Traditional Voltage Control Research Articles

Graph-Based Topological Embedding and Deep Reinforcement Learning for Autonomous Voltage Control in Power System

With increasing power system complexity and distributed energy penetration, traditional voltage control methods struggle with dynamic changes and complex conditions. While existing deep reinforcement learning (DRL) methods have advanced grid control, challenges persist in leveraging topological features and ensuring computational efficiency. To address these issues, this paper proposes a DRL method combining Graph Convolutional Networks (GCNs) and soft actor-critic (SAC) for voltage control through load shedding. The method uses GCNs to extract higher-order topological features of the power grid, enhancing the state representation capability, while the SAC optimizes the load shedding strategy in continuous action space, dynamically adjusting the control scheme to balance load shedding costs and voltage stability. Results from the simulation of the IEEE 39-bus system indicate that the proposed method significantly reduces the amount of load shedding, improves voltage recovery levels, and demonstrates strong control performance and robustness when dealing with complex disturbances and topological changes. This study provides an innovative solution to voltage control problems in smart grids.

Virtual inertia extraction from a DC bus capacitor in a three−phase DC/AC inverter-based microgrid with seamless synchronisation operation modes

Virtual inertia extraction from a DC bus capacitor in a three−phase DC/AC inverter-based microgrid with seamless synchronisation operation modes

Research on reactive power voltage control strategy of distribution network based on information sharing technology

Abstract In view of the fact that the traditional voltage control of the distribution network is suitable for local voltage control and affects the economy of the operation of the distribution network, a reactive power voltage control strategy of the distribution network based on information-sharing technology is proposed. First, the overall architecture of voltage control in the distribution network based on information-sharing technology is analyzed, and secondly, an algorithm based on the Jacobian sensitivity matrix is established with the minimum voltage RMS as the control goal. The model is solved, and finally, the effectiveness of the proposed voltage control strategy is verified by combining actual examples. The results show that the proposed voltage control strategy has a better voltage regulation effect and effectively reduces the overall voltage deviation of the distribution network.

Active Equalization of Lithium Battery Pack with Adaptive Control based on DC Energy Conversion Circuit

Background:: How to solve the inconsistency of battery pack is a key point to ensure reliable operation of electric vehicles. Battery equalization is an effective measure to address the inconsistency. Passive equalization method has poor efficiency and thermal management problems. Average voltage equalization method is only suitable for situations where there is a significant voltage difference between batteries. The SOC-based equalization method is relatively difficult and may inevitably lead to the accumulation of errors during the process. Objective:: In order to avoid the disadvantages of traditional control methods, a new control method is proposed to improve the accuracy and self-adaptation of active equalization, which is easy to be realized without online calculation. Methods:: Cascaded bidirectional Buck-boost circuit is adopted as the novel equalization topology. Based on fuzzy PID theory, an adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed in this paper. Parameter design of the fuzzy PID controller is carried out. A battery equalization system based on cascaded bidirectional Buck-boost circuit is designed and developed. Experimental verification is conducted on relevant hardware platforms. Results:: An adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed. Compared to passive equalization, this proposed method provides high efficiency. Regarding traditional voltage control, the method improves control reliability and flexibility. Compared to the average voltage equalization method, the approach needs less convergence time. Moreover, the control method is much easier to realize than the SOC-based equalization method. Conclusion:: By using the presented adaptive control based on DC energy conversion circuit, the degree of self-adaptation of the equalization process has been obtained as higher and the inconsistency as smaller.

Research on Black Start Control technology of Energy Storage Power Station Based on VSG All Vanadium Flow Battery

To reduce the losses caused by large-scale power outages in the power system, a stable control technology for the black start process of a 100 megawatt all vanadium flow battery energy storage power station is proposed. Firstly, a model is constructed for the liquid flow battery energy storage power station, and in order to improve the system capacity, four unit level power stations are processed in parallel. Secondly, based on the energy storage of all vanadium flow batteries, the traditional voltage and frequency stability control technology has been improved to address the characteristics of low inertia and damping in power electronic interfaces. The improved VSG strategy has been applied to the overall control of a hundred megawatt level flow battery energy storage power station, solving the voltage and frequency instability problems caused by load shocks and fluctuations. Finally, stable control of multiple parallel machines during the self starting process of the liquid flow battery energy storage power station was achieved, avoiding the occurrence of multiple machine circulation and uneven power distribution problems during the self starting process.

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.

