• DocumentCode
    180097
  • Title

    Stochastic resource planning strategy to improve the efficiency of microgrid operation

  • Author

    Zhaohao Ding ; Wei-Jen Lee ; Juanjuan Wang

  • Author_Institution
    Energy Syst. Res. Center, Univ. of Texas at Arlington, Arlington, TX, USA
  • fYear
    2014
  • fDate
    5-9 Oct. 2014
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The intermittence nature of distributed renewable generation presents significant challenges for microgrid operation. Advanced demand side management, with innovative structures and technologies, provides feasible solutions for this issue. This paper presents a stochastic resource planning strategy for microgrid to optimally manage its resources on both generation and demand sides to improve the system operation efficiency. An internal pricing strategy is proposed to integrate with traditional operation scheduling model considering both operational and economic constraints. To address the uncertainties in the renewable generation forecasting and customers´ price responsive patterns, the stochastic model is formulated and corresponding solution method is provided. A sample microgrid is utilized to illustrate and compare the effectiveness of the proposed models.
  • Keywords
    demand side management; distributed power generation; power distribution economics; power distribution planning; power generation economics; power generation planning; pricing; renewable energy sources; stochastic processes; customer price responsive patterns; demand side management; distributed renewable generation; internal pricing strategy; microgrid operation efficiency; renewable generation forecasting; resource management; stochastic resource planning strategy; Elasticity; Energy storage; Generators; Load modeling; Microgrids; Stochastic processes; Supply and demand; Microgrid; demand side management; elasticity; renewable energy integration; stochastic optimization; unit commitment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Society Annual Meeting, 2014 IEEE
  • Conference_Location
    Vancouver, BC
  • Type

    conf

  • DOI
    10.1109/IAS.2014.6978379
  • Filename
    6978379