Wind farm set point optimization with surrogate models for load and power output targets

Nikolay Dimitrov*, Anand Natarajan

*Corresponding author for this work

    Research output: Contribution to journalConference articleResearchpeer-review

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    Abstract

    This study presents a methodology for wind farm set point optimization, which allows including both loads and power output as optimization criteria. The primary control strategy investigated involves de-rating of individual turbines in the wind farm. The optimal de-rating level of each individual turbine is determined by using accurate and computationally efficient surrogate models, mapping the dependency between the choice of de-rating strategy for a given turbine and the load and power outputs of downwind turbines. A case study based on the Lillgrund offshore wind farm shows that for specific wind directions with strong wake interactions, it may be possible to achieve a net gain in power output in the order of 5% at specific mean wind speeds. Alternatively, maintaining nominal power output but optimizing the load distribution could lead to substantial fatigue load reductions.
    Original languageEnglish
    Article number012013
    Book seriesJournal of Physics: Conference Series
    Volume2018
    Issue number1
    Number of pages12
    ISSN1742-6596
    DOIs
    Publication statusPublished - 2021
    EventEERA DeepWind’2021 - 18th Deep Sea Offshore Wind R&D Conference - Online event
    Duration: 13 Jan 202115 Jan 2021
    Conference number: 18
    https://www.eerajpwind.eu/events/eera-deepwind-conference-2021/

    Conference

    ConferenceEERA DeepWind’2021 - 18th Deep Sea Offshore Wind R&D Conference
    Number18
    LocationOnline event
    Period13/01/202115/01/2021
    Internet address

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