The traditional transient stability assessment(TSA)model for power systems has three disadvantages:capturing critical information during faults is difficult,aperiodic and oscillatory unstable conditions are not distin...The traditional transient stability assessment(TSA)model for power systems has three disadvantages:capturing critical information during faults is difficult,aperiodic and oscillatory unstable conditions are not distinguished,and poor generalizability is exhibited by systems with high renewable energy penetration.To address these issues,a novel ResGRU architecture for TSA is proposed in this study.First,a residual neural network(ResNet)is used for deep feature extraction of transient information.Second,a bidirectional gated recurrent unit combined with a multi-attention mechanism(BiGRU-Attention)is used to establish temporal feature dependencies.Their combination constitutes a TSA framework based on the ResGRU architecture.This method predicts three transient conditions:oscillatory instability,aperiodic instability,and stability.The model was trained offline using stochastic gradient descent with a thermal restart(SGDR)optimization algorithm in the offline training phase.This significantly improves the generalizability of the model.Finally,simulation tests on IEEE 145-bus and 39-bus systems confirmed that the proposed method has higher adaptability,accuracy,scalability,and rapidity than the conventional TSA approach.The proposed model also has superior robustness for PMU incomplete configurations,PMU noisy data,and packet loss.展开更多
With the continuous expansion and increasing complexity of power system scales,the binary classifica-tion for transient stability assessment in power systems can no longer meet the safety requirements of power system ...With the continuous expansion and increasing complexity of power system scales,the binary classifica-tion for transient stability assessment in power systems can no longer meet the safety requirements of power system control and regulation.Therefore,this paper proposes a multi-class transient stability assessment model based on an improved Transformer.The model is designed with a dual-tower encoder structure:one encoder focuses on the time dependency of data,while the other focuses on the dynamic correlations between variables.Feature extraction is conducted from both time and variable perspectives to ensure the completeness of the feature extraction process,thereby enhancing the accuracy of multi-class evaluation in power systems.Additionally,this paper introduces a hybrid sampling strategy based on sample boundaries,which addresses the issue of sample imbalance by increasing the number of boundary samples in the minority class and reducing the number of non-boundary samples in the majority class.Considering the frequent changes in power grid topology or operation modes,this paper proposes a two-stage updating scheme based on self-supervised learning:In the first stage,self-supervised learning is employed to mine the structural information from unlabeled data in the target domain,enhancing the model’s generalization capability in new scenarios.In the second stage,a sample screening mechanism is used to select key samples,which are labeled through long-term simulation techniques for fine-tuning the model parameters.This allows for rapid model updates without relying on many labeled samples.This paper’s proposed model and update scheme have been simulated and verified on two node systems,the IEEE New England 10-machine 39-bus system and the IEEE 47-machine 140-bus system,demonstrating their effectiveness and reliability.展开更多
Based on the complementary advantages of Line Commutated Converter(LCC)and Modular Multilevel Converter(MMC)in power grid applications,there are two types of hybrid DC system topologies:one is the parallel connection ...Based on the complementary advantages of Line Commutated Converter(LCC)and Modular Multilevel Converter(MMC)in power grid applications,there are two types of hybrid DC system topologies:one is the parallel connection of LCC converter stations and MMC converter stations,and the other is the series connection of LCC and MMC converter stations within a single station.The hybrid DC transmission system faces broad application prospects and development potential in large-scale clean energy integration across regions and the construction of a new power system dominated by new energy sources in China.This paper first analyzes the system forms and topological characteristics of hybrid DC transmission,introducing the forms and topological characteristics of converter-level hybrid DC transmission systems and system-level hybrid DC transmission systems.Next,it analyzes the operating characteristics of LCC and MMC inverter-level hybrid DC transmission systems,provides insights into the transient stability of hybrid DC transmission systems,and typical fault ride-through control strategies.Finally,it summarizes the networking characteristics of the LCC-MMC series within the converter station hybrid DC transmission system,studies the transient characteristics and fault ridethrough control strategies under different fault types for the LCC-MMC series in the receiving-end converter station,and investigates the transient characteristics and fault ride-through control strategies under different fault types for the LCC-MMC series in the sending-end converter station.展开更多
The data-driven transient stability assessment(TSA)of power systems can predict online real-time prediction by learning the temporal features before and after faults.However,the accuracy of the assessment is limited b...The data-driven transient stability assessment(TSA)of power systems can predict online real-time prediction by learning the temporal features before and after faults.However,the accuracy of the assessment is limited by the quality of the data and has weak transferability.Based on this,this paper proposes a method for TSA of power systems based on an improved extreme gradient boosting(XGBoost)model.Firstly,the gradient detection method is employed to remove noise interference while maintaining the original time series trend.On this basis,a focal loss function is introduced to guide the training of theXGBoostmodel,enhancing the deep exploration of minority class samples to improve the accuracy of the model evaluation.Furthermore,to improve the generalization ability of the evaluation model,a transfer learning method based on model parameters and sample augmentation is proposed.The simulation analysis on the IEEE 39-bus system demonstrates that the proposed method,compared to the traditional machine learning-based transient stability assessment approach,achieves an average improvement of 2.16%in evaluation accuracy.Specifically,under scenarios involving changes in topology structure and operating conditions,the accuracy is enhanced by 3.65%and 3.11%,respectively.Moreover,the model updating efficiency is enhanced by 14–15 times,indicating the model’s transferable and adaptive capabilities across multiple scenarios.展开更多
