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Weikang Wang
Electrical Engineering and Computer Science, University of Tennessee Knoxville, 4292 Knoxville, Tennessee, United States

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Journal article
Published: 24 June 2021 in IEEE Transactions on Power Systems
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Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. The proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

ACS Style

Shengyuan Liu; Shutang You; Z.Z. Lin; Chujie Zeng; Hongyu Li; Weikang Wang; Xuetao Hu; Yilu Liu. Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees. IEEE Transactions on Power Systems 2021, PP, 1 -1.

AMA Style

Shengyuan Liu, Shutang You, Z.Z. Lin, Chujie Zeng, Hongyu Li, Weikang Wang, Xuetao Hu, Yilu Liu. Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees. IEEE Transactions on Power Systems. 2021; PP (99):1-1.

Chicago/Turabian Style

Shengyuan Liu; Shutang You; Z.Z. Lin; Chujie Zeng; Hongyu Li; Weikang Wang; Xuetao Hu; Yilu Liu. 2021. "Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees." IEEE Transactions on Power Systems PP, no. 99: 1-1.

Journal article
Published: 03 March 2021 in IEEE Transactions on Industrial Informatics
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The High Voltage Direct Current (HVDC) intertie has been applied to provide ancillary-services for AC grids, utilizing the real-time feedback from Phasor Measurement Units (PMUs). However, PMU data communication is vulnerable to False Data Injection Attacks (FDIA) due to protocol defects, thus the HVDC ancillary control and system stability will be threatened. To address this issue, this paper proposes a novel HVDC control strategy based on a Hybrid Data-driven (HDD) methodology. The HDD methodology is first proposed to detect the types and duration time of multiple frequency attacks. Specifically, the Hilbert Huang Transform (HHT) is used to decompose the frequency data, using variational mode decomposition (VMD) instead of the traditional empirical mode decomposition, to extract data features. Second, a Multi-kernel Support Vector Machine (MSVM) is proposed to classify the attacked data based on the designed distinctive features from HHT. Meanwhile, the attacking duration time is decided using an unsupervised technique. Third, an HDD-based HVDC ancillary control strategy is established to eliminate the effect of FDIAs on the HVDC frequency response. Comprehensive experiments of HDD-based HVDC ancillary controls under different FDIAs suggest that the proposed HDD could fast and accurately classify the FDIAs, and the HDD-based HVDC ancillary control strategy could significantly suppress the impact of the FDIAs.

ACS Style

Wei Qiu; Kaiqi Sun; Wenxuan Yao; Weikang Wang; Qiu Tang; Yilu Liu. Hybrid Data-Driven Based HVdc Ancillary Control for Multiple Frequency Data Attacks. IEEE Transactions on Industrial Informatics 2021, 17, 8035 -8045.

AMA Style

Wei Qiu, Kaiqi Sun, Wenxuan Yao, Weikang Wang, Qiu Tang, Yilu Liu. Hybrid Data-Driven Based HVdc Ancillary Control for Multiple Frequency Data Attacks. IEEE Transactions on Industrial Informatics. 2021; 17 (12):8035-8045.

Chicago/Turabian Style

Wei Qiu; Kaiqi Sun; Wenxuan Yao; Weikang Wang; Qiu Tang; Yilu Liu. 2021. "Hybrid Data-Driven Based HVdc Ancillary Control for Multiple Frequency Data Attacks." IEEE Transactions on Industrial Informatics 17, no. 12: 8035-8045.

Journal article
Published: 15 February 2021 in IEEE Transactions on Industrial Electronics
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Modern advanced Phasor Measurement Units (PMUs) are developed with ultra-high reporting rates to meet the demand for monitoring the power systems dynamics in detail. Due to the large volume of data, the communication and storage systems are seriously challenged with the presence of Ultra-High-Density (UHD) synchrophasor and Point on Wave (POW) data. Therefore, it is an urgent task to compress the UHD data for more efficient communication and data storage. This paper proposes several methods to compress the synchrophasor and POW data in a lossless manner. First, an Improved-Time-Series-Special Compression (ITSSC) method is proposed to compress the UHD frequency data. Second, a Delta-difference Huffman method is combined with the TSSC algorithm to compress the UHD phase angle data. Finally, a cyclical high-order delta modulation method is proposed to compress the UHD POW data. The proposed models are extensively tested and compared with different existing lossless compression algorithms using the field-collected synchrophasor and POW data at different reporting rates. The results indicate that the proposed algorithms are efficient in performing lossless compression for the UHD synchrophasor and POW data in real time.

