• DocumentCode
    3499054
  • Title

    The role of big data in improving power system operation and protection

  • Author

    Kezunovic, Mladen ; Le Xie ; Grijalva, Santiago

  • Author_Institution
    Texas A&M Univ., College Station, TX, USA
  • fYear
    2013
  • fDate
    25-30 Aug. 2013
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    This paper focuses on the use of extremely large data sets in power system operation, control, and protection, which are difficult to process with traditional database tools and often termed big data. We will discuss three aspects of using such data sets: feature extraction, systematic integration for power system applications, and examples of typical applications in the utility industry. The following analytics tasks based on big data methodology are elaborated upon: corrective, predictive, distributed and adaptive. The paper also outlines several research topics related to asset management, operation planning, realtime monitoring and fault detection/protection that present new opportunities but require further investigation.
  • Keywords
    electricity supply industry; fault diagnosis; power system control; power system faults; power system management; power system measurement; power system planning; power system protection; power utilisation; asset management; big data methodology; fault detection-protection; feature extraction; operation planning; power system control; power system operation; power system protection; real-time monitoring; utility industry; Data handling; Data models; Data storage systems; Decision making; Information management; Planning; Power system stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid (IREP), 2013 IREP Symposium
  • Conference_Location
    Rethymno
  • Electronic_ISBN
    978-1-4799-0199-9
  • Type

    conf

  • DOI
    10.1109/IREP.2013.6629368
  • Filename
    6629368