This page has only limited features, please log in for full access.
The microgrid with the high proportion of renewable sources has become the trend of the future. However, the negative features, such as renewable energy perturbation, nonlinear counterpart, and so on, are prone to causing the low-power quality of the ac microgrid. To deal with these problems, this article proposes an event-triggered consensus control approach. First, the nonlinear state-space function regarding the ac microgrid is built, which is further transformed into the standard linear multiagent model by using the singular perturbation method. It provides indispensable preprocessing for the direct application of advanced linear control approaches. Then, based on this standard linear multiagent model, the secondary consensus approach with the leader is designed to compensate for the output voltage deviation and achieve accurate power sharing. In order to decrease the communication among various distributed generators, the event-triggered communication method is further proposed. Meanwhile, the Zeno behavior is avoided through the theoretical proof. Finally, simulation results are presented to demonstrate the effectiveness of the proposed approach.
Dazhong Ma; Menglin Liu; Huaguang Zhang; Rui Wang; Xiangpeng Xie. Accurate Power Sharing and Voltage Regulation for AC Microgrids: An Event-Triggered Coordinated Control Approach. IEEE Transactions on Cybernetics 2021, PP, 1 -11.
AMA StyleDazhong Ma, Menglin Liu, Huaguang Zhang, Rui Wang, Xiangpeng Xie. Accurate Power Sharing and Voltage Regulation for AC Microgrids: An Event-Triggered Coordinated Control Approach. IEEE Transactions on Cybernetics. 2021; PP (99):1-11.
Chicago/Turabian StyleDazhong Ma; Menglin Liu; Huaguang Zhang; Rui Wang; Xiangpeng Xie. 2021. "Accurate Power Sharing and Voltage Regulation for AC Microgrids: An Event-Triggered Coordinated Control Approach." IEEE Transactions on Cybernetics PP, no. 99: 1-11.
For AC microgrids with three-phase unbalanced loading conditions, the four-wire voltage source inverters (FWVSIs) have become an advisable interfaced converter between the source and loads. Predictive control has been applied to FWVSIs in recent years, but model errors are not solved well, which is caused through parameter mismatch, sampling error and time delay. Thus, the accurate following between reference value and predicted value is difficult to achieve. To this end, a dual-predictive control based on adaptive error correction (DPCEC) for the FW-VSIs is presented. Firstly, the state-space function of FW-VSIs under reference frame is built. Then, the DPCEC strategy is proposed based on the above issue. Therein, an adaptive error correction strategy is severally embedded into both the outer and inner prediction loop. Noting that the impacts of different negative factors can be simultaneously processed and corrected through adaptive error correction strategy. Not only does the proposed control strategy achieve better performance in steady state, but also retains fast dynamic response in transient state. Finally, simulation and experimental results which verify the high performance of the proposed control techniques are provided.
Dazhong Ma; Xingchen Cao; Chenghao Sun; Rui Wang; Qiuye Sun; Xiangpeng Xie; Peng Wang. Dual-Predictive Control with Adaptive Error Correction Strategy for AC Microgrids. IEEE Transactions on Power Delivery 2021, PP, 1 -1.
AMA StyleDazhong Ma, Xingchen Cao, Chenghao Sun, Rui Wang, Qiuye Sun, Xiangpeng Xie, Peng Wang. Dual-Predictive Control with Adaptive Error Correction Strategy for AC Microgrids. IEEE Transactions on Power Delivery. 2021; PP (99):1-1.
Chicago/Turabian StyleDazhong Ma; Xingchen Cao; Chenghao Sun; Rui Wang; Qiuye Sun; Xiangpeng Xie; Peng Wang. 2021. "Dual-Predictive Control with Adaptive Error Correction Strategy for AC Microgrids." IEEE Transactions on Power Delivery PP, no. 99: 1-1.
In the real-time status monitoring of pipeline network, incomplete pressure data are unavoidable due to some device or communication errors. To solve this problem, a hierarchical data recovery method based on generative adversarial networks (GANs) is proposed in this article. First, a hierarchical data recovery framework is proposed to handle different numbers of incomplete data due to the structure of the semicentral pipeline network. Second, a joint attention module is presented to capture both interior nature and correlation relationships of multivariate pressure series and further guarantee the consistency of pressure data. Third, the macromicrodual discriminators are proposed to evaluate the recovery result through the combination of the local and global variation in temporal and spatial dependencies. Based on the novel structures, the proposed model is able to recover incomplete data with abnormal fluctuation values, unreasonable fixed values, or missing values. Finally, under a series of data recovery experiments, the efficiency of the proposed method is evaluated. Experimental results demonstrate that the proposed method is a practical way to ensure data recovery performance in the pipeline network.
Xuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang. Hierarchical Pressure Data Recovery for Pipeline Network via Generative Adversarial Networks. IEEE Transactions on Automation Science and Engineering 2021, PP, 1 -11.
AMA StyleXuguang Hu, Huaguang Zhang, Dazhong Ma, Rui Wang. Hierarchical Pressure Data Recovery for Pipeline Network via Generative Adversarial Networks. IEEE Transactions on Automation Science and Engineering. 2021; PP (99):1-11.
Chicago/Turabian StyleXuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang. 2021. "Hierarchical Pressure Data Recovery for Pipeline Network via Generative Adversarial Networks." IEEE Transactions on Automation Science and Engineering PP, no. 99: 1-11.
Multi-port solid-state transformer (SST) characterized by high scalability is expected to be widely used in AC/DC hybrid microgrid. However, the DC bus voltage deviation and dynamic response speed are two key issues in its application. Therefore, a model predictive direct power control (MPDPC) of the three-port SST (TPSST) is proposed. Compared with the traditional PI-based method, the oscillation of the DC bus voltage is inhibited, and the steady-state performance is improved with the MPDPC method. Moreover, a direct power path is incorporated into the control system in order to integrate the rectifier and dual active bridge (DAB) stage. This power path delivers the power required by the load to the DAB stage and the rectifier stage for power control, thereby improving the dynamic response of the system in the process. Besides, since the MPDPC strategy is a control scheme for the whole system, the design of the control system is simplified. Finally, a low power prototype has been built and tested, and the experimental comparison with the traditional voltage control (TVC) and model predictive voltage control (MPVC) method verifies the efficiency improvement of the proposed control strategy.
Qiuye Sun; Yuyang Li; Dazhong Ma; Yi Zhang; Dehao Qin. Model Predictive Direct Power Control of Three-port Solid-State Transformer for Hybrid AC/DC Zonal Microgrid Applications. IEEE Transactions on Power Delivery 2021, PP, 1 -1.
AMA StyleQiuye Sun, Yuyang Li, Dazhong Ma, Yi Zhang, Dehao Qin. Model Predictive Direct Power Control of Three-port Solid-State Transformer for Hybrid AC/DC Zonal Microgrid Applications. IEEE Transactions on Power Delivery. 2021; PP (99):1-1.
Chicago/Turabian StyleQiuye Sun; Yuyang Li; Dazhong Ma; Yi Zhang; Dehao Qin. 2021. "Model Predictive Direct Power Control of Three-port Solid-State Transformer for Hybrid AC/DC Zonal Microgrid Applications." IEEE Transactions on Power Delivery PP, no. 99: 1-1.
For the quasi-Z-source inverter (qZSI), capacitor voltage stability control, high performance of the inductor current reference tracking and fast response of the active/reactive power are key issues. Thus, a decoupled active/reactive power model predictive control (MPC) of the qZSI for distributed generations (DGs) is proposed to fulfill these requirements without additional control loops. Firstly, the digital observer is constructed to remove the utilization of the front voltage sensor and reduce the number of hardware equipment. Moreover, based on the advance determination of the system operation mode and the simplified cost function, the calculation complexity of the proposed MPC algorithm is simplified. Further, the proposed improved MPC method with the digital observer is proved to achieve the high accuracy and the zero prediction error, of which stability is demonstrated through Lyapunov stability criteria. Eventually, the proposed controller is compared with conventional MPC and PI controller in detail and its effectiveness is verified by both simulation and experimental results from a grid-connected qZSI.
Dazhong Ma; Ke Cheng; Rui Wang; Sen Lin; Xiangpeng Xie. The Decoupled Active/Reactive Power Predictive Control of Quasi-Z-source Inverter for Distributed Generations. International Journal of Control, Automation and Systems 2021, 19, 810 -822.