ACS Style

Chang Chen; Weikang Wang; Yin He; Lingwei Zhan; Yilu Liu. Real-Time Lossless Compression for Ultra-High-Density Synchrophasor and Point on Wave Data. IEEE Transactions on Industrial Electronics 2021, PP, 1 -1.

AMA Style

Chang Chen, Weikang Wang, Yin He, Lingwei Zhan, Yilu Liu. Real-Time Lossless Compression for Ultra-High-Density Synchrophasor and Point on Wave Data. IEEE Transactions on Industrial Electronics. 2021; PP (99):1-1.

Chicago/Turabian Style

Chang Chen; Weikang Wang; Yin He; Lingwei Zhan; Yilu Liu. 2021. "Real-Time Lossless Compression for Ultra-High-Density Synchrophasor and Point on Wave Data." IEEE Transactions on Industrial Electronics PP, no. 99: 1-1.

Journal article
Published: 11 February 2021 in IEEE Transactions on Power Delivery
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Synchronized Phase Angle Measurement (SPAM) are widely used in power systems in the applications of situational awareness. However, the practical time drift can lead to unexpected angle difference among Synchronized Measurement Devices (SMD) manufactured from various vendors. Moreover, since most of SMDs calculate phase angle via Discrete Fourier Transform based approaches, this issue becomes even worse under the off-nominal frequency condition. To mitigate the impact of practical timing shift, this letter presents a fast method to rectify the SPAM for appropriate alignment. To verify the performance of the proposed method, laboratory and field tests have been conducted by implementing the method in SMDs and phasor data concentrator, respectively. The results demonstrate that the standard deviation of the phase angle differences have significantly decreased to 0.1 order with the adoption of the proposed method.

ACS Style

He Yin; Wenpeng Yu; Wenxuan Yao; Weikang Wang; Wei Qiu; Yilu Liu. Alignment Method for Synchronized Phase Angle Measurement With Presence of Practical Time Shift. IEEE Transactions on Power Delivery 2021, 36, 2234 -2237.

AMA Style

He Yin, Wenpeng Yu, Wenxuan Yao, Weikang Wang, Wei Qiu, Yilu Liu. Alignment Method for Synchronized Phase Angle Measurement With Presence of Practical Time Shift. IEEE Transactions on Power Delivery. 2021; 36 (4):2234-2237.

Chicago/Turabian Style

He Yin; Wenpeng Yu; Wenxuan Yao; Weikang Wang; Wei Qiu; Yilu Liu. 2021. "Alignment Method for Synchronized Phase Angle Measurement With Presence of Practical Time Shift." IEEE Transactions on Power Delivery 36, no. 4: 2234-2237.

Journal article
Published: 04 February 2021 in IEEE Transactions on Industry Applications
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Existing synchronization systems in the power grid, such as Global Positioning System (GPS), are susceptible to temporary or permanent failures due to various unpredictable and uncontrollable factors such as cyber-attack and electromagnetic interferences, thus affecting the accuracy and reliability of generated timing signal. In this paper, a pulsar astronomy-based timing system is proposed to provide an alternative synchronization signal. This clock will offer significant security improvements to power grid applications, such as wide-area monitoring system, which depends on precise timing signal. The hardware and software frameworks are described in detail. First, a high-speed sampling hardware platform is designed to collect signals from radio telescopes. Then a Periodic Pulse Extraction Method (PPEM) with three steps is proposed to process the pulsar signal, including polyphase filterbanks, incoherent de-dispersion, and sliding window folding. Lastly, three experiments are conducted to verify the effectiveness of the frameworks. The generated pulsar timing pulse is presented, and the factors affecting its accuracy are also discussed. The analysis results demonstrate that the pulsar signals can provide high-accurate timing pulses for grid synchronization.

ACS Style

Wei Qiu; He Yin; Liang Zhang; Xiqian Luo; Weikang Wang; Yilu Liu; Wenxuan Yao; Liangwei Zhan; Peter L. Fuhr; Thomas J King. Pulsar Based Timing for Grid Synchronization. IEEE Transactions on Industry Applications 2021, 57, 2067 -2076.