This paper proposes a novel framework that enables the simultaneous coordination of the controllers of doubly fed induction generators(DFIGs) and synchronous generators(SGs).The proposed coordination approach is based...This paper proposes a novel framework that enables the simultaneous coordination of the controllers of doubly fed induction generators(DFIGs) and synchronous generators(SGs).The proposed coordination approach is based on the zero dynamics method aims at enhancing the transient stability of multi-machine power systems under a wide range of operating conditions. The proposed approach was implemented to the IEEE39-bus power systems. Transient stability margin measured in terms of critical clearing time along with eigenvalue analysis and time domain simulations were considered in the performance assessment. The obtained results were also compared to those achieved using a conventional power system stabilizer/power oscillation(PSS/POD) technique and the interconnection and damping assignment passivity-based controller(IDA-PBC). The performance analysis confirmed the ability of the proposed approach to enhance damping and improve system’s transient stability margin under a wide range of operating conditions.展开更多
The use of an electrical network as close as possible to its limits can lead to its instability in the event of a high amplitude disturbance. The damping of system oscillations can be achieved by conventional means of...The use of an electrical network as close as possible to its limits can lead to its instability in the event of a high amplitude disturbance. The damping of system oscillations can be achieved by conventional means of voltage and speed regulation but also by FACTS (Flexible AC Transmission Systems) devices, which are increasingly used in power networks. In this work, optimal control coordination between a hybrid power flow controller and a three-level inverter was used to improve the transient stability of a transmission line. The UPFC is a combination of a serial compensator (SSSC) and a parallel compensator (STATCOM) both connected to a DC-LINK DC bus. The SSSC acts as a voltage source for the network and injects a voltage that can be adjusted in phase and amplitude in addition to the network voltage;the STATCOM acts as a current source. The approach used is tested in the Matlab Simulink environment on a single machine network. Optimal controller tuning gives a better transient stability improvement by reducing the transport angle oscillations from 248.17% to 9.85%.展开更多
As photovoltaic （PV） capacity in power system increases, the capacity of synchronous generator needs to be reduced relatively. This leads to the lower system inertia and the higher generator reactance, and hence the...As photovoltaic （PV） capacity in power system increases, the capacity of synchronous generator needs to be reduced relatively. This leads to the lower system inertia and the higher generator reactance, and hence the generator transient stability may negatively be affected. In particular, the impact on the transient stability may become more serious when the considerable amounts of PV systems are disconnected simultaneously during voltage sag. In this work, the generator transient stability in the power system with significant PV penetration is assessed by a numerical simulation. In order to assess the impact from various angles, simulation parameters such as levels of PV penetration, variety of power sources （inverter or rotational machine）, and existence of LVRT capability are considered. The simulation is performed by using PSCAD/EMTDC software.展开更多
The impact of large-scale grid-connected PV （photovoltaics） on power system transient stability is discussed in this paper. In response to an increase of PV capacity, the capacity of conventional synchronous generat...The impact of large-scale grid-connected PV （photovoltaics） on power system transient stability is discussed in this paper. In response to an increase of PV capacity, the capacity of conventional synchronous generator needs to be reduced relatively. This leads to the lower system inertia and the higher generator reactance, and hence, the power system transient stability may negatively be affected. In particular, the impact on the transient stability may become more serious when the considerable amounts of PV systems are disconnected simultaneously during voltage sag. In this work, the potential impact of significant PV penetration on the transient stability is assessed by a numerical simulation using PSCAD/EMTDC.展开更多
With the integration of a voltage source converter(VSC),having variable internal voltages and source impedance,in a microgrid with high resistance to reactance ratio of short lines,angle-based transient stability tech...With the integration of a voltage source converter(VSC),having variable internal voltages and source impedance,in a microgrid with high resistance to reactance ratio of short lines,angle-based transient stability techniques may find limitations.Under such a situation,the Lyapunov function can be a viable option for transient stability assessment(TSA)of such a VSC-interfaced microgrid.However,the determination of the Lyapunov function with the classical method is very challenging for a microgrid with converter controller dynamics.To overcome such challenges,this paper develops a physics-informed,Lyapunov function-based TSA framework for VSC-interfaced microgrids.The method uses the physics involved and the initial and boundary conditions of the system in learning the Lyapunov functions.This method is tested and validated under faults,droop-coefficient changes,generator outages,and load shedding on a small grid-connected microgrid and the CIGRE microgrid.展开更多
The novel quantitative assessment method using transmission line measurement was developed. A new style of stability criterion was suggested which is based on the line measurement. The stability indices for lines, cut...The novel quantitative assessment method using transmission line measurement was developed. A new style of stability criterion was suggested which is based on the line measurement. The stability indices for lines, cutsets and power system according to features of transient energy in the lines were given, which not only provide a reliable and accurate assessment of the transient stability of power system, but also can be used to assess the effect of lines and cutsets on the transient stability and identify the weak transmission segment. Examples were presented by simulation on the IEEE-39 buses test system.展开更多
