• DocumentCode
    2055641
  • Title

    A multi-layer, data-driven advanced reasoning tool for intelligent data mining and analysis for smart grids

  • Author

    Ning Lu ; Pengwei Du ; Greitzer, F.L. ; Guo, X. ; Hohimer, R.E. ; Pomiak, Y.G.

  • Author_Institution
    Pacific Northwest Nat. Lab., Richland, WA, USA
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper presents the multi-layer, data-driven advanced reasoning tool (M-DART), a proof-of-principle decision support tool for improved power system operation. M-DART will cross-correlate and examine different data sources to assess anomalies, infer root causes, and anneal data into actionable information. By performing higher-level reasoning “triage” of diverse data sources, M-DART focuses on early detection of emerging power system events and identifies highest priority actions for the human decision maker. M-DART represents a significant advancement over today´s grid monitoring technologies that apply offline analyses to derive model-based guidelines for online real-time operations and use isolated data processing mechanisms focusing on individual data domains. The development of the M-DART will bridge these gaps by reasoning about results obtained from multiple data sources that are enabled by the smart grid infrastructure. This hybrid approach integrates a knowledge base that is trained offline but tuned online to capture model-based relationships while revealing complex causal relationships among data from different domains.
  • Keywords
    data mining; decision making; power engineering computing; smart power grids; M-DART; diverse data sources; grid monitoring technologies; higher-level reasoning triage; human decision maker; improved power system operation; individual data domains; intelligent data mining; isolated data processing mechanisms; model-based guidelines; model-based relationships; multilayer data-driven advanced reasoning tool; multiple data sources; online real-time operations; proof-of-principle decision support tool; smart grid infrastructure; Cognition; Decision making; Energy consumption; Humans; Monitoring; Smart grids; advanced metering infrastructure; data mining; data-driven models; distribution; energy management systems; information management; meter data management; smart alarm; smart grid; smart meter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345180
  • Filename
    6345180