Nothing Special   »   [go: up one dir, main page]

Zhou et al., 2021 - Google Patents

Abnormal data processing of wind turbine based on combined algorithm and class center imputation

Zhou et al., 2021

Document ID
14578081808701158082
Author
Zhou Q
Ma Y
Lv Q
Zhang R
Wang W
Yang S
Publication year
Publication venue
2021 International Conference on Power System Technology (POWERCON)

External Links

Snippet

High precision wind power curve is essential to wind power predictions. In order to eliminate a host of abnormal data of a wind turbine, the abnormal data is divided into decentralized data or abandoned data, and the wind speed into low wind speed and high wind speed …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/3071—Clustering or classification including class or cluster creation or modification
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GASES [GHG] EMISSION, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/70—Systems integrating technologies related to power network operation and communication or information technologies mediating in the improvement of the carbon footprint of electrical power generation, transmission or distribution, i.e. smart grids as enabling technology in the energy generation sector not used, see subgroups
    • Y02E60/76—Computer aided design [CAD]; Simulation; Modelling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Communication or information technology specific aspects supporting electrical power generation, transmission, distribution or end-user application management
    • Y04S40/20—Information technology specific aspects
    • Y04S40/22—Computer aided design [CAD]; Simulation; Modelling

Similar Documents

Publication Publication Date Title
Shen et al. A combined algorithm for cleaning abnormal data of wind turbine power curve based on change point grouping algorithm and quartile algorithm
CN110750524A (en) A method and system for determining fault characteristics of active distribution network
Wang et al. A fast abnormal data cleaning algorithm for performance evaluation of wind turbine
CN111878320B (en) Monitoring method and system of wind generating set and computer readable storage medium
CN110362045B (en) A fault discrimination method for offshore doubly-fed wind turbines considering marine meteorological factors
Jia et al. Defect prediction of relay protection systems based on LSSVM-BNDT
Wang et al. Investigating the construction, training, and verification methods of k-means clustering fault recognition model for rotating machinery
Shi et al. Study of wind turbine fault diagnosis and early warning based on SCADA data
Bao et al. Wind turbine condition monitoring based on improved active learning strategy and KNN algorithm
Zhou et al. Abnormal data processing of wind turbine based on combined algorithm and class center imputation
Tong et al. A novel ellipsoidal semisupervised extreme learning machine algorithm and its application in wind turbine blade icing fault detection
CN114463143A (en) A SCADA fault data enhancement method for offshore doubly-fed wind turbines
CN111880090B (en) An online fault detection method for one million kilowatt ultra-supercritical units
CN114154567A (en) An abnormal identification method of wind farm operation data based on machine learning
CN111563543A (en) A method and device for cleaning wind speed-generating power data of a wind turbine
Qiao et al. Study on K-means method based on Data-Mining
McKinnon et al. Comparison of novel SCADA data cleaning technique for wind turbine electric pitch system
Sheng et al. Transient Stability Assessment of Power Systems Based on Semi-Supervised Active Learning
Wang et al. Wind turbine abnormal data cleaning method considering multi-scene parameter adaptation
Wang et al. Comparison of Artificial Intelligence-Based Power Curve Cleaning Algorithms for Wind Farms
Han et al. Application of Sparse Representation in SCADA: Wind Turbine Fault Diagnosis Based on K-SVD
Zhang et al. An unsupervised anomaly detection approach based on industrial big data
Duan et al. Cleaning of Transient Fault Data in Distribution Network Based on Clustering by Fast Search and Find of Density Peaks.
Liao et al. Data cleaning method of distributed photovoltaic power generation based on clustering algorithm
Lu et al. Power System Transient Stability Assessment Based on Graph Convolutional Network