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With the rapid applications of communication technology, the hierarchical control of microgrids is threatened by unprecedented cyber attacks and faults. Current researches seldom study the impact on the control of cyber failures and their defense strategies. In this research, an economic control method modified from the traditional droop control is proposed. It requires distributed generators (DGs) to exchange corresponding information through a communication network, which may face potential risks of false data injection attacks (FDIAs). To tackle it, an attack-resilient method (ARM), modified from the weighted mean subsequence reduced (WMSR) algorithm, is proposed. It is proved that the successful attack-resistance and convergence performance require the communication topology to satisfy (r+1)-robust, using the graph theory. By employing the TrueTime2.0 toolbox of MATLAB/Simulink, simulations of two microgrid test systems are performed. Results verify the feasibility and effectiveness of the proposed method on economic control under FDIAs.
Wenhao Zhang; Tong Qian; Xingyu Chen; Kecan Huang; Wenhu Tang; Qinghua Wu. Resilient Economic Control for Distributed Microgrids Under False Data Injection Attacks. IEEE Transactions on Smart Grid 2021, 12, 4435 -4446.
AMA StyleWenhao Zhang, Tong Qian, Xingyu Chen, Kecan Huang, Wenhu Tang, Qinghua Wu. Resilient Economic Control for Distributed Microgrids Under False Data Injection Attacks. IEEE Transactions on Smart Grid. 2021; 12 (5):4435-4446.
Chicago/Turabian StyleWenhao Zhang; Tong Qian; Xingyu Chen; Kecan Huang; Wenhu Tang; Qinghua Wu. 2021. "Resilient Economic Control for Distributed Microgrids Under False Data Injection Attacks." IEEE Transactions on Smart Grid 12, no. 5: 4435-4446.
In offshore wind farms, reignition overvoltages are usually caused by switching-off operations of vacuum circuit breakers, which degrade the insulation of power equipment, especially transformers. This paper proposes a new quantitative evaluation method of overvoltage suppression measures comprehensively considering three main indicators, which include the amplitude, steepness and reignition number. Based on the quantitative evaluation results, an improved suppression measure against high-steepness reignition overvoltages is developed. Firstly, high-frequency transient models of main components of a typical wind farm are developed in PSCAD/EMTDC. Then the stochasticity of opening instants is considered, and three main indicators are extracted for comprehensively analyzing the transient characteristics of reignition overvoltages. Subsequently, a quantitative evaluation is performed to analyze the effectiveness of different suppression measures, which involves surge arresters, RC snubbers and smart chokes with different properties and installation positions. Results show that a new combination of a surge arrester and a smart choke is capable of providing sufficient protection against a high-amplitude, high-steepness and severe-reignitions overvoltage. This research can provide a new overvoltage suppression solution for insulation coordination in offshore wind farms.
Yanli Xin; Boning Zhao; Qiheng Liang; Jiujiang Zhou; Tong Qian; Zeyuan Yu; Wenhu Tang. Development of Improved Suppression Measures Against Reignition Overvoltages Caused by Vacuum Circuit Breakers in Offshore Wind Farms. IEEE Transactions on Power Delivery 2021, PP, 1 -1.
AMA StyleYanli Xin, Boning Zhao, Qiheng Liang, Jiujiang Zhou, Tong Qian, Zeyuan Yu, Wenhu Tang. Development of Improved Suppression Measures Against Reignition Overvoltages Caused by Vacuum Circuit Breakers in Offshore Wind Farms. IEEE Transactions on Power Delivery. 2021; PP (99):1-1.
Chicago/Turabian StyleYanli Xin; Boning Zhao; Qiheng Liang; Jiujiang Zhou; Tong Qian; Zeyuan Yu; Wenhu Tang. 2021. "Development of Improved Suppression Measures Against Reignition Overvoltages Caused by Vacuum Circuit Breakers in Offshore Wind Farms." IEEE Transactions on Power Delivery PP, no. 99: 1-1.
With the integration of large-scale distributed renewable energy, the model of active distribution network (ADN) becomes more complicated. This paper proposes an equivalent ADN model considering the uncertainties of wind turbines, photovoltaic (PV) systems and loads. The model output is composed of deterministic and uncertain components. First, the model of wind turbines, PV systems and loads are developed to describe the deterministic components and the Gaussian probability density model is used to describe the uncertain components. Then, model parameters are optimized using a reinforcement learning algorithm to track the time-varying equivalent wind turbines, PV systems and loads. Finally, case studies are carried out on a 63-bus distribution network. Simulation results demonstrate that errors of power flow calculation of the equivalent ADN model are reduced in the case that the uncertainties of wind turbines, PV systems and loads are considered.
