Failure probability estimation of overhead transmission lines considering the spatial and temporal variation in severe weather

Yang, Shuai; Zhou, Wenjun; Zhu, Shiyang; Wang, Le; Ye, Lisha; Xia, Xuezhi; Han, Li

doi:10.1007/s40565-017-0370-4

Cited by 39 publications

(17 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, it indicates that (2, 3) is the faulty section, which is the correct result. The dominant frequency-band waveforms of section (2, 3), as well as those of neighboring sections (1, 2) and (3,4) are presented in Fig. 7; the calculated similarities are 0.835, 0.126 and 0.831, respectively.…”

Section: A Simulation Verificationmentioning

confidence: 99%

See 1 more Smart Citation

Faulty Feeder Identification and Fault Area Localization in Resonant Grounding System Based on Wavelet Packet and Bayesian Classifier

Chen

Chu

et al. 2020

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

Accurate fault area localization is a challenging problem in resonant grounding systems (RGSs). Accordingly, this paper proposes a novel two-stage localization method for single-phase earth faults in RGSs. Firstly, a faulty feeder identification algorithm based on a Bayesian classifier is proposed. Three characteristic parameters of the RGS (the energy ratio, impedance factor, and energy spectrum entropy) are calculated based on the zero-sequence current (ZSC) of each feeder using wavelet packet transformations. Then, the values of three parameters are sent to a pre-trained Bayesian classifier to recognize the exact fault mode. With this result, the faulty feeder can be finally identified. To find the exact fault area on the faulty feeder, a localization method based on the similarity comparison of dominant frequency-band waveforms is proposed in an RGS equipped with feeder terminal units (FTUs). The FTUs can provide the information on the ZSC at their locations. Through wavelet-packet transformation, ZSC dominant frequency-band waveforms can be obtained at all FTU points. Similarities of the waveforms of characteristics at all FTU points are calculated and compared. The neighboring FTU points with the maximum diversity are the faulty sections finally determined. The proposed method exhibits higher accuracy in both faulty feeder identification and fault area localization compared to the previous methods. Finally, the effectiveness of the proposed method is validated by comparing simulation and experimental results.

show abstract

Section: A Simulation Verificationmentioning

confidence: 99%

“…A case study is described in this paper, in which a singlephase earth fault occurs at 0.02 s with a fault angle of 0°. The faulty feeder is feeder 2, the faulty phase is B, and the faulty section is (2,3). The measured transient Head-ZSC waveforms of the four feeders are shown in Fig.…”

Section: A Simulation Verificationmentioning

confidence: 99%

Faulty Feeder Identification and Fault Area Localization in Resonant Grounding System Based on Wavelet Packet and Bayesian Classifier

Chen

Chu

et al. 2020

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

show abstract

“…Since this paper focuses on the predictive maintenance tool only, the failure prediction model is formulated based on [22]. In this simulation, we use the term odd event which the event that would potentially cause failure.…”

Section: Proposed Ontology-based Predictivementioning

confidence: 99%

“…Fig. 15 shows the predicted failure in which day based on the analysis of odd events, based on [22], when the probability exceeds 0.05, the failure would happen.…”

Section: Substation Ontologymentioning

confidence: 99%

An Ontology-Based Predictive Maintenance Tool for Power Substation Faults in Distribution Grid

Mahmoud¹,

Alicia²,

Kumar³

et al. 2020

IJACSA

View full text Add to dashboard Cite

Recent advances in Power Grid (PG) technology pose an important problem of measuring the effectiveness of power grid configurations. Current assessment models are not adequate to mitigate the setup issues due to the absence of a highfidelity evaluation framework that can consider diverse scenarios based on the market interest. Consequently, we develop a highly flexible Ontology-based Evaluation System that can accommodate and assess different scenarios. The use of ontology as middleware is the best approach to produce an efficient, semantically aware, and operationally accurate system environment for managing flexibility in evaluation. The evaluation is made by predicting the failure intensity and subsequently generate a maintenance report of a particular configuration. The selection of the best configuration is made by comparing the maintenance report of different configurations. The developed evaluation system consists of three main components which are Configuration Generator Tool (GCT), Failure Prediction Model (FDM), and Hybrid Simulation Platform (HSP). The GCT is a knowledge-based system that provides a powerful tool for engineers to generate alternative configurations. The GCT data were collected from literature, validated by experts, and modeled using Web Ontology Language (OWL). While the HSP was developed using several modelings and ontology-based tools such as blender 3D modeling, unity 3d, asp.net, my sql, and apache Jena fuseki. Finally, the FDM was developed based on the impact and relationship of odd events to power grid components and the impact of a failed component to other components, the prediction is modeled using two methods Poisson Model and Likelihood Estimation Method.

show abstract

“…For instance, a type-specific failure rate model accounting for the effects of weather, environmental, and operational conditions for overhead line is proposed in [18] where the proposed method was based on a non-homogenous Poisson process integrating with assumed powerlaw maintenance effect on the failure rate, and maximum likelihood estimation (MLE) was conducted for fitting the relevant parameters. Recently, based on the regression theory, Yang et al [19] proposed a failure probability estimation method for overhead transmission lines considering a temporal and spatial variation of lightning and wind.…”

Section: Introductionmentioning

confidence: 99%

Evaluating weather influences on transmission line failure rate based on scarce fault records via a bi‐layer clustering technique

Wang

Lü

Yao

et al. 2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

Failure probability estimation of overhead transmission lines considering the spatial and temporal variation in severe weather

Cited by 39 publications

References 28 publications

Faulty Feeder Identification and Fault Area Localization in Resonant Grounding System Based on Wavelet Packet and Bayesian Classifier

Faulty Feeder Identification and Fault Area Localization in Resonant Grounding System Based on Wavelet Packet and Bayesian Classifier

An Ontology-Based Predictive Maintenance Tool for Power Substation Faults in Distribution Grid

Evaluating weather influences on transmission line failure rate based on scarce fault records via a bi‐layer clustering technique

Contact Info

Product

Resources

About