The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased.The capacity of the synchronous generators to keep working without losing synchronizat...The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased.The capacity of the synchronous generators to keep working without losing synchronization when the system is exposed to severe faults such as short circuits is referred to as the power system’s transient stability.As the power system’s safe and stable operation and mechanism of action become more complicated,higher demands for accurate and rapid power system transient stability analysis are made.Current methods for analyzing transient stability are less accurate because they do not account formisclassification of unstable samples.As a result,this paper proposes a novel approach for analyzing transient stability.The key concept is to use deep forest(DF)and a neighborhood rough reduction approach together.Using the neighborhood rough sets,the original feature space is obtained by creating many optimal feature subsets at various granularity levels.Then,by deploying the DF cascade structure,the mapping connection between the transient stability state and the features is reinforced.The weighted voting technique is used in the learning process to increase the classification accuracy of unstable samples.When contrasted to current methods,simulation results indicate that the proposed approach outperforms them.展开更多
The length of the trajectory is proposed as a function for the employment of the sensitivity analysis method in power system transient stability analysis. Its sensitivity to the faultclearing time is about 10 times hi...The length of the trajectory is proposed as a function for the employment of the sensitivity analysis method in power system transient stability analysis. Its sensitivity to the faultclearing time is about 10 times higher than that of the energy function or the distance function. The integrating time is reduced to less than 3 s while the accuracy is maintained. It can also be used to provide parameter limits. Simulations on the WSCC 4 machine system and the New England system verify the effectiveness of sensitivity of trajectory length in transient stability analysis.展开更多
With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possi...With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possible higher transmission capacity is very cost-effective.In this regard,to increase the capacity of the transmission lines,the flexible alternating current transmission system(FACTS)has been widely used in power grids in recent years by industrialized countries.One of the essential topics in electrical power systems is the reactive power compensation,and the FACTS plays a significant role in controlling the reactive power current in the power grid and the system voltage oscillations and stability.When a static synchronous compensator(STATCOM)is embedded in a power system to increase the bus voltage,a supplementary damping controller can be designed to enhance the system oscillation damping.Given the expansion of the grids in the power system,the complexity of their optimization and the extraordinary ability of the imperialist competitive algorithm(ICA)for solving such problems,in this paper,the ICA has been used to determine the optimal position and size of the FACTS devices.展开更多
The impact of large-scale grid-connected renewable power sources, such as wind generators and solar photovoitaic systems, on transient stability of synchronous generators is discussed in this paper. The permanent magn...The impact of large-scale grid-connected renewable power sources, such as wind generators and solar photovoitaic systems, on transient stability of synchronous generators is discussed in this paper. The permanent magnet synchronous generator with variable speed wind turbine is used in the simulation analysis as a wind generator model. The transient stability analysis is performed for IEEE 9-bus system model with high-penetration renewable power sources. The effect of FRT （fault ride-through） capability implemented for each power source on the transient stability is investigated.展开更多
In the previous paper [1], the transient stability of synchronous generator in power system with high-penetration PV （photovoltaic） was assessed by simulation analysis of a single-machine infinite-bus system model. ...In the previous paper [1], the transient stability of synchronous generator in power system with high-penetration PV （photovoltaic） was assessed by simulation analysis of a single-machine infinite-bus system model. Through the simulation analysis, we have obtained some conclusions in terms of the impact of high-penetration PV on the stability. However, for more accurate assessment of the transient stability, it is necessary to analyze various simulation models considering many other power system conditions. This paper presents the results of the analysis for the transient stability simulation performed for IEEE 9-bus system model, in which the effects of various conditions, such as variety of power sources （inverter or rotational machine）, load characteristics, existence of LVRT （low-voltage ride-through） capability and fault locations, on the transient stability are investigated.展开更多
Virtual synchronous generators(VSGs)can provide voltage and frequency support to power systems due to their inertial and damping features.Unfortunately,power angle stability and fault current limitations are still cha...Virtual synchronous generators(VSGs)can provide voltage and frequency support to power systems due to their inertial and damping features.Unfortunately,power angle stability and fault current limitations are still challenging aspects of VSGs under large disturbances.Power angle stability and fault current limitations are indispensable for the safe operation of a VSG.However,in existing studies,these aspects are mostly solved as two independent problems.In this paper,the comprehensive transient stability enhancement(CTSE)control strategy for a VSG,considering power angle stability and fault current limitations is proposed.With a CTSE control,VSG's transient power angle stability is guaranteed.In addition,the steady-state and impulse components of the fault current are fully limited.Furthermore,CTSE control parameters adapted to different fault degrees are presented.Finally,simulation and experimental tests are performed to validate the performance of the proposed method.展开更多