Qianlong Wei; Jiehui Zheng; Wenhu Tang; Q. H. Wu. Equivalent Model of Active Distribution Network Considering Uncertainties of Wind Turbines, Photovoltaics and Loads. IOP Conference Series: Earth and Environmental Science 2021, 645, 012086 .
AMA StyleQianlong Wei, Jiehui Zheng, Wenhu Tang, Q. H. Wu. Equivalent Model of Active Distribution Network Considering Uncertainties of Wind Turbines, Photovoltaics and Loads. IOP Conference Series: Earth and Environmental Science. 2021; 645 (1):012086.
Chicago/Turabian StyleQianlong Wei; Jiehui Zheng; Wenhu Tang; Q. H. Wu. 2021. "Equivalent Model of Active Distribution Network Considering Uncertainties of Wind Turbines, Photovoltaics and Loads." IOP Conference Series: Earth and Environmental Science 645, no. 1: 012086.
The use of a wireless power transmission system (WPTS) in modern applications, such as consumer electronics, renewable energy sources (RESs) and electric vehicles (EVs), can significantly increase the safety and convenience of the power supply. However, low efficiency is a major hurdle to the use of a WPTS in these applications. In this article, an adaptive virtual impedance controller (AVIC) is presented to enhance the wireless power transfer (WPT) efficiency of a photovoltaic generator (PVG) to the load. In the proposed controller, a unique method is employed to adaptively estimate the coefficient of coupling and resonant frequency of the WPTS coils as a function of the distance between the coils. Moreover, a modified incremental conductance (IC) based maximum power tracking (MIC-MPPT) technique is presented to operate the PVG at MPPT mode. The proposed MIC-MPPT is tested via a hardware prototype and the controller validation is carried out in the MATLAB/SIMULINK environment under various uncertainties, such as intermittent irradiance, variable load, and the distance between transmitter (Tx) and receiver (Rx) coils. Finally, a comparative analysis between the proposed controller and the conventional non-adaptive and adaptive resonant frequency controller is presented which confirms the superiority of the proposed controller.
Ali Mahdi; Shah Fahad; Wenhu Tang. An Adaptive Current Limiting Controller for a Wireless Power Transmission System Energized by a PV Generator. Electronics 2020, 9, 1648 .
AMA StyleAli Mahdi, Shah Fahad, Wenhu Tang. An Adaptive Current Limiting Controller for a Wireless Power Transmission System Energized by a PV Generator. Electronics. 2020; 9 (10):1648.
Chicago/Turabian StyleAli Mahdi; Shah Fahad; Wenhu Tang. 2020. "An Adaptive Current Limiting Controller for a Wireless Power Transmission System Energized by a PV Generator." Electronics 9, no. 10: 1648.
The fourth industrial revolution – Industry 4.0 – puts emphasis on the application of intelligent technologies in the area of monitoring and identification of electrical equipment. High precision and non-contact qualities make the infrared thermography one of the most suitable technologies for intelligent inspection of high-voltage apparatus. Yet, due to imperfect data acquisition methods and difficulties in collecting data, electrical equipment images are limited in quantities and imbalanced in representing different types of devices. Additionally, it is not easy to extract representative features of infrared images due to their low-intensity contrast and uneven distribution. In this paper, a data-driven framework is proposed for the identification of electrical equipment based on infrared images. The main technique of this proposed system is a novel process of generating synthetic infrared images. For this purpose, an Edge-Oriented Generative Adversarial Network (EOGAN) is developed. The EOGAN is designed to create realistic infrared images that can be used as augmented data for developing data-driven identification methods. Extracted edge features of electrical equipment are utilized as prior information to guide the process of generating realistic infrared images. Finally, comparative experiments are carried out to show the effectiveness of the proposed EOGAN-based framework for equipment identification in the presence of limited and imbalanced image datasets.
Zhewen Niu; Marek Z. Reformat; Wenhu Tang; Baining Zhao. Electrical Equipment Identification Method With Synthetic Data Using Edge-Oriented Generative Adversarial Network. IEEE Access 2020, 8, 136487 -136497.
