• DocumentCode
    30628
  • Title

    Self-Healing Resilient Distribution Systems Based on Sectionalization Into Microgrids

  • Author

    Zhaoyu Wang ; Jianhui Wang

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    30
  • Issue
    6
  • fYear
    2015
  • fDate
    Nov. 2015
  • Firstpage
    3139
  • Lastpage
    3149
  • Abstract
    This paper proposes a novel comprehensive operation and self-healing strategy for a distribution system with both dispatchable and nondispatchable distributed generators (DGs). In the normal operation mode, the control objective of the system is to minimize the operation costs and maximize the revenues. A rolling-horizon optimization method is used to schedule the outputs of dispatchable DGs based on forecasts. In the self-healing mode, the on-outage portion of the distribution system will be optimally sectionalized into networked self-supplied microgrids (MGs) so as to provide reliable power supply to the maximum loads continuously. The outputs of the dispatchable DGs will be rescheduled accordingly too. In order to take into account the uncertainties of DG outputs and load consumptions, we formulate the problems as a stochastic program. A scenario reduction method is applied to achieve a tradeoff between the accuracy of the solution and the computational burden. A modified IEEE 123-node distribution system is used as a test system. The results of case studies demonstrate the effectiveness of the proposed methodology.
  • Keywords
    distributed power generation; power generation dispatch; stochastic programming; dispatchable distributed generators; modified IEEE 123-node distribution system; networked self-supplied microgrids; nondispatchable distributed generators; rolling-horizon optimization method; scenario reduction method; sectionalization; self-healing resilient distribution system; stochastic program; Distributed power generation; Microgrids; Optimization; Power distribution faults; Power system reliability; Stochastic processes; Uncertainty; Distributed power generation; microgrid (MG); power distribution; power distribution faults; self-healing; stochastic optimization;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2015.2389753
  • Filename
    7017458