Energy Balance Control of Energy Storage System Based on Improved Virtual DC Motor

Energy storage units have a big role in microgrids. To enhance the inertia of the DC microgrid while achieving energy balancing of each energy storage system, an energy balancing control of the energy storage system with virtual DC motor characteristics is proposed. By adding the VDCM technique to the traditional constant voltage control and adding the SoC information of the respective energy storage system to the virtual armature induction potential of the armature loop equation in the VDCM control, compared to existing controls, this control method can enhance DC microgrid inertia while balancing the SoC of the energy storage system, as well as charging and discharging mode switching without changing the control strategy. Finally, a multi-storage DC microgrid model is built in Matlab/Simulink, and the feasibility of the method is verified by simulation.

Probabilistic approach to investigate the impact of distributed generation on voltage deviation in distribution system

The increasing penetration of renewable-based generation in the distribution network adds randomness to the bus voltage due to its stochastic characteristics. Consequently, the distribution network faces voltage limit violations at multiple buses. In this scenario, the traditional voltage control method fails to maintain the voltage profile of the network due to its slow response time. A fast and dynamic voltage control technique can be achieved by utilizing the voltage-controlling capability of available DGs in the network with the information about the impact of DG-integrated bus on change in voltage at any bus in the network. Evaluating this information using the traditional probabilistic load flow method is computationally inefficient for real-time applications. Therefore, in this paper, a principal component analysis (PCA)-based novel probabilistic voltage sensitivity index (PVSI) is proposed. It ranks the DG-integrated buses by evaluating the impact of power perturbation at DG-integrated buses on changes in voltage at any bus in the network. The PVSI is analytically derived to reduce the computation time for ranking. Further, the proposed PVSI is validated on the 69-bus and the 141-bus distribution systems by comparing it with the traditional Monte Carlo simulation (MCS) and joint differential entropy (JDE) in terms of accuracy and computation time. From the simulation, it is observed that PVSI gives a similar ranking as both methods in less computation time. Due to the advantage in computation time, the proposed method enables the distribution system operator (DSO) to use this information for fast and dynamic voltage control in a real-time scenario.

Multi-stage voltage control in high photovoltaic based distributed generation penetrated distribution system considering smart inverter reactive power capability

Multi-stage voltage control in high photovoltaic based distributed generation penetrated distribution system considering smart inverter reactive power capability

Coordinated voltage control of active distribution networks with photovoltaic and power to hydrogen

AbstractThe rapid increase of photovoltaic (PV) penetration in active distribution networks (ADN) is posing great challenges to traditional voltage control schemes. A two‐stage voltage control strategy of ADN is proposed by the authors based on the alternating direction method of multipliers (ADMM) with refined power to hydrogen (P2H) model, considering multiple types of PV forms such as residential photovoltaic cluster (RPVC) and small‐scale PV power stations. In the day‐ahead stage, the optimal power flow is performed to determine the optimal scheduling results of on‐load tap changers and capacitor banks etc. In the intra‐day stage, the real‐time voltage control strategy is implemented at the distribution network layer to regulate the power of each type of PV, energy storage systems and P2H to further reduce the voltage deviation. At the customer layer, the residential photovoltaic (RPV) within the RPVC is precisely controlled based on the ADMM algorithm to achieve the minimum voltage deviation at each RPV access point. The proposed strategy is tested on the modified IEEE 33‐bus and IEEE 69‐bus distribution systems, and the simulation results verify its effectiveness in mitigating voltage violations.

Investigation of Nonlinear PI Multi-loop Control Strategy for Aircraft HVDC Generator System with Wound Rotor Synchronous Machine

In order to enhance the transient performance of aircraft high voltage DC (HVDC) generation system with wound rotor synchronous machine (WRSM) under a wide speed range, the nonlinear PI multi-loop control strategy is proposed in this paper. Traditional voltage control method is hard to achieve the dynamic performance requirements of the HVDC generation system under a wide speed range, so the nonlinear PI parameter adjustment, load current feedback and speed feedback are added to the voltage and excitation current double loop control. The transfer function of the HVDC generation system is derived, and the relationship between speed, load current and PI parameters is obtained. The PI parameters corresponding to the load at certain speed are used to shorten the adjusting time when the load suddenly changes. The dynamic responses in transient processes are analyzed by experiment. The results illustrate that the WRSM HVDC generator system with this method has better dynamic performance.