AMA StyleZhewen Niu, Marek Z. Reformat, Wenhu Tang, Baining Zhao. Electrical Equipment Identification Method With Synthetic Data Using Edge-Oriented Generative Adversarial Network. IEEE Access. 2020; 8 (99):136487-136497.
Chicago/Turabian StyleZhewen Niu; Marek Z. Reformat; Wenhu Tang; Baining Zhao. 2020. "Electrical Equipment Identification Method With Synthetic Data Using Edge-Oriented Generative Adversarial Network." IEEE Access 8, no. 99: 136487-136497.
The analysis of the fault propagation path of transmission lines and the method of identification of vulnerable lines during typhoon weather conditions is of great significance. In this context, this paper introduces the failure probability model of transmission lines under such conditions by considering both wind speed and the load of the lines. The Monte Carlo simulation (MCS) and the DC model based on OPA are applied to simulate the failure of transmission lines. The cascading failure state transition diagram (CFSTD) is proposed based on the failure chains and the criticality ranking of nodes in CFSTD by the average weight coefficient (AWC) for identifying vulnerable lines of the power grid under such conditions. A new weight in CFSTD is proposed to describe the vulnerability of each line and a new resilience index is used to assess the impacts of a typhoon on the system. The proposed method is demonstrated by using the modified IEEE 118-bus test system. Results show that the method proposed in this paper can simulate the fault propagation path, and identify the critical components of power grid under a typhoon.
Jun Guo; Tao Feng; Zelin Cai; Xianglong Lian; Wenhu Tang. Vulnerability Assessment for Power Transmission Lines under Typhoon Weather Based on a Cascading Failure State Transition Diagram. Energies 2020, 13, 3681 .
AMA StyleJun Guo, Tao Feng, Zelin Cai, Xianglong Lian, Wenhu Tang. Vulnerability Assessment for Power Transmission Lines under Typhoon Weather Based on a Cascading Failure State Transition Diagram. Energies. 2020; 13 (14):3681.
Chicago/Turabian StyleJun Guo; Tao Feng; Zelin Cai; Xianglong Lian; Wenhu Tang. 2020. "Vulnerability Assessment for Power Transmission Lines under Typhoon Weather Based on a Cascading Failure State Transition Diagram." Energies 13, no. 14: 3681.
Electricity theft is the main reason for non-technical losses (NTL) in distribution networks, which can lead to great economic losses in power supply enterprises. Efficient and accurate detection of abnormal power consumption patterns is a key part of demand side management. With the popular use of smart meters, it is more efficient and reliable to collect customers’ power consumption data, which make on-line monitoring of power consumption possible. In this paper, a detection algorithm based on local matrix reconstruction (LMR) is proposed and utilized to detect abnormal power consumption patterns in power systems. In this algorithm, five daily load characteristics are used to replace high-dimensional daily load curves to characterize power consumption patterns. Then, principal component analysis (PCA) is applied to calculate weighted reconstruction errors in a local scope. The reconstruction error of each sample is compared with its adjacent samples in order to calculate local outlier scores, which represent the abnormal degree of each load sample. Using two open source datasets, the detection performance of the proposed method is verified to be effective and efficient.
Zhiying Feng; Jingjing Huang; W.H. Tang; Mohammad Shahidehpour. Data mining for abnormal power consumption pattern detection based on local matrix reconstruction. International Journal of Electrical Power & Energy Systems 2020, 123, 106315 .
AMA StyleZhiying Feng, Jingjing Huang, W.H. Tang, Mohammad Shahidehpour. Data mining for abnormal power consumption pattern detection based on local matrix reconstruction. International Journal of Electrical Power & Energy Systems. 2020; 123 ():106315.
Chicago/Turabian StyleZhiying Feng; Jingjing Huang; W.H. Tang; Mohammad Shahidehpour. 2020. "Data mining for abnormal power consumption pattern detection based on local matrix reconstruction." International Journal of Electrical Power & Energy Systems 123, no. : 106315.