AMA Style

Wei Qiu, He Yin, Liang Zhang, Xiqian Luo, Weikang Wang, Yilu Liu, Wenxuan Yao, Liangwei Zhan, Peter L. Fuhr, Thomas J King. Pulsar Based Timing for Grid Synchronization. IEEE Transactions on Industry Applications. 2021; 57 (3):2067-2076.

Chicago/Turabian Style

Wei Qiu; He Yin; Liang Zhang; Xiqian Luo; Weikang Wang; Yilu Liu; Wenxuan Yao; Liangwei Zhan; Peter L. Fuhr; Thomas J King. 2021. "Pulsar Based Timing for Grid Synchronization." IEEE Transactions on Industry Applications 57, no. 3: 2067-2076.

Journal article
Published: 01 February 2021 in IEEE Access
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Multiple severe forced oscillation events have recently been observed across the North American interconnections and around the world. These forced oscillations have caused power swings, limited power transfer capability, damaged equipment, and persisted indefinitely until the driving source was located and removed. This paper proposes a comprehensive method to mitigate forced oscillations. Once a forced oscillation is detected, a new source location algorithm can be used to locate the source based on the oscillation mode angle without requiring system topology information. If the source cannot be quickly located and removed, a control strategy can be activated to modulate the active power of utility-scale inverter-based battery energy storage systems (BESSs) to reduce the energy of forced oscillations to a safe level and allow sufficient time for locating the exact source. The proposed source location algorithm is validated using measurements collected during the January 11, 2019 forced oscillation event in North America and other actual grid events, while the proposed control strategy is verified using the Eastern Interconnection dynamic model under the replicated January 11, 2019 forced oscillation event. The simulation results demonstrated that the proposed source location algorithm can accurately identify the forced oscillation source, and the proposed control strategy can significantly reduce forced oscillation energy.

ACS Style

Lin Zhu; Wenpeng Yu; Zhihao Jiang; Chengwen Zhang; Yi Zhao; Jiaojiao Dong; Weikang Wang; Yilu Liu; Evangelos Farantatos; Deepak Ramasubramanian; Andrew Arana; Ryan Quint. A Comprehensive Method to Mitigate Forced Oscillations in Large Interconnected Power Grids. IEEE Access 2021, 9, 22503 -22515.

AMA Style

Lin Zhu, Wenpeng Yu, Zhihao Jiang, Chengwen Zhang, Yi Zhao, Jiaojiao Dong, Weikang Wang, Yilu Liu, Evangelos Farantatos, Deepak Ramasubramanian, Andrew Arana, Ryan Quint. A Comprehensive Method to Mitigate Forced Oscillations in Large Interconnected Power Grids. IEEE Access. 2021; 9 ():22503-22515.

Chicago/Turabian Style

Lin Zhu; Wenpeng Yu; Zhihao Jiang; Chengwen Zhang; Yi Zhao; Jiaojiao Dong; Weikang Wang; Yilu Liu; Evangelos Farantatos; Deepak Ramasubramanian; Andrew Arana; Ryan Quint. 2021. "A Comprehensive Method to Mitigate Forced Oscillations in Large Interconnected Power Grids." IEEE Access 9, no. : 22503-22515.

Article
Published: 14 October 2020 in IET Generation, Transmission & Distribution
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High-density synchrophasors provide valuable information for power grid situational awareness, operation and control. Unfortunately, due to factors including communication instability and hardware failure, their data quality can be greatly deteriorated by anomalies. Since the anomalies can impact the performance of the synchrophasor applications, it is of paramount significance to propose a model to detect anomalies in synchrophasor. In this study, a convolutional neural network model is established to detect and classify the anomalies in the synchrophasor measurements. Four types of anomalies observed in actual synchrophasors including erroneous patterns, random spikes, missing points and high-frequency interferences are considered in this study. The proposed model is extensively evaluated via field-collected measurements from the synchrophasor network in Jiangsu grid, China. The superior performance of the proposed model indicates the great potential of using deep learning for the detection of abnormal synchrophasor measurements.

ACS Style

Xianda Deng; Desong Bian; Weikang Wang; Zhihao Jiang; Wenxuan Yao; Wei Qiu; Ning Tong; Di Shi; Yilu Liu. Deep learning model to detect various synchrophasor data anomalies. IET Generation, Transmission & Distribution 2020, 14, 5739 -5745.