The increasing adoption of grid-forming converters(GFMCs)stems from their capacity to furnish voltage and frequency support for power grids.Nevertheless,GFMCs employing the current reference saturation limiting method...The increasing adoption of grid-forming converters(GFMCs)stems from their capacity to furnish voltage and frequency support for power grids.Nevertheless,GFMCs employing the current reference saturation limiting method often exhibit instability during various transient disturbances including grid voltage sags,frequency variations,and phase jumps.To address this problem,this paper proposes a virtual power angle synchronous(δv-SYN)control method.The fundamental of this method is to achieve synchronization with the grid using the virtual power angleδv instead of the active power.The transient stability characteristics of the proposed method are theoretically elucidated using a novel virtual power angle-power angle(δv-δ)model.The key benefit of the proposed method is its robustness to various grid strengths and diverse forms of transient disturbances,eliminating the requirement for fault identification or control switching.Moreover,it can offer grid-forming support to the grid during grid faults.Hardware-in-the-loop experimental results validate the theoretical analysis and the performance of the proposed method.展开更多
This study proposes a new transient-stability preventive control (TSPC) method based on graph convolutional neural networks (GCNN) and transfer deep reinforcement learning (DRL) to address non-convergence problems of ...This study proposes a new transient-stability preventive control (TSPC) method based on graph convolutional neural networks (GCNN) and transfer deep reinforcement learning (DRL) to address non-convergence problems of traditional optimization algorithms and slow training speed of artificial intelligence algorithms for TSPC. First, a transient stability assessor (TSA) with GCNN is developed to assess current-power-flow state. Sensitivities of the transient-stability index relative to the generators are approximately calculated using TSA;generators with significant influence able to narrow action space are identified. Subsequently, the Markov decision-making process of TSPC is derived by introducing the process of TSPC. A DRL for TSPC is constructed by adding entropy to twin delayed deep deterministic policy gradient (TD3). Knowledge learned by TSA is transferred to DRL based on transfer learning, which improves learning efficiency. Finally, case studies based on the IEEE 39-bus system and an actual power grid prove the effectiveness of the proposed method. Comparisons performed with reference algorithms in literature demonstrate the proposed method has better performance in both control effect and speed.展开更多
This paper presents a quantitative assessment of the transient stability of grid-forming converters,considering current limitations,inertia,and damping effects.The contributions are summarized in two main aspects:Firs...This paper presents a quantitative assessment of the transient stability of grid-forming converters,considering current limitations,inertia,and damping effects.The contributions are summarized in two main aspects:First,the analysis delves into transient stability under a general voltage sag scenario for a converter subject to current limitations.When the voltage sag exceeds a critical threshold,transient instability arises,with its severity influenced by the inertia and damping coefficients within the swing equation.Second,a comprehensive evaluation of these inertia and damping effects is conducted using a model-based phase-portrait approach.This method allows for an accurate assessment of critical clearing time(CCT)and critical clearing angle(CCA)across varying inertia and damping coefficients.Leveraging data obtained from the phase portrait,an artificial neural network(ANN)method is presented to model CCT and CCA accurately.This precise estimation of CCT enables the extension of practical operation time under faults compared to conservative assessments based on equal-area criteria(EAC),thereby fully exploiting the system's low-voltage-ride-through(LVRT)and fault-ride-through(FRT)capabilities.The theoretical transient analysis and estimation method proposed in this paper are validated through PSCAD/EMTDC simulations.展开更多
Deep learning technology is identified as a valid tool for transient stability assessment(TSA).Moreover,the superior performance of the TSA model depends on generously labeled samples.However,the power grid is dynamic...Deep learning technology is identified as a valid tool for transient stability assessment(TSA).Moreover,the superior performance of the TSA model depends on generously labeled samples.However,the power grid is dynamic,and some topologies or operation conditions change substantially.The traditional method generates a significant quantity of samples for each specific topology.Nonetheless,generating these labeled samples and establishing TSA models is very time-consuming.This paper proposes a high-quality sample generation framework based on data-driven methods to build a high-quality offline samples database for TSA model training and updating.Firstly,the representative topologies provided by the system operator are clustered into four different categories by density-based spatial clustering of applications with noise(DBSCAN).Thus the corresponding samples are collected.Then,when a new topology is encountered in the online application,scenario matching is used to match the most similar topology category.After that,instance-based transfer learning is implemented from a database of the best-matched topology category.Finally,a deep convolutional generative adversarial network(DCGAN)is constructed to mitigate the class imbalance problem.That is,unstable scenarios occur far more rarely than stable scenarios.Consequently,a high-quality and balanced TSA model training and updating database is constructed.The comprehensive test results on the Central China Power Grid illustrate that the proposed framework can generate high-quality and balanced TSA samples.Furthermore,the sample generation time is dramatically shortened.In addition,the metrics of accuracy,reliability and adaptability of the TSA model are significantly enhanced.展开更多
基金financially supported by State Key Laboratory of HVDC No.SKLHVDC-2023-KF-03.
