• DocumentCode
    3009131
  • Title

    Developing the physical layer of future power grids: Required for automated asset management and renewable energy integration

  • Author

    Djairam, Dhiradj ; Grizonic, R. ; Zhuang, Qianmeng ; Smit, J.J.

  • Author_Institution
    High Voltage Technol. & Manage, Delft Univ. of Technol., Delft, Netherlands
  • fYear
    2012
  • fDate
    23-27 Sept. 2012
  • Firstpage
    509
  • Lastpage
    512
  • Abstract
    Increased demand for power requires a grid that is equipped to facilitate distributed or large-distance bulk generation. Complying with long term goals, this future grid should be reliable, carbon neutral and sustainable. The main drivers for the upcoming changes in the power grids are the increase of renewable energy production and the aging of the high voltage electrical components. In order to determine the health state of these components, intelligence embedded in the components is required. This includes sensors, communication technology and associated models for interpretation and decision making. To realize an intelligent future grid, it is required that, besides high level smart grids concepts, an actual lower level physical layer is developed. Concrete suggestions will be discussed to implement market ready solutions for predictive health management which can cope with the changing environment of the future grid. Using these suggestions in a case, it is shown that the loss of remaining lifetime can be decreased during a standard 24 hour loading pattern.
  • Keywords
    decision making; power system management; remaining life assessment; renewable energy sources; smart power grids; automated asset management; decision making; future power grids; intelligence embedded; large-distance bulk generation; physical layer; predictive health management; remaining lifetime; renewable energy integration; smart grids; standard 24 hour loading pattern; Load modeling; Oil insulation; Power transformers; Predictive models; Prognostics and health management; Sensors; Stress; condition monitoring; decision making; diagnostic interpretation; diagnostics; high voltage; power grid intelligence; predictive health model; sensoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Condition Monitoring and Diagnosis (CMD), 2012 International Conference on
  • Conference_Location
    Bali
  • Print_ISBN
    978-1-4673-1019-2
  • Type

    conf

  • DOI
    10.1109/CMD.2012.6416191
  • Filename
    6416191