AMA StyleDazhong Ma, Ke Cheng, Rui Wang, Sen Lin, Xiangpeng Xie. The Decoupled Active/Reactive Power Predictive Control of Quasi-Z-source Inverter for Distributed Generations. International Journal of Control, Automation and Systems. 2021; 19 (2):810-822.
Chicago/Turabian StyleDazhong Ma; Ke Cheng; Rui Wang; Sen Lin; Xiangpeng Xie. 2021. "The Decoupled Active/Reactive Power Predictive Control of Quasi-Z-source Inverter for Distributed Generations." International Journal of Control, Automation and Systems 19, no. 2: 810-822.
In daily pipeline inspection, it is significant to ensure good network communication and security. With the development of drone technology, it is possible to apply drones as air routers to collect information from pipeline networks and transmit it to pipeline inspectors. It is also crucial to achieve optimal drone deployment in pipeline networks. This article proposes a two-phase evolution optimal 3-D drone layout algorithm to deploy drones in pipeline networks. First, a 3-D pipeline graph model is designed to represent the possible projection position of drones, and the objective function is proposed for optimal drone deployment. Then, in the first phase, based on the features of the 3-D pipeline graph, the drone flight rules and constraint conditions are presented to calculate the number of drones and the initial layout sequence. In the second phase, according to the objective function and the above results, every drone is continuously moved in a small area to achieve a tradeoff between signal coverage and interference. Moreover, the key parameters of the objective function can be discussed to further optimize drone deployment. Simulation results are presented to illustrate the effectiveness and advantages of the proposed algorithm.
Dazhong Ma; Yunbo Li; Xuguang Hu; Huaguang Zhang; Xiangpeng Xie. An Optimal Three-Dimensional Drone Layout Method for Maximum Signal Coverage and Minimum Interference in Complex Pipeline Networks. IEEE Transactions on Cybernetics 2021, PP, 1 -11.
AMA StyleDazhong Ma, Yunbo Li, Xuguang Hu, Huaguang Zhang, Xiangpeng Xie. An Optimal Three-Dimensional Drone Layout Method for Maximum Signal Coverage and Minimum Interference in Complex Pipeline Networks. IEEE Transactions on Cybernetics. 2021; PP (99):1-11.
Chicago/Turabian StyleDazhong Ma; Yunbo Li; Xuguang Hu; Huaguang Zhang; Xiangpeng Xie. 2021. "An Optimal Three-Dimensional Drone Layout Method for Maximum Signal Coverage and Minimum Interference in Complex Pipeline Networks." IEEE Transactions on Cybernetics PP, no. 99: 1-11.
The droop control is an advantageous approach for stand-alone supply systems consisting of multiple batteries, allowing among various inverters without intercommunication. The droop coefficients of batteries always vary with their state-of-charge (SoC) and charge/discharge mode, resulting in small-signal instability. Nevertheless, the existing impedance-based approaches can only assess the droop coefficients stability point, but not the stability region. Therefore, this paper proposes a droop coefficients stability region analysis approach. Firstly, the charge/discharge SoC-based droop controlled battery, the $P\&Q$ controlled distributed generator and the constant power load are separately discussed. Meanwhile, the state matrix and return-ratio matrix are established, respectively. Furthermore, the novel forbidden region criterion based on the return-ratio matrix is constructed, which reduces conservatism compared with norm-based impedance criteria and partial forbidden region criteria. Such a forbidden region criterion is first switched to the Hurwitz identification problem regarding the equivalent return-ratio matrix. Combined the state matrix and the equivalent return-ratio matrix, the generalized incidence matrix is constructed to simultaneously identify subsystem stability and interactive stability. Based on the generalized incidence matrix, an adaptive step search strategy is proposed to obtain the droop coefficients coordinated stability region. Finally, the simulation and experimental results illustrate the validity of the proposed method.
Rui Wang; Qiuye Sun; Wei Hu; Yushuai Li; Dazhong Ma; Peng Wang. SoC-Based Droop Coefficients Stability Region Analysis of the Battery for Stand-Alone Supply Systems With Constant Power Loads. IEEE Transactions on Power Electronics 2021, 36, 7866 -7879.
AMA StyleRui Wang, Qiuye Sun, Wei Hu, Yushuai Li, Dazhong Ma, Peng Wang. SoC-Based Droop Coefficients Stability Region Analysis of the Battery for Stand-Alone Supply Systems With Constant Power Loads. IEEE Transactions on Power Electronics. 2021; 36 (7):7866-7879.