The previously developed control methods based on the conservation of energy in circuits require the accurate estimation of energy losses, which is difficult to measure and calculate for boost converters. Consequently, there always exist steady-state errors in the output voltage if neglecting such circuit energy losses. To address this issue, an improved energy balance control (IEBC) method is proposed in this paper by integrating a simplified energy balance controller (SEBC) with a PI controller. The proposed IEBC can reduce the steady-state output voltage errors without requiring the estimation of circuit energy losses. Furthermore, the proposed IEBC can operate in both the continuous current mode (CCM) and the discontinuous current mode (DCM), thus accurate static and fast dynamic performances are achieved over the entire load operation range. Moreover, the stability of the IEBC is proved using the Lyapunov stability criterion. Compared with that of the SEBC, both simulations and experiments validate the feasibility and robustness of the proposed IEBC method.
Lei Wang; Qinghua Wu; Wenhu Tang. Improved Energy Balance Control for Boost Converters Without Estimating Circuit Energy Losses. IEEE Access 2020, 8, 146323 -146330.
AMA StyleLei Wang, Qinghua Wu, Wenhu Tang. Improved Energy Balance Control for Boost Converters Without Estimating Circuit Energy Losses. IEEE Access. 2020; 8 (99):146323-146330.
Chicago/Turabian StyleLei Wang; Qinghua Wu; Wenhu Tang. 2020. "Improved Energy Balance Control for Boost Converters Without Estimating Circuit Energy Losses." IEEE Access 8, no. 99: 146323-146330.
Vacuum circuit breakers may cause severe reignition overvoltage when switching off inductive loads, which may cause damage to other equipment connected with them, especially in the offshore wind farm power collection system. In order to study this process, a 35 kV electrical system was built in a laboratory platform, and the reignition overvoltage was recorded and analyzed. The measurements were used to improve the vacuum circuit breaker model. The parameters of dielectric strength of a 40.5 kV vacuum circuit breaker model were discussed in this publication. Then, a simulation model based on the experimental system was established using PSCAD/EMTDC. The reignition breakdown voltage across vacuum circuit breakers and the voltage at the high-voltage side of the connected transformer were equal, and the reason was explained according to the theory of wave propagation. Surge arresters and RC snubber are often used for overvoltage suppression, and the different configurations of them were evaluated. Finally, the efficiency of overvoltage suppression was compared both in the time domain and energy spectral density based on the simulation results.
Yaxun Guo; Xiaofeng Jiang; Yun Chen; Ming Zheng; Gang Liu; Xiaohua Li; Wenhu Tang. Reignition overvoltages induced by vacuum circuit breakers and its suppression in offshore wind farms. International Journal of Electrical Power & Energy Systems 2020, 122, 106227 .
AMA StyleYaxun Guo, Xiaofeng Jiang, Yun Chen, Ming Zheng, Gang Liu, Xiaohua Li, Wenhu Tang. Reignition overvoltages induced by vacuum circuit breakers and its suppression in offshore wind farms. International Journal of Electrical Power & Energy Systems. 2020; 122 ():106227.
Chicago/Turabian StyleYaxun Guo; Xiaofeng Jiang; Yun Chen; Ming Zheng; Gang Liu; Xiaohua Li; Wenhu Tang. 2020. "Reignition overvoltages induced by vacuum circuit breakers and its suppression in offshore wind farms." International Journal of Electrical Power & Energy Systems 122, no. : 106227.
The global-based and partition-based dynamic power dispatch problems with wind power integrated into the carbon emission trading system are established and investigated. To meet this challenge, a distributed dual consensus algorithm based the alternating direction method of multipliers is implemented by sharing Lagrangian multipliers associated with coupling constraints between partitioned subproblems rather than phase angles on adjacent buses that are usually shared, thus protecting the key private information of each subsystem. Furthermore, a fully decentralized algorithm is proposed by adopting the finite-time average consensus algorithm, which enables each partition to iteratively approach a consensus of its shared information in a finite number of steps. For comparison purposes, a global-based centralized optimization is implemented at first, adopting the effect of carbon price on the operation of a modified IEEE-30 bus system, followed by tests of the proposed algorithms with three different partitioning methods of power systems. Results illustrate that a higher carbon price can be regarded as an incentive to decrease the wind curtailment rates and spur the increased use of clean fuel. Compared with the results of the centralized optimization, both the algorithms can achieve satisfactory convergence accuracies, although the fully decentralized algorithm requires slightly longer time for computation.
Tong Qian; Wenhu Tang; Qinghua Wu. A fully decentralized dual consensus method for carbon trading power dispatch with wind power. Energy 2020, 203, 117634 .
