• DocumentCode
    2069583
  • Title

    Optimizing grid connected renewable energy resources with variability

  • Author

    Momoh, J.A. ; D´Arnaud, K.

  • Author_Institution
    Center for Energy Syst. & Control (CESaC), Howard Univ., Washington, DC, USA
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The randomness of photovoltaic (PV) and wind as renewable energy resources (RER) are best modeled as stochastic variable resources with given status and probability density function (pdf). The objective´s multiple criteria consist of cost and reliability. These are interlinked by the impact of RER and networks consisting of voltages, flows and available generation resources. To account for the variability and randomness, heuristic technique is developed so as to handle the resources in the implication of the optimal power flow. This will account for the stochastic nature of the problem. The scheme proposed is a framework towards building or designing a stochastic optimal power flow for handling variability of the load randomness. Case studies are proposed under different power output of PV and wind contributions are tested for both the performance load flow and optimization.
  • Keywords
    load flow; photovoltaic power systems; power generation economics; power generation reliability; power grids; power system simulation; probability; renewable energy sources; stochastic processes; wind power plants; PDF; PV RER; generation resource; grid connected renewable energy resource optimization; handling variability; heuristic technique; photovoltaic renewable energy resource; probability density function; reliability; stochastic optimal power flow; stochastic variable resource; wind RER; wind renewable energy resource; Indexes; Load flow; Load modeling; Loading; Mathematical model; Probabilistic logic; Wind speed; optimal power flow; probability density function; renewable resources; variability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345704
  • Filename
    6345704