Chicago/Turabian StyleRui Wang; Qiuye Sun; Wei Hu; Yushuai Li; Dazhong Ma; Peng Wang. 2021. "SoC-Based Droop Coefficients Stability Region Analysis of the Battery for Stand-Alone Supply Systems With Constant Power Loads." IEEE Transactions on Power Electronics 36, no. 7: 7866-7879.
Due to the widely deployed sensors in pipeline network, the data-driven detection method is a natural choice with multiple sensor measurements. However, the incomplete data problem caused by device failure or network interruption seriously hinders the implementation of pipeline status monitoring. Aiming at this difficulty, this paper proposes a generative adversarial networks based on tri-networks form (tnGAN) to handle leak detection problem with incomplete sensor data. Firstly, the generative model is proposed to recover incomplete data through fully exploiting the same-level nature similarity of data features. Therein, the same type of sensor data, obtained from pipeline network, is used as the input. Next, to further boost the temporal evolvement characteristics and the spatial similarity, a multi-view awareness strategy is incorporated in the established model to facilitate the integration of inherent information. Then a dual-discriminative network architecture is proposed to detect pipeline status through computing the similarity of the latent features of samples. With the above mentioned structure, the proposed method can achieve different incomplete data recovery situation such as individual lost and random missing. Additionally, it can also aggregate the output and features of the discriminative networks to obtain the pipeline leak detection result. Finally, the experiment results on a pipeline network demonstrate that the capability and effectiveness of the proposed method in both data recovery and leak detection.
Xuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang. A tnGAN-Based Leak Detection Method for Pipeline Network Considering Incomplete Sensor Data. IEEE Transactions on Instrumentation and Measurement 2020, 70, 1 -10.
AMA StyleXuguang Hu, Huaguang Zhang, Dazhong Ma, Rui Wang. A tnGAN-Based Leak Detection Method for Pipeline Network Considering Incomplete Sensor Data. IEEE Transactions on Instrumentation and Measurement. 2020; 70 (99):1-10.
Chicago/Turabian StyleXuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang. 2020. "A tnGAN-Based Leak Detection Method for Pipeline Network Considering Incomplete Sensor Data." IEEE Transactions on Instrumentation and Measurement 70, no. 99: 1-10.
In terms of pipeline leak detection, the unavoidable fact is that existing data could not provide enough effective leak data to train a high accuracy model. To address this issue, this article proposes mixed generative adversarial networks (mixed-GANs) as a practical way to provide additional data, ensuring data reliability. First, multitype generative networks with heterogeneous parameter-updating mechanisms are designed to explore a variety of different solutions and eliminate the potential risks of instable training and scenario collapse. Then, based on expert experience, two data constraints are proposed to describe leak characteristics and further evaluate the quality of generated leak data in the training process. Through integrating the particle swarm optimization algorithm into generative model training, mixed-GAN has better generation performance than the conventional gradient descent algorithm. Based on the above-mentioned contents, the proposed model is able to provide satisfactory leak data with different scenarios, contributing to data quantity expansion, data credibility enhancement, and data variety enrichment. Finally, extensive experiments are given to illustrate the effectiveness of the proposed generative model for pipeline network leak detection.
Huaguang Zhang; Xuguang Hu; Dazhong Ma; Rui Wang; Xiangpeng Xie. Insufficient Data Generative Model for Pipeline Network Leak Detection Using Generative Adversarial Networks. IEEE Transactions on Cybernetics 2020, PP, 1 -14.
AMA StyleHuaguang Zhang, Xuguang Hu, Dazhong Ma, Rui Wang, Xiangpeng Xie. Insufficient Data Generative Model for Pipeline Network Leak Detection Using Generative Adversarial Networks. IEEE Transactions on Cybernetics. 2020; PP (99):1-14.
Chicago/Turabian StyleHuaguang Zhang; Xuguang Hu; Dazhong Ma; Rui Wang; Xiangpeng Xie. 2020. "Insufficient Data Generative Model for Pipeline Network Leak Detection Using Generative Adversarial Networks." IEEE Transactions on Cybernetics PP, no. 99: 1-14.