AMA StyleTong Qian, Wenhu Tang, Qinghua Wu. A fully decentralized dual consensus method for carbon trading power dispatch with wind power. Energy. 2020; 203 ():117634.
Chicago/Turabian StyleTong Qian; Wenhu Tang; Qinghua Wu. 2020. "A fully decentralized dual consensus method for carbon trading power dispatch with wind power." Energy 203, no. : 117634.
Wind power forecasting (WPF) plays an increasingly essential role in power system operations. So far, most forecasting models have focused on a single-step-ahead WPF, and the obtained results are insufficient for planning and operations of the power system due to the intermittent and fluctuated nature of wind. At the same time, most of the current multi-step-ahead WPF models neglect the correlation between different forecasting tasks. In this paper, we propose a novel sequence-to-sequence model using the Attention-based Gated Recurrent Unit (AGRU) that improves accuracy of forecasting processes. It embeds the task of correlating different forecasting steps by hidden activations of GRU blocks. In addition, an attention mechanism is designed as a feature selection method to identify the most important input variables. To validate the effectiveness of the proposed AGRU model, three different case studies focused on forecasting accuracy, computational efficiency, and feature selection abilities are carried out. Their performances are compared with various wind power forecasting benchmarks.
Zhewen Niu; Zeyuan Yu; Wenhu Tang; Qinghua Wu; Marek Reformat. Wind power forecasting using attention-based gated recurrent unit network. Energy 2020, 196, 117081 .
AMA StyleZhewen Niu, Zeyuan Yu, Wenhu Tang, Qinghua Wu, Marek Reformat. Wind power forecasting using attention-based gated recurrent unit network. Energy. 2020; 196 ():117081.
Chicago/Turabian StyleZhewen Niu; Zeyuan Yu; Wenhu Tang; Qinghua Wu; Marek Reformat. 2020. "Wind power forecasting using attention-based gated recurrent unit network." Energy 196, no. : 117081.
Wenhu Tang; Xingyu Chen; Tong Qian; Gang Liu; Mengshi Li; Licheng Li. Technologies and Applications of Digital Twin for Developing Smart Energy Systems. Chinese Journal of Engineering Science 2020, 22, 74 -85.
AMA StyleWenhu Tang, Xingyu Chen, Tong Qian, Gang Liu, Mengshi Li, Licheng Li. Technologies and Applications of Digital Twin for Developing Smart Energy Systems. Chinese Journal of Engineering Science. 2020; 22 (4):74-85.
Chicago/Turabian StyleWenhu Tang; Xingyu Chen; Tong Qian; Gang Liu; Mengshi Li; Licheng Li. 2020. "Technologies and Applications of Digital Twin for Developing Smart Energy Systems." Chinese Journal of Engineering Science 22, no. 4: 74-85.
For the study of transient overvoltage (TOV) in an offshore wind farm (OWF) collector system caused by switching off vacuum circuit breakers (VCBs), a simplified experimental platform of OWF medium-voltage (MV) cable collector system was established in this paper to conduct switching operation tests of VCB and obtain the characteristic parameters for VCB, especially dielectric strength parameters; also, the effectiveness of the VCB reignition model was verified. Then, PSCAD/EMTDC was used to construct the MV collector system of the OWF, and the effects of normal switching and fault switching on TOV amplitude, steepness, and the total number of reignition of the VCB were studied, respectively, with the experimental parameters and traditional parameters of dielectric strength of the VCB. The simulation results show that when the VCB is at the tower bottom, the overvoltage amplitude generated by the normal switching is the largest, which is 1.83 p.u., and the overvoltage steepness of the fault switching is the largest, up to 142 kV/μs. The overvoltage amplitude and steepness caused by switching off VCB at the tower bottom faultily with traditional parameters are about 2 and 1.5 times of the experimental parameters under the same operating condition.
Zikai Zhou; Yaxun Guo; Xiaofeng Jiang; Gang Liu; Wenhu Tang; Honglei Deng; Xiaohua Li; Ming Zheng. Study on Transient Overvoltage of Offshore Wind Farm Considering Different Electrical Characteristics of Vacuum Circuit Breaker. Journal of Marine Science and Engineering 2019, 7, 415 .
AMA StyleZikai Zhou, Yaxun Guo, Xiaofeng Jiang, Gang Liu, Wenhu Tang, Honglei Deng, Xiaohua Li, Ming Zheng. Study on Transient Overvoltage of Offshore Wind Farm Considering Different Electrical Characteristics of Vacuum Circuit Breaker. Journal of Marine Science and Engineering. 2019; 7 (11):415.
