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1. WO2020140104 - SYSTEM AND METHOD FOR PROACTIVE HANDLING OF MULTIPLE FAULTS IN AN ELECTRICAL NETWORK OF ENERGY ASSETS

Publication Number WO/2020/140104
Publication Date 02.07.2020
International Application No. PCT/US2019/068843
International Filing Date 27.12.2019
IPC
G01R 31/08 2020.1
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
08Locating faults in cables, transmission lines, or networks
G01R 31/14 2006.1
GPHYSICS
01MEASURING; TESTING
RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
31Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
12Testing dielectric strength or breakdown voltage
14Circuits therefor
CPC
G05B 13/02
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
13Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
02electric
G05B 23/0229
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
23Testing or monitoring of control systems or parts thereof
02Electric testing or monitoring
0205by means of a monitoring system capable of detecting and responding to faults
0218characterised by the fault detection method dealing with either existing or incipient faults
0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
0227Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
0229knowledge based, e.g. expert systems; genetic algorithms
G05B 23/024
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
23Testing or monitoring of control systems or parts thereof
02Electric testing or monitoring
0205by means of a monitoring system capable of detecting and responding to faults
0218characterised by the fault detection method dealing with either existing or incipient faults
0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
024Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
G05B 23/0272
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
23Testing or monitoring of control systems or parts thereof
02Electric testing or monitoring
0205by means of a monitoring system capable of detecting and responding to faults
0259characterized by the response to fault detection
0267Fault communication, e.g. human machine interface [HMI]
0272Presentation of monitored results, e.g. selection of status reports to be displayed; Filtering information to the user
G05B 23/0283
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
23Testing or monitoring of control systems or parts thereof
02Electric testing or monitoring
0205by means of a monitoring system capable of detecting and responding to faults
0259characterized by the response to fault detection
0283Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
H02J 13/0006
HELECTRICITY
02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
13Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
0006for single frequency AC networks
Applicants
  • SRINIVASAN, Guruprasad [IN]/[IN]
  • KIM, Younghun [US]/[US]
Inventors
  • SRINIVASAN, Guruprasad
  • KIM, Younghun
Agents
  • KLOKE, Daniel
Priority Data
16/234,45027.12.2018US
Publication Language English (EN)
Filing Language English (EN)
Designated States
Title
(EN) SYSTEM AND METHOD FOR PROACTIVE HANDLING OF MULTIPLE FAULTS IN AN ELECTRICAL NETWORK OF ENERGY ASSETS
(FR) SYSTÈME ET PROCÉDÉ DE GESTION PROACTIVE DE DÉFAILLANCES MULTIPLES DANS UN RÉSEAU ÉLECTRIQUE DE RESSOURCES ÉNERGÉTIQUES
Abstract
(EN)
An example method comprises receiving historical sensor data of a renewable energy asset for a first time period, identifying historical log data in one or more log sources, retrieving dates of the identified historical log data, retrieving sequences of historical sensor data using the dates, training hidden Markov models using the sequences of historical sensor data to identify probability of shifting states of one or more components of the renewable energy asset, receiving current sensor data of a second time period, identifying current log data in the one or more log sources, retrieving dates of the identified current log data, retrieving sequences of current sensor data using the dates, applying the hidden Markov models to the sequences of the current sensor data to assess likelihood of the one or more faults, creating a prediction of a future fault, and generating a report including the prediction of the future fault.
(FR)
L'invention concerne un procédé donné à titre d'exemple consistant à recevoir des données de capteur historiques d'une ressource énergétique renouvelable pour une première période de temps, à identifier des données de journal historiques dans une ou plusieurs sources de journal, à récupérer des dates des données de journal historiques identifiées, à récupérer des séquences de données de capteur historiques à l'aide des dates, à entraîner des modèles de Markov cachés à l'aide des séquences de données de capteur historiques afin d'identifier la probabilité d'états de décalage d'un ou plusieurs composants de la ressource énergétique renouvelable, à recevoir des données de capteur de courant d'une seconde période de temps, à identifier des données de journal de courant dans lesdites sources de journal, à récupérer des dates des données de journal de courant identifiées, à récupérer des séquences de données de capteur de courant à l'aide des dates, à appliquer les modèles de Markov cachés aux séquences des données de capteur de courant afin d'évaluer la probabilité d'une ou plusieurs défaillances, à créer une prédiction d'une défaillance future, et à générer un rapport comprenant la prédiction de la défaillance future.
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