Optimisation of the bidding strategy for wind power trading

David I. Hamilton, David McMillan, Victoria M. Catterson

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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The optimal bidding strategy for trading electricity from a wind farm is not always clear. This paper outlines a method for predicting whether the market will be long or short and uses this information to select the best quantile regression for the current market conditions. Results from a simulation with a 2.5MW turbine produced a savings of over £2,000 compared to using only a P50 forecaster.
Original languageEnglish
Title of host publicationPowerTech, 2015 IEEE Eindhoven
Number of pages5
ISBN (Electronic)9781479976935
Publication statusPublished - 29 Jun 2015
EventIEEE PowerTech 2015 - Eindhoven, Netherlands
Duration: 29 Jun 20152 Jul 2015


ConferenceIEEE PowerTech 2015


  • wind energy
  • energy markets
  • quantille regression
  • wind forecasting
  • pricing
  • predictive models
  • artificial neural networks
  • generators
  • wind farms
  • electricity supply industry


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