proposed sensitivity calculation method has some deviation, it can meet the requirements of engineering practicality and effectively achieve voltage over-limit control.

Comparative Study of Voltage Control Methods in Power Flow Analysis

Comparative Study of Voltage Control Methods in Power Flow Analysis

Evaluation of the energy saving potential in electric motors applying a load-based voltage control method

This paper studies the viability of energy savings in electric motors by adjusting the voltage according to load in motors that operate under significant load variations during their work cycles. The laboratory test program used a 1.1 kW electric motor to compare its measured efficiency operating without voltage control with the load-based voltage control method results. A neural network was developed, and a time series generator was used to model the motor and estimate the results of applying the method in its useful life in the load behavior of three operating regimes. The results show an energy saving potential of 2 %–5.2 % using the load-based voltage control method in motors operating with a load factor of less than 40 % during the simulated motor life cycle for the three operating regimes. Also, the economic feasibility of implementing the load-based voltage control method was evaluated on three industrial electric motors. Results indicated potential annual savings between $1227 and USD 1,549, with a projected investment payback period of less than three and a half years.

An Improved Voltage Control Method for EAST Fast Control Power Supply

The Experimental Advanced Superconducting Tokamak (EAST) fast control power supply (FCPS) is an important device for controlling the vertical displacement of plasma during the nuclear fusion power generation process, adopting a multiple H-bridge invertor branch parallel operation structure to output total current. At the beginning of each shot of plasma discharge, FCPS works in open-loop voltage control mode (VCM) or closed-loop current control mode (CCM) determined by the plasma control system to output current for exciting the load coil, to achieve plasma vertical displacement control. VCM has the characteristics of fast dynamic response speed but poor consistency of branch current and insufficient branch current control accuracy and stability because of open-loop control. CCM has the characteristics of high branch current control accuracy but poor dynamic response and robustness because of control delay and control parameters determined based on engineering experience. To achieve fast and robust control, an improved voltage control method (IVCM) is proposed by combining the advantages of VCM and CCM. In the beginning of establishing the output current, FCPS operates in VCM, and rapid establishment of the output current is ensured. After the output current rapidly increases to the critical value, closed-loop current control is added to VCM to ensure the accuracy of output current control. In closed-loop current control, linear super-twisting sliding mode control is designed to achieve fast and robust control, ensuring good consistency and fast dynamic response performance of each branch current. Simulations and experiments verify that the designed IVCM has better compatibility characteristics in output current stability, control accuracy, and consistency of each branch current compared to VCM.

An Enhanced Voltage Control Method for Fair Active Power Curtailment of Rooftop PV Systems in LV Distribution Networks

Solutions based on active power curtailment (APC) of photovoltaic inverters (PVIs) have been effectively used to alleviate overvoltages in low-voltage distribution networks (LVDNs) due to real power injection supplied by rooftop photovoltaic (PV) systems. However, volt–watt control methods presently available can lead to unfair APC among the PVIs, penalizing financially customers located far away from the distribution transformer of the LVDN. This paper proposes an innovative real-time voltage control method to address the unfair APC issue in LVDNs with rooftop PV systems. The proposed method is based on a centralized control architecture to calculate two fair curtailment factors for all PVIs of the LVDN. Additionally, to explore the extended communication infrastructure brought by centralized control architecture, this paper proposes a novel simplified method to compute the voltage sensitivity matrix (VSM) for applications on unbalanced three-phase LVDNs. Performance tests were conducted on a set of LVDNs, evaluating the effectiveness and fairness of APC quantitatively using Jain’s Fairness Index (JFI) as a metric. The results confirmed the effectiveness of the proposed control method for mitigating the overvoltage issue, ensuring fairness by presenting average JFI values close to one (the maximum allowed value). Furthermore, in comparison to conventional VWC strategies, penalties arising from the local dependence of PVIs on APC were eliminated for both curtailment factors. Finally, an accuracy test was performed on the proposed VSM model, based on voltage estimation through the linearized model of LVDN at a specific operating point. The findings demonstrated outstanding accuracy, with an error of less than 0.2%, compared to voltage estimation via power flow.

Low-voltage and high-penetration distributed photovoltaic access control technology based on intelligent measurement

Abstract This project takes high-penetration distributed photovoltaic access as the background and studies the control method for low voltage and high penetration distributed photovoltaic access. Firstly, by analyzing the measured data of the low-voltage distribution network, the daily load and measured values of the low-voltage distribution network were obtained. On this basis, the topology structure of a high-penetration distributed photovoltaic grid-connected system is studied, and the voltage, current, power, and other parameters of the grid-connected system are obtained. A low-voltage and high-penetration distributed photovoltaic grid-connected control method based on a genetic algorithm is adopted. Experiments have shown that the maximum allowable capacity of this scheme is smaller than the standard value and can effectively suppress voltage fluctuations. The experimental results show that the system has good grid connection performance, which is of great significance for improving the operational stability and efficiency of low-voltage distribution systems.

Centralized and decentralized combined voltage control for distribution network with high penetration PV connected

With the high penetration of distributed photovoltaics (DPVs) integrated into the distribution network, the voltage problem becomes a critical problem. At present, the resources in the current distribution network hardly satisfy the requirements of voltage regulation. However, the huge amount of DPVs in the distribution network could be a potential voltage regulation resource due to the controllable active power and reactive power. In this paper, a day-ahead centralized and intraday decentralized combined voltage control method is proposed for high penetration DPVs connected distribution Networks. In the part of day-ahead control, centralized compensation of the distribution network voltage is achieved by controlling the gear ratio of the capacitor/reactor group on an hourly scale. The intraday control part consists of decentralized local control based on DPVs and centralized control based on energy storage (ES) equipment. The reactive and active power of DPVs is controlled in a decentralized way by using local priority sensitivity control based on the coordination with capacitor optimization. Finally, simulations are performed to verify the performance of the method. The results indicate that this method can effectively solve the voltage problem caused by DPVs.

Probabilistic photovoltaic generation and load demand uncertainties modelling for active distribution networks hosting capacity calculations

With the increasing integration of photovoltaic (PV) systems in active distribution networks (ADNs), accurate modelling of PV power generation and the network demand has become essential, especially for system operators (SO). However, existing studies have focused on deterministic representations of hourly profiles for PV generation and load consumption, which cannot thoroughly evaluate the existing uncertainties of PV power output and load demands. In this study, uncertain parameters load demand and PV power output profile will be modelled with forecasted values, and their profile will be obtained over probability density functions (PDFs). Firstly, a vast quantity of realistic load and PV generation profiles are produced over a day with 15-minute resolution, with a scenario generation method using the Monte Carlo methodology. Afterward, the generated scenarios are reduced to a set of scenarios to represent the span of all generated scenarios. A fully local reactive power regulation strategy is used in this study to evaluate the hosting capacity of the ADN. This proposed method is tested on modified 33-bus and 69-bus distribution test systems by using practical solar generation and load data. The proposed methodology results in the hosting capacity improvement by 20% besides the existing Q-Voltage and PF-Power local voltage control methods, where it has the flexibility to be implemented to any distribution feeder.