Chicago/Turabian StyleZikai Zhou; Yaxun Guo; Xiaofeng Jiang; Gang Liu; Wenhu Tang; Honglei Deng; Xiaohua Li; Ming Zheng. 2019. "Study on Transient Overvoltage of Offshore Wind Farm Considering Different Electrical Characteristics of Vacuum Circuit Breaker." Journal of Marine Science and Engineering 7, no. 11: 415.
This study proposes a cooperative secondary voltage and frequency control strategy to reduce the number of controller updates by using an event-triggered approach. The proposed approach is applied to the secondary control that will offset primary control deviations in islanded microgrids with limited computation resources. The controller updating mechanism considered here is event-triggered which judges whether a certain measurement error has reached the event-triggered condition (ETC) associated with the norm of a function with a standard state. We consider two secondary control options to form an ETC, which include a centralized strategy in which an auxiliary controller would collect all agents’ states, and a distributed control strategy which only require the neighboring agents information. The corresponding stability and convergence analyses are presented and simulation results for an islanded microgrid test system consisting of four distributed generators (DGs) are provided. The simulation results validate the effectiveness of the proposed control strategies and show that the proposed strategies based on an event-triggered approach can dramatically reduce controller updates.
Tong Qian; Yang Liu; Wenhao Zhang; W. H. Tang; Mohammad Shahidehpour. Event-Triggered Updating Method in Centralized and Distributed Secondary Controls for Islanded Microgrid Restoration. IEEE Transactions on Smart Grid 2019, 11, 1387 -1395.
AMA StyleTong Qian, Yang Liu, Wenhao Zhang, W. H. Tang, Mohammad Shahidehpour. Event-Triggered Updating Method in Centralized and Distributed Secondary Controls for Islanded Microgrid Restoration. IEEE Transactions on Smart Grid. 2019; 11 (2):1387-1395.
Chicago/Turabian StyleTong Qian; Yang Liu; Wenhao Zhang; W. H. Tang; Mohammad Shahidehpour. 2019. "Event-Triggered Updating Method in Centralized and Distributed Secondary Controls for Islanded Microgrid Restoration." IEEE Transactions on Smart Grid 11, no. 2: 1387-1395.
This paper investigates the impact factors of switching transient overvoltage (SOV) in an offshore wind farm (OWF) by analyzing multiple ignitions of a vacuum circuit breaker. The statistical features of transient overvoltages, which occur under real switching operation scenarios, are analyzed based on measurements in a laboratory platform, which is built according to the configuration of an actual OWF. Next, an OWF simulation transient model is established considering high frequency characteristics of circuit breakers, which is verified to be able to calculate the SOV accurately. Based on the developed OWF simulation model, the occurrence mechanism of SOV is discussed in detail by studying characteristics of transient voltage and current during multiple ignitions within a vacuum circuit breaker, when it is switched off. Then, key impact factors of switching-off induced overvoltage are identified, which include the inter-phase capacitance of cable in a windmill tower, the actual operating capacity of a wind turbine generator, and the single-phase inlet capacitance in terminals of a wind turbine transformer. Finally, the recommended configurations are given for transient mitigation in an OWF.
Jiujiang Zhou; Yanli Xin; Wenhu Tang; Gang Liu; Qinghua Wu. Impact Factor Identification for Switching Overvoltage in an Offshore Wind Farm by Analyzing Multiple Ignition Transients. IEEE Access 2019, 7, 64651 -64662.
AMA StyleJiujiang Zhou, Yanli Xin, Wenhu Tang, Gang Liu, Qinghua Wu. Impact Factor Identification for Switching Overvoltage in an Offshore Wind Farm by Analyzing Multiple Ignition Transients. IEEE Access. 2019; 7 (99):64651-64662.
Chicago/Turabian StyleJiujiang Zhou; Yanli Xin; Wenhu Tang; Gang Liu; Qinghua Wu. 2019. "Impact Factor Identification for Switching Overvoltage in an Offshore Wind Farm by Analyzing Multiple Ignition Transients." IEEE Access 7, no. 99: 64651-64662.
