• DocumentCode
    2314225
  • Title

    Unit Commitment under Wind Power and Demand Uncertainties

  • Author

    Pappala, V.S. ; Erlich, I. ; Singh, S.N.

  • Author_Institution
    Inst. of Electr. Power Syst., Univ. Duisburg-Essen, Duisburg
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper addresses a multistage stochastic model for the optimal operation of wind farm, pumped storage and thermal power plants. The output of the wind farm and the electrical demand are considered as two independent stochastic processes. The evolution of these processes over time is modeled as a scenario tree. Considering all possible realizations of stochastic process, leads to a huge set of scenarios. These scenarios are reduced by a particle swarm optimization based scenario reduction algorithm. The scenario tree modeling transforms the cost model to a stochastic model. The stochastic model can be used to estimate the operation costs of the hybrid system under the influence of the uncertainties. The stochastic model is solved using adaptive particle swarm optimization.
  • Keywords
    particle swarm optimisation; power generation planning; wind power; electrical demand uncertainties; multistage stochastic model; particle swarm optimization; pumped storage; scenario reduction algorithm; thermal power plants; unit commitment; wind farm; wind power; Costs; Power generation; Power system modeling; Power system planning; Stochastic processes; Uncertainty; Wind energy; Wind energy generation; Wind farms; Wind power generation; Economic Model; Evolutionary Programming; Multi-stage Scenario tree; Particle Swarm Optimization; Random Process; Stochastic Programming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. Joint International Conference on
  • Conference_Location
    New Delhi
  • Print_ISBN
    978-1-4244-1763-6
  • Electronic_ISBN
    978-1-4244-1762-9
  • Type

    conf

  • DOI
    10.1109/ICPST.2008.4745274
  • Filename
    4745274