For the operational status detection of a pipeline network, it is essential to obtain enough samples of each class during the network operation. However, the phenomenon of few actual leak samples give rise to the imbalanced dataset problem. To address this issue, this paper proposes a minor class-based status detection method using enhanced generative adversarial networks (enhanced-GANs). First, a generative model with a U-net structure is established to generate the required samples with the modified normal samples, and the L1 loss and L2 loss functions are utilized to update the network parameters. Then, output results and extracted features regarding different layers of discriminative network are added in the generative network loss function to improve the quality of the generated samples. Furthermore, based on the hidden features extracted by the trained discriminative network, an enhanced dual judgment scheme is proposed to improve the status detection performance. Finally, extensive experiments are carried out to evaluate the proposed method with the dataset collected from a practical pipeline network. The experiment results show that the proposed method can not only provide enough leak samples but also effectively improves the status detection accuracy for a pipeline network.
Xuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang; Jun Zheng. Minor class-based status detection for pipeline network using enhanced generative adversarial networks. Neurocomputing 2020, 424, 71 -83.
AMA StyleXuguang Hu, Huaguang Zhang, Dazhong Ma, Rui Wang, Jun Zheng. Minor class-based status detection for pipeline network using enhanced generative adversarial networks. Neurocomputing. 2020; 424 ():71-83.
Chicago/Turabian StyleXuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang; Jun Zheng. 2020. "Minor class-based status detection for pipeline network using enhanced generative adversarial networks." Neurocomputing 424, no. : 71-83.
Weak grids are gaining considerable attention since power generation resources are remote from constant power loads (CPLs), which results in low-frequency/harmonic oscillation. Meanwhile, due to the play and plug demand of modern power system, the line inductance of weak grids often changes, which is also regarded as the variation regarding short circuit ratio (SCR). Based on this, the conventional impedance-based stability operation point assessment approaches should be expanded into stability domain assessment approach considering the line inductance variation. Therefore, the stability-oriented line inductance stability domain assessment approach for weak grids with CPLs is proposed in this paper. Firstly, the source impedance matrix of weak grid and load admittance matrix of CPLs are separately built. Secondly, an improved stability forbidden domain criterion is proposed through related mapping transformation process, which has lower conservatism than the norm-based criteria and the traditional stability forbidden criteria. Thirdly, the improved stability forbidden domain criterion is switched into the condition that the intermediate matrices are Hurwitz. Meanwhile, the line inductance stability domain is directly obtained through these intermediate matrices and guardian map theory. Finally, the simulation and experiment results illustrate that the proposed approach has less conservatism and high efficiency.
Wang Rui; Sun Qiuye; Ma Dazhong; Qin Dehao; Gui Yonghao; Wang Peng. Line Inductance Stability Operation Domain Assessment for Weak Grids With Multiple Constant Power Loads. IEEE Transactions on Energy Conversion 2020, 36, 1045 -1055.
AMA StyleWang Rui, Sun Qiuye, Ma Dazhong, Qin Dehao, Gui Yonghao, Wang Peng. Line Inductance Stability Operation Domain Assessment for Weak Grids With Multiple Constant Power Loads. IEEE Transactions on Energy Conversion. 2020; 36 (2):1045-1055.
Chicago/Turabian StyleWang Rui; Sun Qiuye; Ma Dazhong; Qin Dehao; Gui Yonghao; Wang Peng. 2020. "Line Inductance Stability Operation Domain Assessment for Weak Grids With Multiple Constant Power Loads." IEEE Transactions on Energy Conversion 36, no. 2: 1045-1055.
Situation awareness is essential to ensure operation of integrated energy systems consisting of the electricity, gas and heat systems. However, the multi-energy flow characteristics of system result in strong coupling relationships among different subsystems including different detection variables, which bring new challenges to situation awareness. To address this issue, a data driven detection method based on spectral analysis of random matrix is proposed in this paper. Firstly, a detection matrix model, which combines different types of variables, is established to fully reflect the interdependencies among subsystems, both internal and external. Furthermore, a novel detection method, which analyzes the degree of the spectral deviation of presented model, is presented to accomplish situation awareness. The proposed method can effectively handle the problem of power-gas-heat coupling, multi-variable modeling and rapid situation judging without requiring complicated numerical model. With this effort, not only the changed time but also the position of changed node could be obtained simultaneously through only spectral computation. Finally, simulation results are presented to illustrate the effectiveness of the proposed detection method.
Xuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang. Situation awareness method using spectral analysis of random matrix for integrated energy system. ISA Transactions 2020, 99, 240 -251.
AMA StyleXuguang Hu, Huaguang Zhang, Dazhong Ma, Rui Wang. Situation awareness method using spectral analysis of random matrix for integrated energy system. ISA Transactions. 2020; 99 ():240-251.
Chicago/Turabian StyleXuguang Hu; Huaguang Zhang; Dazhong Ma; Rui Wang. 2020. "Situation awareness method using spectral analysis of random matrix for integrated energy system." ISA Transactions 99, no. : 240-251.
This paper deals with the problem of the fault-tolerant fuzzy master–slave systems synchronization through an adaptive event-triggered scheme (AETS). First, a Takagi–Sugeno (T–S) fuzzy model is employed to represent the master–slave system dynamics. Second, an AETS is introduced to judge whether the newly sampled controller’s signals should be released to the slave system or not. Consequently, the less computation resources and network bandwidth are utilized under the AETS. Meanwhile, a novel adaptive law is designed to achieve the threshold of event-triggering condition on-line. Third, a novel fuzzy controller is designed, containing a state feedback controller and a fault compensator to achieve the fault-tolerant synchronization, which is formulated to study the global asymptotical stability of the error system. As a results, applying Lyapunov theory and inequality technique, new sufficient condition is obtained to guarantee the stability of the error system. Further, the controller gain and the weight of event-triggering condition are designed through linear matrix inequalities (LMIs) approach. Finally, a numerical simulation example is employed to demonstrate the practical utility of this method.
Xiaoyu Li; Dazhong Ma; Xiangpeng Xie; Qiuye Sun. Fault-Tolerant Synchronization of Chaotic Systems with Fuzzy Sampled Data Controller Based on Adaptive Event-Triggered Scheme. International Journal of Fuzzy Systems 2020, 22, 917 -929.
AMA StyleXiaoyu Li, Dazhong Ma, Xiangpeng Xie, Qiuye Sun. Fault-Tolerant Synchronization of Chaotic Systems with Fuzzy Sampled Data Controller Based on Adaptive Event-Triggered Scheme. International Journal of Fuzzy Systems. 2020; 22 (3):917-929.
Chicago/Turabian StyleXiaoyu Li; Dazhong Ma; Xiangpeng Xie; Qiuye Sun. 2020. "Fault-Tolerant Synchronization of Chaotic Systems with Fuzzy Sampled Data Controller Based on Adaptive Event-Triggered Scheme." International Journal of Fuzzy Systems 22, no. 3: 917-929.
Although the low-frequency/harmonic oscillation of grid-tied inverters under weak grids has been widely researched, the classical impedance-based approach focuses more on the identification of stable operating points and the stability margin of return-ratio matrix. Furthermore, it cannot provide stability regions of system parameters. Therefore, this paper proposes a line impedance cooperative stability region identification method. Firstly, the output impedance matrix and the input admittance matrix are respectively built in d-q axis. Secondly, a novel stability forbidden region is proposed. It is less conservative than the forbidden region criteria in existing literatures. Based on the stability forbidden region, the stability operation region is established via mirror, translation and rotation mappings. It is less conservative compared with the norm-based stability criteria. The solving of stability operation region is first transformed into the eigenvalue identification problem in this paper. Furthermore, the detailed line impedance cooperative stability region is solved by guardian map theory. It can provide guidance for system planning and stabilization method researches with simplified computational process. Finally, the simulation and experimental results show that the proposed line impedance cooperative stability region identification method is more effective and less conservative.
Wang Rui; Sun Qiuye; Ma Dazhong; Hu Xuguang. Line Impedance Cooperative Stability Region Identification Method for Grid-Tied Inverters Under Weak Grids. IEEE Transactions on Smart Grid 2020, 11, 2856 -2866.
AMA StyleWang Rui, Sun Qiuye, Ma Dazhong, Hu Xuguang. Line Impedance Cooperative Stability Region Identification Method for Grid-Tied Inverters Under Weak Grids. IEEE Transactions on Smart Grid. 2020; 11 (4):2856-2866.
Chicago/Turabian StyleWang Rui; Sun Qiuye; Ma Dazhong; Hu Xuguang. 2020. "Line Impedance Cooperative Stability Region Identification Method for Grid-Tied Inverters Under Weak Grids." IEEE Transactions on Smart Grid 11, no. 4: 2856-2866.