This paper investigates the characteristics of reignition overvoltage of vacuum circuit breaker, and analyzes the influences of reignition overvoltage on a power collection grid in offshore wind farms. An offshore wind farm model, including an opening model of VCB, is developed based on a parameter fitting method in PSCAD/EMTDC, which is experimentally validated covering main offshore wind farm components. The established laboratory experiment setup comprises vacuum circuit breakers, cables, transformers and equivalent equipment of a wind turbine. The experiment reignition overvoltages and currents are recorded to analyze its transient behavior, contributing to understanding the occurrence mechanisms of reignition overvoltages in offshore wind farms. Moreover, a sensitivity analysis is performed to identify factors affecting reignition overvoltages based on the developed simulation model. The statistical result analysis indicates that four out of seven investigated factors (including the capacitance (stray capacitance and cable length), the rate of rise of dielectric strength and the opening phase angle of vacuum circuit breaker) have remarkable influences on reignition overvoltages of offshore wind farms.
Y.L. Xin; W.H. Tang; J.J. Zhou; Y.H. Yang; G. Liu. Sensitivity analysis of reignition overvoltage for vacuum circuit breaker in offshore wind farm using experiment-based modeling. Electric Power Systems Research 2019, 172, 86 -95.
AMA StyleY.L. Xin, W.H. Tang, J.J. Zhou, Y.H. Yang, G. Liu. Sensitivity analysis of reignition overvoltage for vacuum circuit breaker in offshore wind farm using experiment-based modeling. Electric Power Systems Research. 2019; 172 ():86-95.
Chicago/Turabian StyleY.L. Xin; W.H. Tang; J.J. Zhou; Y.H. Yang; G. Liu. 2019. "Sensitivity analysis of reignition overvoltage for vacuum circuit breaker in offshore wind farm using experiment-based modeling." Electric Power Systems Research 172, no. : 86-95.
Daily peak load forecasting is an essential tool for decision making in power system operation and planning. However, the daily peak load is a nonlinear, nonstationary and volatile time series, which makes it difficult to be forecasted accurately. This paper, for the first time, proposes a bespoke gated recurrent neural network combining dynamic time warping (DTW) for accurate daily peak load forecasting. The shape-based DTW distance is used to match the most similar load curve, which can capture trends in load changes. By analyzing the relationship between the load curve and the cycle of human social activities, the some-hot encoding scheme is firstly applied on the discrete variables to expand the features to further characterize their impact on load curves. Then a 3-layer gated recurrent neural network is developed to forecast daily peak load. The proposed algorithm is implemented on the Theano deep learning platform and tested on the load dataset of the European Network on Intelligent Technologies (EUNITE). The simulation results show that the proposed algorithm achieves satisfactory results compared with other algorithms using the same dataset in this study
Zeyuan Yu; Zhewen Niu; Wenhu Tang; Qinghua Wu. Deep Learning for Daily Peak Load Forecasting–A Novel Gated Recurrent Neural Network Combining Dynamic Time Warping. IEEE Access 2019, 7, 17184 -17194.
AMA StyleZeyuan Yu, Zhewen Niu, Wenhu Tang, Qinghua Wu. Deep Learning for Daily Peak Load Forecasting–A Novel Gated Recurrent Neural Network Combining Dynamic Time Warping. IEEE Access. 2019; 7 (99):17184-17194.
Chicago/Turabian StyleZeyuan Yu; Zhewen Niu; Wenhu Tang; Qinghua Wu. 2019. "Deep Learning for Daily Peak Load Forecasting–A Novel Gated Recurrent Neural Network Combining Dynamic Time Warping." IEEE Access 7, no. 99: 17184-17194.
This paper investigates the switching transient overvoltage (SOV) in an offshore wind farm (OWF) based on the measurements on an established laboratory experiment platform. The transient voltage under different vacuum circuit breaker (VCB) operation sceneries is measured, in which the measurement positions include: the terminal of wind turbine transformer (WTT), the source side of WTG VCB, and the load side of WTT. Then the feature and occurrence causes of the SOV are analyzed by revealing the variation characteristics of the transient voltage and current. To explore the mitigation effect of this SOV when protection devices are used, an OWF high frequency model considering the pre-strike and re-ignition characteristics of VCB is built in PSCAD/EMTDC and verified by the measured results. Finally, the SOV in an OWF, when the arrester and the RC Snubber are used, are obtained based on the self-defined simulation model. Additionally, the mitigation effects and their advantages and disadvantages are compared as well.