文摘The traditional transient stability assessment(TSA)model for power systems has three disadvantages:capturing critical information during faults is difficult,aperiodic and oscillatory unstable conditions are not distinguished,and poor generalizability is exhibited by systems with high renewable energy penetration.To address these issues,a novel ResGRU architecture for TSA is proposed in this study.First,a residual neural network(ResNet)is used for deep feature extraction of transient information.Second,a bidirectional gated recurrent unit combined with a multi-attention mechanism(BiGRU-Attention)is used to establish temporal feature dependencies.Their combination constitutes a TSA framework based on the ResGRU architecture.This method predicts three transient conditions:oscillatory instability,aperiodic instability,and stability.The model was trained offline using stochastic gradient descent with a thermal restart(SGDR)optimization algorithm in the offline training phase.This significantly improves the generalizability of the model.Finally,simulation tests on IEEE 145-bus and 39-bus systems confirmed that the proposed method has higher adaptability,accuracy,scalability,and rapidity than the conventional TSA approach.The proposed model also has superior robustness for PMU incomplete configurations,PMU noisy data,and packet loss.
基金the National Natural Science Foundation of China(5227-7084).
文摘With the continuous expansion and increasing complexity of power system scales,the binary classifica-tion for transient stability assessment in power systems can no longer meet the safety requirements of power system control and regulation.Therefore,this paper proposes a multi-class transient stability assessment model based on an improved Transformer.The model is designed with a dual-tower encoder structure:one encoder focuses on the time dependency of data,while the other focuses on the dynamic correlations between variables.Feature extraction is conducted from both time and variable perspectives to ensure the completeness of the feature extraction process,thereby enhancing the accuracy of multi-class evaluation in power systems.Additionally,this paper introduces a hybrid sampling strategy based on sample boundaries,which addresses the issue of sample imbalance by increasing the number of boundary samples in the minority class and reducing the number of non-boundary samples in the majority class.Considering the frequent changes in power grid topology or operation modes,this paper proposes a two-stage updating scheme based on self-supervised learning:In the first stage,self-supervised learning is employed to mine the structural information from unlabeled data in the target domain,enhancing the model’s generalization capability in new scenarios.In the second stage,a sample screening mechanism is used to select key samples,which are labeled through long-term simulation techniques for fine-tuning the model parameters.This allows for rapid model updates without relying on many labeled samples.This paper’s proposed model and update scheme have been simulated and verified on two node systems,the IEEE New England 10-machine 39-bus system and the IEEE 47-machine 140-bus system,demonstrating their effectiveness and reliability.
基金supported by the Joint Research Fund in Smart Grid(U23B20120)under cooperative agreement between the National Natural Science Foundation of China and State Grid Corporation of China。
文摘Based on the complementary advantages of Line Commutated Converter(LCC)and Modular Multilevel Converter(MMC)in power grid applications,there are two types of hybrid DC system topologies:one is the parallel connection of LCC converter stations and MMC converter stations,and the other is the series connection of LCC and MMC converter stations within a single station.The hybrid DC transmission system faces broad application prospects and development potential in large-scale clean energy integration across regions and the construction of a new power system dominated by new energy sources in China.This paper first analyzes the system forms and topological characteristics of hybrid DC transmission,introducing the forms and topological characteristics of converter-level hybrid DC transmission systems and system-level hybrid DC transmission systems.Next,it analyzes the operating characteristics of LCC and MMC inverter-level hybrid DC transmission systems,provides insights into the transient stability of hybrid DC transmission systems,and typical fault ride-through control strategies.Finally,it summarizes the networking characteristics of the LCC-MMC series within the converter station hybrid DC transmission system,studies the transient characteristics and fault ridethrough control strategies under different fault types for the LCC-MMC series in the receiving-end converter station,and investigates the transient characteristics and fault ride-through control strategies under different fault types for the LCC-MMC series in the sending-end converter station.
基金This work is supported by the State Grid Shanxi Electric Power Company Technology Project(52053023000B).