By utilizing dynamic event-triggered control strategy, this paper deals with consensus problem of a class of heterogeneous leader-following multi-agent systems(MASs) consisting of a high-dimensional leader system but low-dimensional following systems. A kind of observer-based consensus controllers is put forward with a dynamic event-triggered function consisting of the measurement error and a threshold based on the neighbors discrete states to reduce unnecessary utilization of limited communication and computation resources. Meanwhile, a dynamic variable is used to generate the event-triggered law using Input-to-State Stability(ISS) criteria. Based on this criteria, the proposed control strategy ensures stability of MASs, which fully reflects of the relationship between the external control inputs of the following systems and the internal states of the leader system and fully considered the influence of disturbances or noises on the MASs. Furthermore, the Zeno behavior for triggering time sequence is excluded. At last, a numerical simulation is provided to demonstrate the feasibility and effectiveness of the theoretical results.
Xiaoyu Li; Dazhong Ma; Xuguang Hu; Qiuye Sun. Dynamic Event-triggered Control for Heterogeneous Leader-following Consensus of Multi-agent Systems Based on Input-to-state Stability. International Journal of Control, Automation and Systems 2019, 18, 293 -302.
AMA StyleXiaoyu Li, Dazhong Ma, Xuguang Hu, Qiuye Sun. Dynamic Event-triggered Control for Heterogeneous Leader-following Consensus of Multi-agent Systems Based on Input-to-state Stability. International Journal of Control, Automation and Systems. 2019; 18 (2):293-302.
Chicago/Turabian StyleXiaoyu Li; Dazhong Ma; Xuguang Hu; Qiuye Sun. 2019. "Dynamic Event-triggered Control for Heterogeneous Leader-following Consensus of Multi-agent Systems Based on Input-to-state Stability." International Journal of Control, Automation and Systems 18, no. 2: 293-302.
This paper investigates the situation awareness issue of power system with massive measured data. To address this issue, first, a graph-theory-based network partitioning algorithm is proposed to realize decentralized detection in a faster response speed, while using power flow characteristics highlights the independency of different groups. Further, a hierarchical event detection method is proposed to judge voltage change and locate event position according to spectral distribution change of established multidimensional matrix. With the proposed method, the system situation can be assessed and the knowledge of the system model is not required. In addition, the accurate result of weak event happened in system could also be obtained. The simulation results are presented to illustrate the effectiveness of the proposed detection method.
Dazhong Ma; Xuguang Hu; Huaguang Zhang; Qiuye Sun; Xiangpeng Xie. A Hierarchical Event Detection Method Based on Spectral Theory of Multidimensional Matrix for Power System. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2019, 51, 2173 -2186.
AMA StyleDazhong Ma, Xuguang Hu, Huaguang Zhang, Qiuye Sun, Xiangpeng Xie. A Hierarchical Event Detection Method Based on Spectral Theory of Multidimensional Matrix for Power System. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2019; 51 (4):2173-2186.
Chicago/Turabian StyleDazhong Ma; Xuguang Hu; Huaguang Zhang; Qiuye Sun; Xiangpeng Xie. 2019. "A Hierarchical Event Detection Method Based on Spectral Theory of Multidimensional Matrix for Power System." IEEE Transactions on Systems, Man, and Cybernetics: Systems 51, no. 4: 2173-2186.
This paper proposes an innovative energy interacting unit (“We-Energy”) with the characteristic of full duplex trading mode. In order to manage all the We-Energies in an optimal way, a new integrated energy management framework based on a noncooperative game is performed so as to allocate the energy demands of each WE such that the benefit of each WE can be maximized. To overcome the impact of the randomness and inaccurate information of renewable energy sources, Nash Q-learning algorithm is applied for computation of game equilibrium under the unknown environment. The novelty of the proposed algorithms is related to the incorporation of the continuous action space into the discrete adaptive action set and combined the equilibrium transfer to improve the efficiency of the algorithm. Simulation studies of modified IMS confirm that it has a better performance with the desired equilibrium strategy and convergence speed.
Lingxiao Yang; Qiuye Sun; Dazhong Ma; Qinglai Wei. Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy. Neurocomputing 2019, 396, 216 -223.
