Predictability of Wave Energy and Electricity Markets

Julia Fernandez Chozas

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    The articlw addresses an important challenge ahead the integration of the electricity generated by wave energy conversion technologies into the electric grid. Particularly, it looks into the role of wave energy within the day-ahead electricity market. For that the predictability of the theoretical power outputs of three wave energy technologies in the Danish North Sea are examined. The simultaneous and co-located forecast and buoy-measured wave parameters at Hanstholm, Denmark, during a non-consecutive autumn and winter 3-month period form the basis of the investigation.

    The objective of the study is to provide an indication on the accuracy of the forecast of i) wave parameters, ii) the normalised theoretical power productions from each of the selected technologies (Pelamis, Wave Dragon and Wavestar), and iii) the normalised theoretical power production of a combination of the three devices, during a very energetic time period.

    Results show that for the 12 to 36 hours time horizon forecast, the accuracy in the predictions (in terms of scatter index) of the significant wave height, zero crossing period and wave power are 22%, 11% and 68%, respectively; and the accuracy in the predictions of the normalised theoretical power outputs of Pelamis, Wave Dragon and Wavestar are 44%, 52% and 62%, respectively. The best compromise between forecast accuracy and mean power production results when considering the combined production of the three devices.
    Original languageEnglish
    JournalModern Energy Review
    Volume4
    Issue number1
    Pages (from-to)57-59
    Number of pages3
    Publication statusPublished - 2012

    Keywords

    • Wave Energy
    • Electricity Market
    • Grid Integration
    • Power Output
    • Predictability
    • Denmark
    • North Sea
    • Hanstholm
    • Pelamis
    • Wave Dragon
    • Wavestar

    Fingerprint

    Dive into the research topics of 'Predictability of Wave Energy and Electricity Markets'. Together they form a unique fingerprint.

    Cite this