文摘The data-driven transient stability assessment(TSA)of power systems can predict online real-time prediction by learning the temporal features before and after faults.However,the accuracy of the assessment is limited by the quality of the data and has weak transferability.Based on this,this paper proposes a method for TSA of power systems based on an improved extreme gradient boosting(XGBoost)model.Firstly,the gradient detection method is employed to remove noise interference while maintaining the original time series trend.On this basis,a focal loss function is introduced to guide the training of theXGBoostmodel,enhancing the deep exploration of minority class samples to improve the accuracy of the model evaluation.Furthermore,to improve the generalization ability of the evaluation model,a transfer learning method based on model parameters and sample augmentation is proposed.The simulation analysis on the IEEE 39-bus system demonstrates that the proposed method,compared to the traditional machine learning-based transient stability assessment approach,achieves an average improvement of 2.16%in evaluation accuracy.Specifically,under scenarios involving changes in topology structure and operating conditions,the accuracy is enhanced by 3.65%and 3.11%,respectively.Moreover,the model updating efficiency is enhanced by 14–15 times,indicating the model’s transferable and adaptive capabilities across multiple scenarios.
文摘This paper proposes a novel framework that enables the simultaneous coordination of the controllers of doubly fed induction generators(DFIGs) and synchronous generators(SGs).The proposed coordination approach is based on the zero dynamics method aims at enhancing the transient stability of multi-machine power systems under a wide range of operating conditions. The proposed approach was implemented to the IEEE39-bus power systems. Transient stability margin measured in terms of critical clearing time along with eigenvalue analysis and time domain simulations were considered in the performance assessment. The obtained results were also compared to those achieved using a conventional power system stabilizer/power oscillation(PSS/POD) technique and the interconnection and damping assignment passivity-based controller(IDA-PBC). The performance analysis confirmed the ability of the proposed approach to enhance damping and improve system’s transient stability margin under a wide range of operating conditions.
文摘The use of an electrical network as close as possible to its limits can lead to its instability in the event of a high amplitude disturbance. The damping of system oscillations can be achieved by conventional means of voltage and speed regulation but also by FACTS (Flexible AC Transmission Systems) devices, which are increasingly used in power networks. In this work, optimal control coordination between a hybrid power flow controller and a three-level inverter was used to improve the transient stability of a transmission line. The UPFC is a combination of a serial compensator (SSSC) and a parallel compensator (STATCOM) both connected to a DC-LINK DC bus. The SSSC acts as a voltage source for the network and injects a voltage that can be adjusted in phase and amplitude in addition to the network voltage;the STATCOM acts as a current source. The approach used is tested in the Matlab Simulink environment on a single machine network. Optimal controller tuning gives a better transient stability improvement by reducing the transport angle oscillations from 248.17% to 9.85%.
文摘As photovoltaic （PV） capacity in power system increases, the capacity of synchronous generator needs to be reduced relatively. This leads to the lower system inertia and the higher generator reactance, and hence the generator transient stability may negatively be affected. In particular, the impact on the transient stability may become more serious when the considerable amounts of PV systems are disconnected simultaneously during voltage sag. In this work, the generator transient stability in the power system with significant PV penetration is assessed by a numerical simulation. In order to assess the impact from various angles, simulation parameters such as levels of PV penetration, variety of power sources （inverter or rotational machine）, and existence of LVRT capability are considered. The simulation is performed by using PSCAD/EMTDC software.
文摘The impact of large-scale grid-connected PV （photovoltaics） on power system transient stability is discussed in this paper. In response to an increase of PV capacity, the capacity of conventional synchronous generator needs to be reduced relatively. This leads to the lower system inertia and the higher generator reactance, and hence, the power system transient stability may negatively be affected. In particular, the impact on the transient stability may become more serious when the considerable amounts of PV systems are disconnected simultaneously during voltage sag. In this work, the potential impact of significant PV penetration on the transient stability is assessed by a numerical simulation using PSCAD/EMTDC.
基金supported by the National Science Foundation under Grant No.ITE-2134840This work relates to the Department of Navy award N00014-23-1-2124 issued by the Office of Naval Research.The United States Government has a royalty-free license worldwide for all copyrightable material contained herein。
文摘With the integration of a voltage source converter(VSC),having variable internal voltages and source impedance,in a microgrid with high resistance to reactance ratio of short lines,angle-based transient stability techniques may find limitations.Under such a situation,the Lyapunov function can be a viable option for transient stability assessment(TSA)of such a VSC-interfaced microgrid.However,the determination of the Lyapunov function with the classical method is very challenging for a microgrid with converter controller dynamics.To overcome such challenges,this paper develops a physics-informed,Lyapunov function-based TSA framework for VSC-interfaced microgrids.The method uses the physics involved and the initial and boundary conditions of the system in learning the Lyapunov functions.This method is tested and validated under faults,droop-coefficient changes,generator outages,and load shedding on a small grid-connected microgrid and the CIGRE microgrid.