AMA StyleLingxiao Yang, Qiuye Sun, Dazhong Ma, Qinglai Wei. Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy. Neurocomputing. 2019; 396 ():216-223.
Chicago/Turabian StyleLingxiao Yang; Qiuye Sun; Dazhong Ma; Qinglai Wei. 2019. "Nash Q-learning based equilibrium transfer for integrated energy management game with We-Energy." Neurocomputing 396, no. : 216-223.
Dazhong Ma; Junda Wang; Qiuye Sun; Xuguang Hu. A Novel Broad Learning System Based Leakage Detection and Universal Localization Method for Pipeline Networks. IEEE Access 2019, 7, 42343 -42353.
AMA StyleDazhong Ma, Junda Wang, Qiuye Sun, Xuguang Hu. A Novel Broad Learning System Based Leakage Detection and Universal Localization Method for Pipeline Networks. IEEE Access. 2019; 7 ():42343-42353.
Chicago/Turabian StyleDazhong Ma; Junda Wang; Qiuye Sun; Xuguang Hu. 2019. "A Novel Broad Learning System Based Leakage Detection and Universal Localization Method for Pipeline Networks." IEEE Access 7, no. : 42343-42353.
In this paper, Denial-of-Service (DoS) attacks on a microgrid (MG), especially on service-provider-edge routers in the MG, are considered and analysed. To increase the tolerance of the MG for DoS attacks with decreased computing time, we present consensus-based secondary frequency controllers with dynamic P-f droop controllers. Then, with the consideration of the impact on these controllers caused by DoS attacks, a state-space model of the MG is established based on which the stability analysis is derived. Finally, the effectiveness of the method is verified by simulation and experimental results.
Bingyu Wang; Qiuye Sun; Renke Han; Dazhong Ma. Consensus-based secondary frequency control under denial-of-service attacks of distributed generations for microgrids. Journal of the Franklin Institute 2019, 358, 114 -130.
AMA StyleBingyu Wang, Qiuye Sun, Renke Han, Dazhong Ma. Consensus-based secondary frequency control under denial-of-service attacks of distributed generations for microgrids. Journal of the Franklin Institute. 2019; 358 (1):114-130.
Chicago/Turabian StyleBingyu Wang; Qiuye Sun; Renke Han; Dazhong Ma. 2019. "Consensus-based secondary frequency control under denial-of-service attacks of distributed generations for microgrids." Journal of the Franklin Institute 358, no. 1: 114-130.
Recently, the converters controlled by droop controller with phase-locked loop (PLL) were observed in islanded ac microgrids. However, only state-space-based approach was applied to investigate the stability of this converter in the previous works. Compared with state-space-based approach, characteristic equation approach has plenty of advantages, such as convenient stability margin analysis (Phase Margin, Gain Margin, and so on) and simply stability criterion (Routh Criterion). Thus, a novel small-signal modeling approach based on characteristic equation for converter-dominated ac microgrids is proposed to assess the system low-frequency stability in this paper. Firstly, considering zero-order holder (ZOH) and time delay, the smallsignal characteristic equation of this converter is presented by Padé approximation and dynamic phasor model. Furthermore, the implementation and parameter design of the converters are studied under the practical considerations. Compared with the existing characteristic equation methods, the proposed approach can be verified that the performance is significantly improved. Eventually, simulations and experimental results are presented, indicating that the proposed approach can assess the system lowfrequency stability conveniently and accurately.
Rui Wang; Qiuye Sun; Dazhong Ma; Zhenwei Liu. The Small-Signal Stability Analysis of the Droop-Controlled Converter in Electromagnetic Timescale. IEEE Transactions on Sustainable Energy 2019, 10, 1459 -1469.
AMA StyleRui Wang, Qiuye Sun, Dazhong Ma, Zhenwei Liu. The Small-Signal Stability Analysis of the Droop-Controlled Converter in Electromagnetic Timescale. IEEE Transactions on Sustainable Energy. 2019; 10 (3):1459-1469.
Chicago/Turabian StyleRui Wang; Qiuye Sun; Dazhong Ma; Zhenwei Liu. 2019. "The Small-Signal Stability Analysis of the Droop-Controlled Converter in Electromagnetic Timescale." IEEE Transactions on Sustainable Energy 10, no. 3: 1459-1469.