Intelligent Voltage Control Method in Active Distribution Networks Based on Averaged Weighted Double Deep Q-network Algorithm

High penetration of distributed renewable energy sources and electric vehicles (EVs) makes future active distribution network (ADN) highly variable. These characteristics put great challenges to traditional voltage control methods. Voltage control based on the deep Q-network (DQN) algorithm offers a potential solution to this problem because it possesses human-level control performance. However, the traditional DQN methods may produce overestimation of action reward values, resulting in degradation of obtained solutions. In this paper, an intelligent voltage control method based on averaged weighted double deep Q-network (AWDDQN) algorithm is proposed to overcome the shortcomings of overestimation of action reward values in DQN algorithm and underestimation of action reward values in double deep Q-network (DDQN) algorithm. Using the proposed method, the voltage control objective is incorporated into the designed action reward values and normalized to form a Markov decision process (MDP) model which is solved by the AWDDQN algorithm. The designed AWDDQN-based intelligent voltage control agent is trained offline and used as online intelligent dynamic voltage regulator for the ADN. The proposed voltage control method is validated using the IEEE 33-bus and 123-bus systems containing renewable energy sources and EVs, and compared with the DQN and DDQN algorithms based methods, and traditional mixed-integer nonlinear program based methods. The simulation results show that the proposed method has better convergence and less voltage volatility than the other ones.

An Information Theoretic Approach to Identify Dominant Voltage Influencers for Unbalanced Distribution Systems

Smart distribution grid with multiple renewable energy sources can experience random voltage fluctuations due to variable generation, which may result in voltage violations. Traditional voltage control algorithms are inadequate to handle fast voltage variations. Therefore, new dynamic control methods are being developed that can significantly benefit from the knowledge of dominant voltage influencer (DVI) nodes. DVI nodes for a particular node of interest refer to nodes that have a relatively high impact on the voltage fluctuations at that node. Conventional power flow-based algorithms to identify DVI nodes are computationally complex, which limits their use in real-time applications. This paper proposes a novel information theoretic voltage influencing score (VIS) that quantifies the voltage influencing capacity of nodes with DERs/active loads in a three phase unbalanced distribution system. VIS is then employed to rank the nodes and identify the DVI set. VIS is derived analytically in a computationally efficient manner and its efficacy to identify DVI nodes is validated using the IEEE 37-node test system. It is shown through experiments that KL divergence and Bhattacharyya distance are effective indicators of DVI nodes with an identifying accuracy of more than 90%. The computation burden is also reduced by an order of 5, thus providing the foundation for efficient voltage control.

Bus Voltage Control of Photovoltaic Grid Connected Inverter Based on Adaptive Linear Active Disturbance Rejection

According to the traditional voltage and current double closed-loop control mode, the inverter management strategy for photovoltaic grid connection has insufficient anti-interference ability and slow response. This paper proposes a control strategy that applies adaptive-linear active disturbance rejection control (A–LADRC) to the outer loop control to achieve the purpose of anti-interference. The control strategy uses the linear extended state observer (LESO) to evaluate external interference caused by the change of external conditions and the internal disturbance caused by parameter uncertainty. PD controller compensates the disturbances and adds adaptive control to simplify parameter adjustment. Finally, this paper takes advantage of Lyapunov theory to conduct stability analysis. Compared with the traditional linear active disturbance rejection control (LADRC), the superiority of this control strategy is verified. The experimental results show that the system has better control performance and anti-interference ability in the face of various disturbances.

Data-Driven Fast Voltage Control in Non-DPMU Distribution Networks With Microgrids

Traditional voltage control methods for distribution networks assume perfect knowledge of the power system model. Nevertheless, the extensive scale of future distribution networks makes it unrealistic to acquire the overall operation state monitoring. Moreover, with the deregulation of distribution networks, partial controllable resources belong to independent systems, such as microgrids, causing distribution system operators unable to force them to provide voltage support directly. To cope with the previously mentioned problems, a data-driven fast voltage control method for distribution networks with MGs is proposed in this article. First, voltage sensitivity matrices are estimated indirectly by identifying line parameters in a regression approach, without using measurement data of distribution phasor measurement units (DPMUs) in distribution networks. Then, an incomplete information game model is proposed to motivate MGs to provide ancillary services of voltage control. To guarantee privacy, only a little key information is shared among MGs and distribution system operators. Moreover, MGs make voltage control strategies autonomously based on the data-driven deep reinforcement learning algorithms, while maximizing their own profits. Finally, we test the method on the modified IEEE 33-node networks and IEEE 123-node networks. The results demonstrate that the proposed method can provide an accurate voltage estimation in electricity markets with non-DPMU measurement data and increase energy and asset utilization.

