• DocumentCode
    1489896
  • Title

    Multiagent System for Real-Time Operation of a Microgrid in Real-Time Digital Simulator

  • Author

    Logenthiran, Thillainathan ; Srinivasan, Dipti ; Khambadkone, Ashwin M. ; Aung, Htay Nwe

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • Volume
    3
  • Issue
    2
  • fYear
    2012
  • fDate
    6/1/2012 12:00:00 AM
  • Firstpage
    925
  • Lastpage
    933
  • Abstract
    This paper presents a multiagent system (MAS) for real-time operation of a microgrid. The proposed operational strategy is mainly focused on generation scheduling and demand side management. In generation scheduling, schedule coordinator agent executes a two-stage scheduling: day-ahead and real-time scheduling. The day-ahead scheduling finds out hourly power settings of distributed energy resources (DERs) from a day-ahead energy market. The real-time scheduling updates the power settings of the distributed energy resources by considering the results of the day-ahead scheduling and feedback from real-time operation of the microgrid in real-time digital simulator (RTDS). A demand side management agent performs load shifting before the day-ahead scheduling, and does load curtailing in real-time whenever it is necessary and possible. The distributed multiagent model proposed in this paper provides a common communication interface for all components of the microgrid to interact with one another for autonomous intelligent control actions. Furthermore, the multiagent system maximizes the power production of local distributed generators, minimizes the operational cost of the microgrid, and optimizes the power exchange between the main power grid and the microgrid subject to system constraints and constraints of distributed energy resources. Outcome of simulation studies demonstrates the effectiveness of the proposed multiagent approach for real-time operation of a microgrid.
  • Keywords
    demand side management; distributed power generation; multi-agent systems; power engineering computing; power generation scheduling; autonomous intelligent control; day-ahead energy market; day-ahead scheduling; demand side management; distributed energy resources; distributed multiagent model; generation scheduling; load shifting; microgrids; multiagent system; operational cost; operational strategy; power exchange; real time digital simulator; real time operation; real time scheduling; schedule coordinator agent; Batteries; Computer architecture; Generators; Multiagent systems; Power systems; Real time systems; Schedules; Distributed energy resources; microgrid; multiagent system; real-time digital simulator; real-time operation;
  • fLanguage
    English
  • Journal_Title
    Smart Grid, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3053
  • Type

    jour

  • DOI
    10.1109/TSG.2012.2189028
  • Filename
    6180026