Adaptive 100% Injection-Based Generator Stator Ground Fault Protection With Real-Time Fault Location Capability

Safari-Shad, N.; Franklin, Russ; Negahdari, Amir; Toliyat, H.A.

doi:10.1109/tpwrd.2018.2802423

Cited by 34 publications

(7 citation statements)

References 12 publications

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“…Thus, the complex amplitude-time-frequency matrix of discrete signal can be obtained by (3). Notations (N /2 + 1) = number of rows in the matrix S, which corresponds to the sampling frequency; N = number of columns in the matrix S, which corresponds to the point of sampling time.…”

Section: Background Theories a S-transformmentioning

confidence: 99%

“…The zero-sequence fundamental over-voltage relay has blind zones near the generator neutral, so it can only be used to determine the fault at the generator terminal [1], [2]. The sub-harmonic voltage injection scheme with neutral grounding signal [3] and the third-harmonic voltage scheme [4] are important schemes to solve the blind zones. But the former requires additional sub-harmonic power supplies, which increases the investment costs for the implementation of protection, while the latter achieves certain applications.…”

Section: Introductionmentioning

confidence: 99%

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Stator Single-Line-to-Ground Fault Protection for Bus-Connected Powerformers Based on S-Transform and Bagging Ensemble Learning

et al. 2020

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In order to achieve selective ground fault protection for bus-connected Powerformers and improve the reliability of the protection scheme, this paper presents a novel stator single-line-to-ground (SLG) fault protection scheme for bus-connected Powerformers based on S-transform (ST) and bagging ensemble learning algorithm. The scheme utilizes ST to decompose the zero-sequence current signals acquired from the Powerformer terminal to obtain the amplitude-time-frequency matrix. Then, fault features extraction is presented, and three features including the transient energy, the comprehensive correlation coefficient, and the zero-sequence active power are discussed and selected as feature vectors. The calculated data set is then extracted from feature vectors and used as inputs to the bagging ensemble learning algorithm to detect faults. Simulation results have shown that, under different fault conditions, the novel scheme can detect in which Powerformer a stator SLG fault is occurring and can detect internal faults from external faults reliably even if the fault resistance is at 8000. The proposed protection scheme does not need to set the threshold value and has noise-tolerant ability. Furthermore, the proposed technique performs better than support vector machine (SVM), random forest (RF) and k-Nearest Neighbor (KNN) techniques in detecting faults.

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Section: Background Theories a S-transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stator Single-Line-to-Ground Fault Protection for Bus-Connected Powerformers Based on S-Transform and Bagging Ensemble Learning

et al. 2020

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“…This increases the threat to protection schemes due to: blinding of feeder protection, sympathetic tripping, failed reclosing, unintentional islanding, and recloser-fuse miscoordination [17][18][19], driving the protection and control engineers to re-evaluate long-established practices, as well as the way the relays are tested and certified. Adaptive protection is a protection strategy that is widely studied by the scientific community which tries to tackle some of these protection issues by adjusting protection equipment set points based on system operations [17,[20][21][22][23]. The modeling of faults and protection strategies also needs to be studied and verified with transients (EMT simulations), which makes PHIL a good option to validate fault behaviors [24,25].…”

Section: Introductionmentioning

confidence: 99%

Advanced Laboratory Testing Methods Using Real-Time Simulation and Hardware-in-the-Loop Techniques: A Survey of Smart Grid International Research Facility Network Activities

et al. 2020

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The integration of smart grid technologies in interconnected power system networks presents multiple challenges for the power industry and the scientific community. To address these challenges, researchers are creating new methods for the validation of: control, interoperability, reliability of Internet of Things systems, distributed energy resources, modern power equipment for applications covering power system stability, operation, control, and cybersecurity. Novel methods for laboratory testing of electrical power systems incorporate novel simulation techniques spanning real-time simulation, Power Hardware-in-the-Loop, Controller Hardware-in-the-Loop, Power System-in-the-Loop, and co-simulation technologies. These methods directly support the acceleration of electrical systems and power electronics component research by validating technological solutions in high-fidelity environments. In this paper, members of the Survey of Smart Grid International Research Facility Network task on Advanced Laboratory Testing Methods present a review of methods, test procedures, studies, and experiences employing advanced laboratory techniques for validation of range of research and development prototypes and novel power system solutions.

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“…Injection method for fault location is more targeted than manual line patrol to find fault points. However, this method requires new equipment, high cost, and the strength of the injected signal is difficult to grasp [7,8]. Various fault location methods for transmission networks are proposed by scholars at home and abroad with the continuous progress of computer, communication and measurement technology.…”

Section: Introductionmentioning

confidence: 99%

A Novel Traveling Wave Fault Location Method for Transmission Network Based on Directed Tree Model and Linear Fitting

Zeng

Zhang

et al. 2020

IEEE Access

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In order to solve the problem of inaccurate fault location in the transmission network under some abnormal conditions, such as traveling wave location device faults, startup failure and time recording error, a novel traveling wave fault location method based on directed tree model and linear fitting is proposed. A directed tree model of the fault traveling wave transmission along the shortest path is established based on graph theory analysis of traveling wave transmission network. Two straight lines are fitted on the coordinate plane where the accurate fault location is obtained direct by coordinate information of the intersection of these two fitted straight lines (FSLs), according to the transmission characteristics of the fault traveling wave in the directed tree model. The wave velocity is used as the slope of the fitted straight line, and the influence of its uncertainty on the fault location is eliminated. The time record error points of the location device are automatically eliminated in the linear fitting. PSCAD simulation results prove that fault information of the entire transmission network is comprehensively utilized by the proposed method and the ring network is automatically unlooped. The reliability and accuracy of fault location are remarkably improved, particularly for the fault scenarios with recorded information abnormity. INDEX TERMS Transmission network, fault location, traveling wave, directed tree model, linear fitting.

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Adaptive 100% Injection-Based Generator Stator Ground Fault Protection With Real-Time Fault Location Capability

Cited by 34 publications

References 12 publications

Stator Single-Line-to-Ground Fault Protection for Bus-Connected Powerformers Based on S-Transform and Bagging Ensemble Learning

Stator Single-Line-to-Ground Fault Protection for Bus-Connected Powerformers Based on S-Transform and Bagging Ensemble Learning

Advanced Laboratory Testing Methods Using Real-Time Simulation and Hardware-in-the-Loop Techniques: A Survey of Smart Grid International Research Facility Network Activities

A Novel Traveling Wave Fault Location Method for Transmission Network Based on Directed Tree Model and Linear Fitting

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