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 language | English |
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Article number | 012013 |
Book series | Journal of Physics: Conference Series |
Volume | 2018 |
Issue number | 1 |
Number of pages | 12 |
ISSN | 1742-6596 |
DOIs | |
Publication status | Published - 2021 |
Event | EERA DeepWind’2021 - 18th Deep Sea Offshore Wind R&D Conference - Online event Duration: 13 Jan 2021 → 15 Jan 2021 Conference number: 18 https://www.eerajpwind.eu/events/eera-deepwind-conference-2021/ |
Conference
Conference | EERA DeepWind’2021 - 18th Deep Sea Offshore Wind R&D Conference |
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Number | 18 |
Location | Online event |
Period | 13/01/2021 → 15/01/2021 |
Internet address |