基金National Natural Science Foundation ofChina( No.5 99770 0 1)
文摘The novel quantitative assessment method using transmission line measurement was developed. A new style of stability criterion was suggested which is based on the line measurement. The stability indices for lines, cutsets and power system according to features of transient energy in the lines were given, which not only provide a reliable and accurate assessment of the transient stability of power system, but also can be used to assess the effect of lines and cutsets on the transient stability and identify the weak transmission segment. Examples were presented by simulation on the IEEE-39 buses test system.
基金The authors extend their appreciation to the Deanship of Scientific Research at Jouf University for funding this work through research Grant No.(DSR-2021-02-0113).
文摘The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased.The capacity of the synchronous generators to keep working without losing synchronization when the system is exposed to severe faults such as short circuits is referred to as the power system’s transient stability.As the power system’s safe and stable operation and mechanism of action become more complicated,higher demands for accurate and rapid power system transient stability analysis are made.Current methods for analyzing transient stability are less accurate because they do not account formisclassification of unstable samples.As a result,this paper proposes a novel approach for analyzing transient stability.The key concept is to use deep forest(DF)and a neighborhood rough reduction approach together.Using the neighborhood rough sets,the original feature space is obtained by creating many optimal feature subsets at various granularity levels.Then,by deploying the DF cascade structure,the mapping connection between the transient stability state and the features is reinforced.The weighted voting technique is used in the learning process to increase the classification accuracy of unstable samples.When contrasted to current methods,simulation results indicate that the proposed approach outperforms them.
基金Supported by the National Natural Science Foundation of China (60474018)
文摘The length of the trajectory is proposed as a function for the employment of the sensitivity analysis method in power system transient stability analysis. Its sensitivity to the faultclearing time is about 10 times higher than that of the energy function or the distance function. The integrating time is reduced to less than 3 s while the accuracy is maintained. It can also be used to provide parameter limits. Simulations on the WSCC 4 machine system and the New England system verify the effectiveness of sensitivity of trajectory length in transient stability analysis.
基金This work was supported in part by an International Research Partnership“Electrical Engineering-Thai French Research Center(EE-TFRC)”under the project framework of the Lorraine Universited’Excellence(LUE)in cooperation between Universitede Lorraine and King Mongkut’s University of Technology North Bangkok and in part by the National Research Council of Thailand(NRCT)under Senior Research Scholar Program under Grant No.N42A640328.
文摘With the daily expansion of global energy consumption,developing the power grids is of uttermost importance.However,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possible higher transmission capacity is very cost-effective.In this regard,to increase the capacity of the transmission lines,the flexible alternating current transmission system(FACTS)has been widely used in power grids in recent years by industrialized countries.One of the essential topics in electrical power systems is the reactive power compensation,and the FACTS plays a significant role in controlling the reactive power current in the power grid and the system voltage oscillations and stability.When a static synchronous compensator(STATCOM)is embedded in a power system to increase the bus voltage,a supplementary damping controller can be designed to enhance the system oscillation damping.Given the expansion of the grids in the power system,the complexity of their optimization and the extraordinary ability of the imperialist competitive algorithm(ICA)for solving such problems,in this paper,the ICA has been used to determine the optimal position and size of the FACTS devices.
文摘The impact of large-scale grid-connected renewable power sources, such as wind generators and solar photovoitaic systems, on transient stability of synchronous generators is discussed in this paper. The permanent magnet synchronous generator with variable speed wind turbine is used in the simulation analysis as a wind generator model. The transient stability analysis is performed for IEEE 9-bus system model with high-penetration renewable power sources. The effect of FRT （fault ride-through） capability implemented for each power source on the transient stability is investigated.
文摘In the previous paper [1], the transient stability of synchronous generator in power system with high-penetration PV （photovoltaic） was assessed by simulation analysis of a single-machine infinite-bus system model. Through the simulation analysis, we have obtained some conclusions in terms of the impact of high-penetration PV on the stability. However, for more accurate assessment of the transient stability, it is necessary to analyze various simulation models considering many other power system conditions. This paper presents the results of the analysis for the transient stability simulation performed for IEEE 9-bus system model, in which the effects of various conditions, such as variety of power sources （inverter or rotational machine）, load characteristics, existence of LVRT （low-voltage ride-through） capability and fault locations, on the transient stability are investigated.
基金supported by the National Natural Science Foundation of China(51907057,52077072).
文摘Virtual synchronous generators(VSGs)can provide voltage and frequency support to power systems due to their inertial and damping features.Unfortunately,power angle stability and fault current limitations are still challenging aspects of VSGs under large disturbances.Power angle stability and fault current limitations are indispensable for the safe operation of a VSG.However,in existing studies,these aspects are mostly solved as two independent problems.In this paper,the comprehensive transient stability enhancement(CTSE)control strategy for a VSG,considering power angle stability and fault current limitations is proposed.With a CTSE control,VSG's transient power angle stability is guaranteed.In addition,the steady-state and impulse components of the fault current are fully limited.Furthermore,CTSE control parameters adapted to different fault degrees are presented.Finally,simulation and experimental tests are performed to validate the performance of the proposed method.