AMA Style

Xianda Deng, Desong Bian, Weikang Wang, Zhihao Jiang, Wenxuan Yao, Wei Qiu, Ning Tong, Di Shi, Yilu Liu. Deep learning model to detect various synchrophasor data anomalies. IET Generation, Transmission & Distribution. 2020; 14 (24):5739-5745.

Chicago/Turabian Style

Xianda Deng; Desong Bian; Weikang Wang; Zhihao Jiang; Wenxuan Yao; Wei Qiu; Ning Tong; Di Shi; Yilu Liu. 2020. "Deep learning model to detect various synchrophasor data anomalies." IET Generation, Transmission & Distribution 14, no. 24: 5739-5745.

Review
Published: 25 September 2020 in Sustainability
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Due to the heavy stress on environmental deterioration and the excessive consumption of fossil resources, the transition of global energy from fossil fuel energy to clean energy has significantly accelerated in recent years. The power industry and policymakers in almost all countries are focusing on clean energy development. Thanks to progressive clean energy policies, significant progress in clean energy integration and greenhouse gas reduction has been achieved around the world. However, due to the differences in economic structures, clean energy distributions, and development models, clean energy policy scope, focus, and coverage vary between different countries, states, and utilities. This paper aims at providing a policy review for readers to easily obtain clean energy policy information on various clean energies in the U.S. and some other countries. Firstly, this paper reviews and compares some countries’ clean energy policies on electricity. Then, taking the U.S. as an example, this paper introduces the clean energy policies of some representative states and utilities in the U.S in perspectives of renewable energies, electric vehicles, and energy storage.

ACS Style

Kaiqi Sun; HuangQing Xiao; Shengyuan Liu; Shutang You; Fan Yang; Yuqing Dong; Weikang Wang; Yilu Liu. A Review of Clean Electricity Policies—From Countries to Utilities. Sustainability 2020, 12, 7946 .

AMA Style

Kaiqi Sun, HuangQing Xiao, Shengyuan Liu, Shutang You, Fan Yang, Yuqing Dong, Weikang Wang, Yilu Liu. A Review of Clean Electricity Policies—From Countries to Utilities. Sustainability. 2020; 12 (19):7946.

Chicago/Turabian Style

Kaiqi Sun; HuangQing Xiao; Shengyuan Liu; Shutang You; Fan Yang; Yuqing Dong; Weikang Wang; Yilu Liu. 2020. "A Review of Clean Electricity Policies—From Countries to Utilities." Sustainability 12, no. 19: 7946.

Journal article
Published: 05 August 2020 in IEEE Transactions on Smart Grid
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The synchrophasor data recorded by Phasor Measurement Units (PMUs) plays an increasingly critical role in the regulation and situational awareness of power systems. However, the widely installed PMUs are vulnerable to multiple malicious attacks from cyber hackers during data transmission and storage. To address this problem, a Modified Ensemble Empirical Mode Decomposition (MEEMD) is proposed first to extract the intrinsic mode functions of each Synchrophasor Data Attacks (SDA). The frequency-based adaptive screening criterion embedded in MEEMD is used to eliminate the false intrinsic mode functions. Next, a Multivariate Convolutional Neural Network (MCNN) is proposed to identify multiple SDA by utilizing the extracted intrinsic mode functions and original SDA as input vectors. A fusion block as the main structure of MCNN is also leveraged to increase the diversity of features and compress the model parameters. Integrating MEEMD and MCNN, a framework with automatic feature extraction and multi-source information fusion capability, referred to as Feature Interactive Network (FIN), is proposed to detect multiple SDA. Based on the proposed FIN framework, six types of SDA are explored for the first time using actual synchrophasor data in FNET/Grideye that was collected from different locations in the U.S. Eastern Interconnection. Finally, a large quantity of experiments with different attack strengths are used to evaluate the adaptability and classification performance of the proposed FIN.

ACS Style

Wei Qiu; Qiu Tang; Kunzhi Zhu; Weikang Wang; Yilu Liu; Wenxuan Yao. Detection of Synchrophasor False Data Injection Attack Using Feature Interactive Network. IEEE Transactions on Smart Grid 2020, 12, 659 -670.

