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Scheduling electric power production at a wind farm


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  • Zhang, Zijun
  • Kusiak, Andrew
  • Song, Zhe
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    We present a model for scheduling power generation at a wind farm, and introduce a particle swarm optimization algorithm with a small world network structure to solve the model. The solution generated by the algorithm defines the operational status of wind turbines for a scheduling horizon selected by a decision maker. Different operational scenarios are constructed based on time series data of electricity price, grid demand, and wind speed. The computational results provide insights into management of a wind farm.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 224 (2013)
    Issue (Month): 1 ()
    Pages: 227-238

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    Handle: RePEc:eee:ejores:v:224:y:2013:i:1:p:227-238

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    Keywords: Scheduling; Evolutionary computations; Wind farm; Particle swarm optimization; Small world network;


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    1. Kusiak, Andrew & Zheng, Haiyang & Song, Zhe, 2009. "On-line monitoring of power curves," Renewable Energy, Elsevier, vol. 34(6), pages 1487-1493.
    2. Kusiak, Andrew & Li, Mingyang, 2010. "Reheat optimization of the variable-air-volume box," Energy, Elsevier, vol. 35(5), pages 1997-2005.
    3. Kim, Byung-In & Kim, Seongbae & Park, Junhyuk, 2012. "A school bus scheduling problem," European Journal of Operational Research, Elsevier, vol. 218(2), pages 577-585.
    4. Kusiak, Andrew & Zheng, Haiyang & Song, Zhe, 2009. "Models for monitoring wind farm power," Renewable Energy, Elsevier, vol. 34(3), pages 583-590.
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