基金supported in part by the National Natural Science Foundation of China(No.52377186)the Natural Science Foundation of Guangdong Province(No.2024A1515012428)+1 种基金the Science and Technology Planning Project of Guangdong Province,China(No.2023A1111120023)the Basic and Applied Basic Research Foundation of Guangdong Province(No.2022A1515240026)。
文摘The increasing adoption of grid-forming converters(GFMCs)stems from their capacity to furnish voltage and frequency support for power grids.Nevertheless,GFMCs employing the current reference saturation limiting method often exhibit instability during various transient disturbances including grid voltage sags,frequency variations,and phase jumps.To address this problem,this paper proposes a virtual power angle synchronous(δv-SYN)control method.The fundamental of this method is to achieve synchronization with the grid using the virtual power angleδv instead of the active power.The transient stability characteristics of the proposed method are theoretically elucidated using a novel virtual power angle-power angle(δv-δ)model.The key benefit of the proposed method is its robustness to various grid strengths and diverse forms of transient disturbances,eliminating the requirement for fault identification or control switching.Moreover,it can offer grid-forming support to the grid during grid faults.Hardware-in-the-loop experimental results validate the theoretical analysis and the performance of the proposed method.
文摘This study proposes a new transient-stability preventive control (TSPC) method based on graph convolutional neural networks (GCNN) and transfer deep reinforcement learning (DRL) to address non-convergence problems of traditional optimization algorithms and slow training speed of artificial intelligence algorithms for TSPC. First, a transient stability assessor (TSA) with GCNN is developed to assess current-power-flow state. Sensitivities of the transient-stability index relative to the generators are approximately calculated using TSA;generators with significant influence able to narrow action space are identified. Subsequently, the Markov decision-making process of TSPC is derived by introducing the process of TSPC. A DRL for TSPC is constructed by adding entropy to twin delayed deep deterministic policy gradient (TD3). Knowledge learned by TSA is transferred to DRL based on transfer learning, which improves learning efficiency. Finally, case studies based on the IEEE 39-bus system and an actual power grid prove the effectiveness of the proposed method. Comparisons performed with reference algorithms in literature demonstrate the proposed method has better performance in both control effect and speed.
基金supported by the EPSRC project‘Sustainable Urban Power Supply through Intelligent Control and Enhanced Restoration of AC/DC Networks'under Grant EP/T021985/1.
文摘This paper presents a quantitative assessment of the transient stability of grid-forming converters,considering current limitations,inertia,and damping effects.The contributions are summarized in two main aspects:First,the analysis delves into transient stability under a general voltage sag scenario for a converter subject to current limitations.When the voltage sag exceeds a critical threshold,transient instability arises,with its severity influenced by the inertia and damping coefficients within the swing equation.Second,a comprehensive evaluation of these inertia and damping effects is conducted using a model-based phase-portrait approach.This method allows for an accurate assessment of critical clearing time(CCT)and critical clearing angle(CCA)across varying inertia and damping coefficients.Leveraging data obtained from the phase portrait,an artificial neural network(ANN)method is presented to model CCT and CCA accurately.This precise estimation of CCT enables the extension of practical operation time under faults compared to conservative assessments based on equal-area criteria(EAC),thereby fully exploiting the system's low-voltage-ride-through(LVRT)and fault-ride-through(FRT)capabilities.The theoretical transient analysis and estimation method proposed in this paper are validated through PSCAD/EMTDC simulations.
基金supported by the Technology Project from China Electric Power Planning&Engineering Institute(No.K202312)。
文摘Deep learning technology is identified as a valid tool for transient stability assessment(TSA).Moreover,the superior performance of the TSA model depends on generously labeled samples.However,the power grid is dynamic,and some topologies or operation conditions change substantially.The traditional method generates a significant quantity of samples for each specific topology.Nonetheless,generating these labeled samples and establishing TSA models is very time-consuming.This paper proposes a high-quality sample generation framework based on data-driven methods to build a high-quality offline samples database for TSA model training and updating.Firstly,the representative topologies provided by the system operator are clustered into four different categories by density-based spatial clustering of applications with noise(DBSCAN).Thus the corresponding samples are collected.Then,when a new topology is encountered in the online application,scenario matching is used to match the most similar topology category.After that,instance-based transfer learning is implemented from a database of the best-matched topology category.Finally,a deep convolutional generative adversarial network(DCGAN)is constructed to mitigate the class imbalance problem.That is,unstable scenarios occur far more rarely than stable scenarios.Consequently,a high-quality and balanced TSA model training and updating database is constructed.The comprehensive test results on the Central China Power Grid illustrate that the proposed framework can generate high-quality and balanced TSA samples.Furthermore,the sample generation time is dramatically shortened.In addition,the metrics of accuracy,reliability and adaptability of the TSA model are significantly enhanced.
