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Xinan Wang

from McKinney, TX

Xinan Wang Phones & Addresses

  • McKinney, TX
  • Dallas, TX
  • Santa Clara, CA
  • Tempe, AZ

Work

  • Company:
    Dell
    Jul 2011
  • Position:
    Part time salesman

Education

  • School / High School:
    Arizona State University
    Aug 2013
  • Specialities:
    Master of Engineering in Electrical Engr

Skills

matlab • powerworld • pscad • mathematica • c...

Resumes

Xinan Wang Photo 1

Junior Machine Learning Engineer

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Location:
Santa Clara, CA
Work:

Junior Machine Learning Engineer
Xinan Wang Photo 2

Xinan Wang

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Xinan Wang Photo 3

Xinan Wang Tempe, AZ

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Work:
Dell

Jul 2011 to Sep 2011
Part time salesman
Education:
Arizona State University
Aug 2013
Master of Engineering in Electrical Engr
Northwestern Polytechnical University We have three members
Jan 2013 to Jul 2013
Northwestern Polytechnical University
Sep 2009 to Jul 2013
Bachelor of Electronics and Information in Energy
Tractor & Farm Transporter Research Center of China
Oct 2012 to Dec 2012
design
Skills:
matlab, powerworld,pscad,mathematica,c...

Us Patents

  • Data Mining Based Approach For Online Calibration Of Phasor Measurement Unit (Pmu)

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  • US Patent:
    20180156886, Jun 7, 2018
  • Filed:
    Oct 18, 2017
  • Appl. No.:
    15/787365
  • Inventors:
    Xiao Lu - Nanjing, CN
    Xinan Wang - Santa Clara CA, US
    Di Shi - San Jose CA, US
    Zhiwei Wang - Santa Clara CA, US
    Jianyu Luo - Nanjing, CN
    Chunlei Xu - Nanjing, CN
  • International Classification:
    G01R 35/00
    G01R 19/25
  • Abstract:
    Data quality of Phasor Measurement Unit (PMU) is receiving increasing attention as it has been identified as one of the limiting factors that affect many wide-area measurement system (WAMS) based applications. In general, existing PMU calibration methods include offline testing and model based approaches. However, in practice, the effectiveness of both is limited due to the very strong assumptions employed. This invention presents a novel framework for online error detection and calibration of PMU measurement using density-based spatial clustering of applications with noise (DBSCAN) based on much relaxed assumptions. With a new problem formulation, the proposed data mining based methodology is applicable across a wide spectrum of practical conditions and one side-product of it is more accurate transmission line parameters for the energy management system (EMS) database and protective relay settings. Case studies are presented to demonstrate the effectiveness of the proposed method.

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