[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Hosseini et al., 2018 - Google Patents

AMI-enabled distribution network line outage identification via multi-label SVM

Hosseini et al., 2018

View PDF
Document ID
10464056305598188847
Author
Hosseini Z
Mahoor M
Khodaei A
Publication year
Publication venue
IEEE Transactions on Smart Grid

External Links

Snippet

This letter proposes an effective data mining method for identifying distribution network line outages by leveraging data collected through Advanced Metering Infrastructure (AMI). The line outage identification method is developed based on a Multi-Label Support Vector …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6279—Classification techniques relating to the number of classes
    • G06K9/6284—Single class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Hosseini et al. AMI-enabled distribution network line outage identification via multi-label SVM
Bhattacharya et al. Intelligent fault analysis in electrical power grids
Zhou et al. Partial knowledge data-driven event detection for power distribution networks
US11448671B2 (en) Signature identification for power system events
US20200292608A1 (en) Residual-based substation condition monitoring and fault diagnosis
Song et al. Multiple event detection and recognition for large-scale power systems through cluster-based sparse coding
Gilanifar et al. Multi-task logistic low-ranked dirty model for fault detection in power distribution system
Pavlovski et al. Hierarchical convolutional neural networks for event classification on PMU measurements
Waghmare et al. Data driven approach to attack detection in a cyber-physical smart grid system
WO2020026442A1 (en) Event monitoring apparatus, method and program recording medium
Jiang et al. Automated distribution network fault cause identification with advanced similarity metrics
Mnyanghwalo et al. Deep learning approaches for fault detection and classifications in the electrical secondary distribution network: Methods comparison and recurrent neural network accuracy comparison
Lima et al. Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection
Munawar et al. Electricity theft detection in smart meters using a hybrid Bi-directional GRU Bi-directional LSTM model
Francis et al. Topology identification of power distribution systems using time series of voltage measurements
Maaji et al. On-line voltage stability monitoring using an Ensemble AdaBoost classifier
Zhao et al. Efficient neural network architecture for topology identification in smart grid
Vosughi et al. Synchrophasor-based event detection, classification, and localization using koopman, transient energy matrix, best worth method, and dynamic graph
Anderson et al. Distribution system bad data detection using graph signal processing
Song et al. Multiple event analysis for large-scale power systems through cluster-based sparse coding
Viegas et al. Prediction of events in the smart grid: Interruptions in distribution transformers
De Santis et al. Fault recognition in smart grids by a one-class classification approach
Krishna Ponukumati et al. Evolving fault diagnosis scheme for unbalanced distribution network using fast normalized cross-correlation technique
Shuvra et al. Root cause identification of power system faults using waveform analytics
Wanik et al. PMU analytics for power fault awareness and prediction