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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Abstract

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
PublisherIEEE
Number of pages5
ISBN (Electronic)9781479976935
Publication statusPublished - 29 Jun 2015
EventIEEE PowerTech 2015 - Eindhoven, Netherlands
Duration: 29 Jun 20152 Jul 2015

Conference

ConferenceIEEE PowerTech 2015
CountryNetherlands
CityEindhoven
Period29/06/152/07/15

Keywords

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

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  • Cite this

    Hamilton, D. I., McMillan, D., & Catterson, V. M. (2015). Optimisation of the bidding strategy for wind power trading. In PowerTech, 2015 IEEE Eindhoven IEEE.