AMA Style

Wei Qiu, Qiu Tang, Kunzhi Zhu, Weikang Wang, Yilu Liu, Wenxuan Yao. Detection of Synchrophasor False Data Injection Attack Using Feature Interactive Network. IEEE Transactions on Smart Grid. 2020; 12 (1):659-670.

Chicago/Turabian Style

Wei Qiu; Qiu Tang; Kunzhi Zhu; Weikang Wang; Yilu Liu; Wenxuan Yao. 2020. "Detection of Synchrophasor False Data Injection Attack Using Feature Interactive Network." IEEE Transactions on Smart Grid 12, no. 1: 659-670.

Research article
Published: 10 July 2020 in IET Generation, Transmission & Distribution
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With the large-scale deployment of power electronic equipment, harmonic sources in the power system are gradually increasing. Traditional harmonic source location methods are inaccurate and they usually require prior information of the location, which is difficult to obtain. This study presents a novel method of harmonic source location that can use less prior information to accurately locate the location of harmonic sources. First, a linear screening criterion is constructed using sparse component analysis. Then, the source signals separated by complex independent component analysis are filtered by linear and non-Gaussian secondary screening, improving the accuracy of source signals and mixing matrix. Finally, the precise location of the harmonic is obtained by matching the mixing matrix with the columns of the matrix, which related to the system topology. Three IEEE systems are used to validate the proposed method. The simulation results show the high accuracy of the proposed method in the harmonic source location.

ACS Style

Guangui Wang; Xiaoyang Ma; Weikang Wang; Honggeng Yang; Chang Chen; Qiuling Yang. Multi‐harmonic sources location based on sparse component analysis and complex independent component analysis. IET Generation, Transmission & Distribution 2020, 14, 4195 -4206.

AMA Style

Guangui Wang, Xiaoyang Ma, Weikang Wang, Honggeng Yang, Chang Chen, Qiuling Yang. Multi‐harmonic sources location based on sparse component analysis and complex independent component analysis. IET Generation, Transmission & Distribution. 2020; 14 (19):4195-4206.

Chicago/Turabian Style

Guangui Wang; Xiaoyang Ma; Weikang Wang; Honggeng Yang; Chang Chen; Qiuling Yang. 2020. "Multi‐harmonic sources location based on sparse component analysis and complex independent component analysis." IET Generation, Transmission & Distribution 14, no. 19: 4195-4206.

Journal article
Published: 29 June 2020 in IEEE Transactions on Industrial Informatics
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The increasing deployment of phasor measurement units and the advances of their reporting rates are challenging the present data centers in terms of storing and analyzing large-volume data. Under power system disturbance conditions, it is difficult to retain critical information while compressing the synchrophasor data effectively. This article combines the cross entropy and the singular value decomposition, proposing a novel model to compress the synchrophasor data to an extremely small size yet keep superior accuracy. The proposed model is extensively tested and compared with the state-of-the-art algorithms using the simulated and the FNET/GridEye field-collected data. The result indicates that the proposed algorithm has superior performance in compressing the data while retaining critical information under disturbance conditions.

ACS Style

Weikang Wang; Chang Chen; Wenxuan Yao; Kaiqi Sun; Wei Qiu; Yilu Liu. Synchrophasor Data Compression Under Disturbance Conditions via Cross-Entropy-Based Singular Value Decomposition. IEEE Transactions on Industrial Informatics 2020, 17, 2716 -2726.

AMA Style

Weikang Wang, Chang Chen, Wenxuan Yao, Kaiqi Sun, Wei Qiu, Yilu Liu. Synchrophasor Data Compression Under Disturbance Conditions via Cross-Entropy-Based Singular Value Decomposition. IEEE Transactions on Industrial Informatics. 2020; 17 (4):2716-2726.

Chicago/Turabian Style

Weikang Wang; Chang Chen; Wenxuan Yao; Kaiqi Sun; Wei Qiu; Yilu Liu. 2020. "Synchrophasor Data Compression Under Disturbance Conditions via Cross-Entropy-Based Singular Value Decomposition." IEEE Transactions on Industrial Informatics 17, no. 4: 2716-2726.

