IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v8y2014i1p233-256d44083.html
   My bibliography  Save this article

A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming

Author

Listed:
  • Wushan Cheng

    (School of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)

  • Haifeng Zhang

    (School of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)

Abstract

In order to maintain the stability and security of the power system, the uncertainty and intermittency of wind power must be taken into account in economic dispatch (ED) problems. In this paper, a dynamic economic dispatch (DED) model based on chance constrained programming is presented and an improved particle swarm optimization (PSO) approach is proposed to solve the problem. Wind power is regarded as a random variable and is included in the chance constraint. New formulation of up and down spinning reserve constraints are presented under expectation meaning. The improved PSO algorithm combines a feasible region adjustment strategy with a hill climbing search operation based on the basic PSO. Simulations are performed under three distinct test systems with different generators. Results show that both the proposed DED model and the improved PSO approach are effective.

Suggested Citation

  • Wushan Cheng & Haifeng Zhang, 2014. "A Dynamic Economic Dispatch Model Incorporating Wind Power Based on Chance Constrained Programming," Energies, MDPI, vol. 8(1), pages 1-24, December.
  • Handle: RePEc:gam:jeners:v:8:y:2014:i:1:p:233-256:d:44083
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/8/1/233/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/8/1/233/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Zhou & Hui Sun & Yu Peng, 2010. "Risk Reserve Constrained Economic Dispatch Model with Wind Power Penetration," Energies, MDPI, vol. 3(12), pages 1-15, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Fan & Bie, Zhaohong & Liu, Shiyu & Ding, Tao, 2017. "Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements," Applied Energy, Elsevier, vol. 188(C), pages 399-408.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jin, Xin & Zhang, Zhaolong & Shi, Xiaoqiang & Ju, Wenbin, 2014. "A review on wind power industry and corresponding insurance market in China: Current status and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 1069-1082.
    2. Ying-Yi Hong & Gerard Francesco DG. Apolinario, 2021. "Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications," Energies, MDPI, vol. 14(20), pages 1-47, October.
    3. Li, Cun-bin & Li, Peng & Feng, Xia, 2014. "Analysis of wind power generation operation management risk in China," Renewable Energy, Elsevier, vol. 64(C), pages 266-275.
    4. Xie, Min & Ji, Xiang & Hu, Xintong & Cheng, Peijun & Du, Yuxin & Liu, Mingbo, 2018. "Autonomous optimized economic dispatch of active distribution system with multi-microgrids," Energy, Elsevier, vol. 153(C), pages 479-489.
    5. Kyung-bin Kwon & Hyeongon Park & Jae-Kun Lyu & Jong-Keun Park, 2016. "Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand," Energies, MDPI, vol. 9(10), pages 1-16, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:8:y:2014:i:1:p:233-256:d:44083. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.