IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-1-4419-1129-2_10.html
   My bibliography  Save this book chapter

Generation of Synthetic Sequences of Electricity Demand with Applications

In: Uncertainty and Environmental Decision Making

Author

Listed:
  • J. W. Boland

    (University of South Australia, Mawson Lakes Boulevard, Mawson Lakes)

Abstract

We have developed a model to generate synthetic sequences of half hourly electricity demand. The generated sequences represent possible realisations of electricity load that can have occurred. Each of the components included in the model has a physical interpretation. These components are yearly and daily seasonality which were modelled using Fourier series, weekly seasonality modelled with dummy variables, and the relationship with current temperature described by polynomial functions of temperature. Finally the stochastic componentwas modelled with ARMA processes. The temperature series was modelled in a similar fashion. The stochastic modelling was performed to build probability distributions of the outputs to calculate probabilistic forecasts.As one application several summers of half hourly electricity demand were generated and from them the value of demand that is not expected to be exceeded more than once in ten years was calculated. Additionally, the bivariate temperature and demand model was used in software designed to optimise the orientation of photovoltaic cells to match demand.

Suggested Citation

  • J. W. Boland, 2009. "Generation of Synthetic Sequences of Electricity Demand with Applications," International Series in Operations Research & Management Science, in: Jerzy A. Filar & Alain Haurie (ed.), Uncertainty and Environmental Decision Making, chapter 0, pages 275-314, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-1129-2_10
    DOI: 10.1007/978-1-4419-1129-2_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:isochp:978-1-4419-1129-2_10. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.