Journal article
Published: 02 March 2020 in IEEE Transactions on Power Systems
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ACS Style

Weikang Wang; Wenxuan Yao; Chang Chen; Xianda Deng; Yilu Liu. Fast and Accurate Frequency Response Estimation for Large Power System Disturbances Using Second Derivative of Frequency Data. IEEE Transactions on Power Systems 2020, 35, 2483 -2486.

AMA Style

Weikang Wang, Wenxuan Yao, Chang Chen, Xianda Deng, Yilu Liu. Fast and Accurate Frequency Response Estimation for Large Power System Disturbances Using Second Derivative of Frequency Data. IEEE Transactions on Power Systems. 2020; 35 (3):2483-2486.

Chicago/Turabian Style

Weikang Wang; Wenxuan Yao; Chang Chen; Xianda Deng; Yilu Liu. 2020. "Fast and Accurate Frequency Response Estimation for Large Power System Disturbances Using Second Derivative of Frequency Data." IEEE Transactions on Power Systems 35, no. 3: 2483-2486.

Journal article
Published: 05 February 2020 in IEEE Transactions on Smart Grid
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Power system frequency disturbances are caused by various generation and transmission events including generator trips, load disconnections, line trips, etc. Accurate detections of the events are crucial to bulk power system situation awareness and event investigation. This paper utilizes the recent advances of deep learning to build a convolutional neural network model to detect events in an accurate yet straightforward manner. In this paper, the rate of change of frequency and the relative angle shift are converted to images as the inputs of the proposed model. Finally, this paper uses two convolutional neural networks and classifier fusion to achieve the detection result. Compared with the conventional event detection algorithm and the frequency only deep learning model, the proposed model improves the detection accuracy by over 48%. As a promising tool for bulk power system situation awareness, the proposed model requires a short decision time, which is suitable for practical scenarios.

ACS Style

Weikang Wang; He Yin; Chang Chen; Abigail Till; Wenxuan Yao; Xianda Deng; Yilu Liu. Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning. IEEE Transactions on Smart Grid 2020, 11, 3593 -3605.

AMA Style

Weikang Wang, He Yin, Chang Chen, Abigail Till, Wenxuan Yao, Xianda Deng, Yilu Liu. Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning. IEEE Transactions on Smart Grid. 2020; 11 (4):3593-3605.

Chicago/Turabian Style

Weikang Wang; He Yin; Chang Chen; Abigail Till; Wenxuan Yao; Xianda Deng; Yilu Liu. 2020. "Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning." IEEE Transactions on Smart Grid 11, no. 4: 3593-3605.

Journal article
Published: 28 January 2020 in IEEE Transactions on Power Delivery
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The half-wavelength ultra-high-voltage transmission system is an alternative technique for bulk-power transmission over very long distances. However, the operations and fault-characteristics of such systems are extremely different from conventional ones. Therefore, there is an urgent need to propose a protection scheme that adapts to the characteristics of the half-wavelength lines. Towards this end, a lo-cal-measurement-based approach is proposed. According to the frequency-dependent model of the half-wavelength line, this pa-per uses the wavelet transform to decompose the arrival of the aerial-modal surge into several frequency bands. To acquire better accuracy, a weighted average approach is employed to modify the surge arrival time in each frequency band. Accord-ing to the surge arrival interval between the predefined low-frequency and high-frequency bands, all types of fault, ex-cept single-line-to-ground faults when the fault inception angle is at zero-crossings, can be identified in a very short time-window. Simulation results indicate that the proposed protection scheme has satisfactory performance against internal faults and is quite secure under external fault conditions. Using local measurement only, the reach of the proposed protection scheme is no less than 80% of the entire length of the line, and the resistive coverage is also sufficiently high for UHV transmission systems.

ACS Style

Ning Tong; Le Chen; Weikang Wang; Xiangning Lin; Zhengtian Li. Local-Measurement-Based High-Speed Protection for Half-Wavelength UHV Lines. IEEE Transactions on Power Delivery 2020, 35, 2481 -2494.

AMA Style

Ning Tong, Le Chen, Weikang Wang, Xiangning Lin, Zhengtian Li. Local-Measurement-Based High-Speed Protection for Half-Wavelength UHV Lines. IEEE Transactions on Power Delivery. 2020; 35 (5):2481-2494.

