IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v133y2017icp380-387.html
   My bibliography  Save this article

Stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources

Author

Listed:
  • Hemmati, Reza
  • Saboori, Hedayat
  • Jirdehi, Mehdi Ahmadi

Abstract

This paper presents an optimal planning and scheduling on energy storage systems (ESSs) for congestion management in electric power systems including renewable energy resources. The proposed problem finds optimal capacity and charging-discharging regime of ESSs. The storage units are optimally charged and discharged to tackle the uncertainty related to wind-solar units as well as relief congestion in the lines. Output power of solar and wind units is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to tackle the uncertainty. Simulation results demonstrate that the proposed planning can manage congestion of the network efficiently while dealing with wind and solar resources uncertainties.

Suggested Citation

  • Hemmati, Reza & Saboori, Hedayat & Jirdehi, Mehdi Ahmadi, 2017. "Stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources," Energy, Elsevier, vol. 133(C), pages 380-387.
  • Handle: RePEc:eee:energy:v:133:y:2017:i:c:p:380-387
    DOI: 10.1016/j.energy.2017.05.167
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421730957X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.05.167?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:energy:v:133:y:2017:i:c:p:380-387. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.