Jiujiang Zhou; Wenhu Tang; Yanli Xin; Qinghua Wu. Investigation on Switching Overvoltage in an Offshore Wind Farm and Its Mitigation Methods Based on Laboratory Experiments. 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) 2018, 189 -193.
AMA StyleJiujiang Zhou, Wenhu Tang, Yanli Xin, Qinghua Wu. Investigation on Switching Overvoltage in an Offshore Wind Farm and Its Mitigation Methods Based on Laboratory Experiments. 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). 2018; ():189-193.
Chicago/Turabian StyleJiujiang Zhou; Wenhu Tang; Yanli Xin; Qinghua Wu. 2018. "Investigation on Switching Overvoltage in an Offshore Wind Farm and Its Mitigation Methods Based on Laboratory Experiments." 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) , no. : 189-193.
Ice disasters have frequently occurred worldwide in recent years, which seriously affected power transmission system operations. To improve the resilience of power grids and minimize economic losses, this paper proposes a framework for assessing the influence of ice disasters on the resilience of power transmission systems. This method considers the spatial–temporal impact of ice disasters on the resilience of power transmission systems, and the contingence set for risk assessment is established according to contingency probabilities. Based on meteorological data, the outage models of power transmission components are developed in the form of generic fragility curves, and the ice load is given by a simplified freezing rain ice model. A cell partition method is adopted to analyze the way ice disasters affect the operation of power transmission systems. The sequential Monte Carlo simulation method is used to assess resilience for capturing the stochastic impact of ice disasters and deriving the contingency set. Finally, the IEEE RTS-79 system is employed to investigate the impact of ice disasters by two case studies, which demonstrate the viability and effectiveness of the proposed framework. In turn, the results help recognize the resilience of the system under such disasters and the effects of different resilience enhancement measures.
Jiazheng Lu; Jun Guo; Zhou Jian; Yihao Yang; Wenhu Tang. Resilience Assessment and Its Enhancement in Tackling Adverse Impact of Ice Disasters for Power Transmission Systems. Energies 2018, 11, 2272 .
AMA StyleJiazheng Lu, Jun Guo, Zhou Jian, Yihao Yang, Wenhu Tang. Resilience Assessment and Its Enhancement in Tackling Adverse Impact of Ice Disasters for Power Transmission Systems. Energies. 2018; 11 (9):2272.
Chicago/Turabian StyleJiazheng Lu; Jun Guo; Zhou Jian; Yihao Yang; Wenhu Tang. 2018. "Resilience Assessment and Its Enhancement in Tackling Adverse Impact of Ice Disasters for Power Transmission Systems." Energies 11, no. 9: 2272.
Reliable power grids are also vulnerable to extreme events, which are with a low probability but highly risk events, such as a typhoon. Power system, as an important infrastructure, should have the ability to withstand the adverse effect of such extreme events. This paper proposes a quantitative resilience assessment framework for power transmission systems operated under typhoon weather, which considers both the spatial and temporal impacts of typhoon. The proposed framework allows systematic estimation of resilience considering weather intensity, fault location of components, restoration resources, and emergency response plans. The typhoon wind field model for disaster risk assessment is applied to evaluate the intensity and the duration of impacts. The finite element modeling of components is developed to model the outage probability of components. A new resilience index considering the duration of extreme events (RICD) is proposed, which not only considers the performance of system but also considers characteristics of disruption. The proposed method is demonstrated by four case studies using the modified IEEE 6-bus test system. The numerical results reveal that the proposed method is able to quantify the influence of extreme event on power system resilience, and it shows that RICD is more feasible than two traditional indices in terms of normalization and comparability.
Yihao Yang; Wenhu Tang; Yang Liu; Yanli Xin; Qinghua Wu. Quantitative Resilience Assessment for Power Transmission Systems Under Typhoon Weather. IEEE Access 2018, 6, 40747 -40756.
AMA StyleYihao Yang, Wenhu Tang, Yang Liu, Yanli Xin, Qinghua Wu. Quantitative Resilience Assessment for Power Transmission Systems Under Typhoon Weather. IEEE Access. 2018; 6 ():40747-40756.
Chicago/Turabian StyleYihao Yang; Wenhu Tang; Yang Liu; Yanli Xin; Qinghua Wu. 2018. "Quantitative Resilience Assessment for Power Transmission Systems Under Typhoon Weather." IEEE Access 6, no. : 40747-40756.