Influence of automatic voltage control on small signal stability of photovoltaic system

In order to solve the problem of large delay and uncertain impact on the system when traditional automatic voltage control is used in photovoltaic power station system control, a small signal analysis model of photovoltaic grid connected system including automatic voltage control is established. Firstly, considering that the actual automatic voltage control system contains dead time and delay link, the continuous dead time model of photovoltaic system is defined; Then, considering the nonlinear part of automatic voltage control, the small disturbance model of photovoltaic grid connected system with dead time and delay part is derived. The small disturbance model of photovoltaic system is formed by using the linearization principle, which is used to describe the expressions of damping torque and synchronous torque of photovoltaic system; Then, the expressions of PV active power increment, power angle increment and speed increment are obtained by small signal model; Finally, the validity of the model is verified by the comparison of theoretical calculation and simulation results. The results show that the proposed model can describe the damping component and synchronous component effect of photovoltaic system under disturbance, and provide a reference for the study of photovoltaic stability.

Research on the Application of Artificial Intelligence Technology in Power System Intelligent Dispatching Automation

From the perspective of meeting the power quality requirements of users, the article analyses the characteristics of traditional voltage and reactive power control mode and the regional power grid reactive voltage optimization centralized closed-loop control mode (AVC system) based on the dispatch automation system (SCADA/EMS) from the perspective of technical management. Combining the reactive power/voltage real-time optimization control model, a real-time optimization control method of the regional power grid based on the improved differential evolution algorithm is proposed. The particle swarm algorithm is combined with the characteristics of reactive power/voltage control to improve the initial particle quality, reduce the optimization space, and introduce a crossover operator to improve the calculation speed and efficiency of the algorithm. Taking an actual regional power grid as an example, the simulation calculation of reactive power/voltage real-time optimization is carried out. The results show that the proposed algorithm and control strategy are feasible and effective.

Event-Triggered Mechanism Based Control Method of SMES to Improve Microgrids Stability Under Extreme Conditions

Microgrids with multiple converters suffer from excessive pressure on the communication network during traditional voltage and frequency regulation control. This paper proposed an event-triggered control strategy based superconducting magnetic energy storage (SMES) scheme to improve AC microgrids stability under successive disconnection of sources or step change of loads. By designing an event-triggered mechanism, each converter in the microgrid sends its own information to SMES in a non-periodic way. Then the control method of bus voltage and frequency regulation using SMES is constructed, which enables SMES to update its control mode. The microgrid model is established in PSCAD/EMTDC, and two cases of extreme conditions are conducted to demonstrate the effectiveness of the proposed method.

Distributed Voltage Control for Three-Phase Unbalanced Distribution Systems With DERs and Practical Constraints

Traditional voltage control schemes in the power distribution system are typically centralized or local. Local control often gives nonoptimal solutions utilizing local measurements and lacks global coordination. Centralized control gives optimal solutions but lack scalability and robustness, especially with the increasing number of distributed energy resources (DERs). Recent advancement in power electronics with improved automation and digitalization in power grid control provides an opportunity to enable distributed optimization approaches for voltage control. This article proposes an optimal distributed voltage control algorithm based on augmented Lagrangian multiplier theory and primal-dual gradients for three-phase unbalanced distribution systems. In the developed algorithm, each node uses its own local measurements and neighboring nodes measurements to compute optimal reactive power setpoints, while meeting reactive power injection constraints for DERs. The proposed algorithm also considers practical constraints, such as communication delays, measurement noises, modeling errors, limited control devices, and infrequent switching required for field implementation. The proposed algorithm is validated for voltage control in an unbalanced, three-phase IEEE 123-bus feeder modeled in OpenDSS to demonstrate superior performance.

Decentralized Voltage Control in Active Distribution Systems: Features and Open Issues

Voltage control is becoming a key issue in active distribution systems, which are electric distribution networks characterized by a large penetration of DERs. Traditional voltage control devices, as well as the active and reactive powers injected by DERs, can be used as ancillary services to support voltage profiles along the distribution feeders. Due to the peculiar characteristics of active distribution systems, the decentralized control approach presents the most promising technical and economical features. In the paper, the decentralized voltage control structure is hierarchically decomposed into different control levels, characterized by different objectives and time frames. The primary and secondary control levels have been analyzed, always according to a decentralized approach. For each level, the various techniques for solving the voltage control problem that have been proposed in the literature are presented, and their main features compared. The main open issues related to the real time practical implementation of the decentralized architectures at both primary and secondary voltage control levels are investigated, keeping always in mind both technical and economical aspects, which always represent the components of a trade-off solution.