Chicago/Turabian Style

Ning Tong; Le Chen; Weikang Wang; Xiangning Lin; Zhengtian Li. 2020. "Local-Measurement-Based High-Speed Protection for Half-Wavelength UHV Lines." IEEE Transactions on Power Delivery 35, no. 5: 2481-2494.

Journal article
Published: 27 January 2020 in Electric Power Systems Research
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Distributed parameter characteristics of Ultra-long Distance Transmission Lines (UDTLs) are prone to cause harmonic amplification. Amplified harmonic components deteriorate the quality of energy delivery, and consequently affect the safety and operations of a power grid. This paper proposes a method based on Frequency-Length Factor (FLF) to investigate the harmonic transmission characteristics (HTCs) for UDTLs, including Half-Wavelength Transmission Lines (HWTLs). The proposed method considers the impact of line loss and reveals the comprehensive effects of line length, operation mode, and frequency on HTCs analysis for UDTLs. It is proved that only inter-harmonics can be amplified and cause resonance in lossy standard HWTLs propagation. Using the proposed method, the severity of harmonic amplification is quantitatively calculated. Additionally, this paper provides a fast evaluation approach for potential resonance frequencies of UDTLs, mitigating power quality issues caused by harmonic amplification. The effectiveness of the proposed method is verified by PSCAD simulation.

ACS Style

Chang Chen; Honggeng Yang; Weikang Wang; Mirka Mandich; Wenxuan Yao; Yilu Liu. Harmonic transmission characteristics for ultra-long distance AC transmission lines based on frequency-length factor. Electric Power Systems Research 2020, 182, 106189 .

AMA Style

Chang Chen, Honggeng Yang, Weikang Wang, Mirka Mandich, Wenxuan Yao, Yilu Liu. Harmonic transmission characteristics for ultra-long distance AC transmission lines based on frequency-length factor. Electric Power Systems Research. 2020; 182 ():106189.

Chicago/Turabian Style

Chang Chen; Honggeng Yang; Weikang Wang; Mirka Mandich; Wenxuan Yao; Yilu Liu. 2020. "Harmonic transmission characteristics for ultra-long distance AC transmission lines based on frequency-length factor." Electric Power Systems Research 182, no. : 106189.

Journal article
Published: 02 July 2019 in IEEE Transactions on Smart Grid
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The increase of renewable penetration in power grids calls for loads to participate in frequency regulation to avoid under-frequency load shedding after large resource contingencies. The motivation of this paper is to fulfill a fast residential load control for frequency stability enhancement. For this purpose, a novel mobile distribution-level phasor measurement unit (MDPMU) is developed for disturbance event detection, power mismatch estimation and fast load control. First, the systematic design of the MDPMU introduced. The proposed MDPMU has the major advantages of low cost and high frequency measurement accuracy. Second, the distribution-level measurement is utilized for the rate of change of frequency (ROCOF) calculation. Upon detection of a power system frequency event, power mismatch is estimated at the early stage of the event. Details of a robust approach to calculate ROCOF and determine the event starting point are presented. Practical issues including the measurement reporting rate and estimation time are also considered. Last, with the proposed control system, residential load responses can be controlled coordinately based on load availability and compensation prices offered by customers, providing adaptive frequency regulation service after large resource contingencies. The accuracy of frequency measurement and power mismatch estimation are evaluated via experimental analysis. The frequency stability improvement by load control is validated via PSS/E simulation.

ACS Style

Wenxuan Yao; Shutang You; Weikang Wang; Xianda Deng; Yicheng Li; Lingwei Zhan; Yilu Liu. A Fast Load Control System Based on Mobile Distribution-Level Phasor Measurement Unit. IEEE Transactions on Smart Grid 2019, 11, 895 -904.

AMA Style

Wenxuan Yao, Shutang You, Weikang Wang, Xianda Deng, Yicheng Li, Lingwei Zhan, Yilu Liu. A Fast Load Control System Based on Mobile Distribution-Level Phasor Measurement Unit. IEEE Transactions on Smart Grid. 2019; 11 (1):895-904.

Chicago/Turabian Style

Wenxuan Yao; Shutang You; Weikang Wang; Xianda Deng; Yicheng Li; Lingwei Zhan; Yilu Liu. 2019. "A Fast Load Control System Based on Mobile Distribution-Level Phasor Measurement Unit." IEEE Transactions on Smart Grid 11, no. 1: 895-904.