• DocumentCode
    3600605
  • Title

    Coordinated Energy Management of Networked Microgrids in Distribution Systems

  • Author

    Zhaoyu Wang ; Bokan Chen ; Jianhui Wang ; Begovic, Miroslav M. ; Chen Chen

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    6
  • Issue
    1
  • fYear
    2015
  • Firstpage
    45
  • Lastpage
    53
  • Abstract
    This paper proposes a novel control strategy for coordinated operation of networked microgrids (MGs) in a distribution system. The distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize the operation costs. It is assumed that both the dispatchable and nondispatchable distributed generators (DGs) exist in the networked MGs. In order to achieve the equilibrium among all entities and take into account the uncertainties of DG outputs, we formulate the problem as a stochastic bi-level problem with the DNO in the upper level and MGs in the lower level. Each level consists of two stages. The first stage is to determine base generation setpoints based on the load and nondispatchable DG output forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. A scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Case studies of a distribution system with multiple MGs of different types demonstrate the effectiveness of the proposed methodology. The centralized control, deterministic formulation, and stochastic formulation are also compared.
  • Keywords
    distributed power generation; energy management systems; power distribution control; base generation setpoints; centralized control; control strategy; coordinated energy management; coordinated operation; deterministic formulation; distribution network operator; distribution systems; generation outputs; networked microgrids; nondispatchable distributed generators; operation costs; scenario reduction method; stochastic bi-level problem; stochastic formulation; Biological system modeling; Electricity; Energy management; Mathematical model; Optimization; Stochastic processes; Uncertainty; Distributed generator (DG); Microgrid (MG); distribution network; mathematical program with complementarity constraints (MPCC); microgrid (MG);
  • fLanguage
    English
  • Journal_Title
    Smart Grid, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3053
  • Type

    jour

  • DOI
    10.1109/TSG.2014.2329846
  • Filename
    6872821