Wind Farm Power Production and Fatigue Load Optimization Through Wake Steering

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Abstract

Wake steering has proven potential to increase
wind farm production. However, this control strategy prioritizes
the maximum power without considering the effects of fatigue
load, a remaining life indicator on a wind turbine component.
Reducing fatigue loads is one of the most important goals
of wind farm control, especially for long-established wind
farms. Therefore, it is crucial to consider the fatigue load
when optimizing the yaw angles. This paper proposes a multiobjective
wake steering control strategy to balance power
production and fatigue load. Firstly, a power production model
based on Gauss–Curl Hybrid (GCH) wake model is introduced
to estimate the farm power. Secondly, a fatigue load prediction
model is proposed based on Gaussian Process Regression
(GPR). Finally, the Particle Swarm Optimization (PSO) method
is adopted to optimize the yaw offset by considering the tradeoff
between power production and fatigue load. The proposed
balancing strategy shows an increase in power generation by
16% compared to the baseline strategy (Greedy strategy) while
reducing the average and maximum fatigue load by 12% and
10%, respectively.
Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
Number of pages6
PublisherIEEE
Publication dateAug 2023
ISBN (Print)979-8-3503-2070-1
ISBN (Electronic)979-8-3503-2069-5
DOIs
Publication statusPublished - Aug 2023
Event19th International Conference on Automation Science and Engineering (CASE) - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Conference

Conference19th International Conference on Automation Science and Engineering (CASE)
Country/TerritoryNew Zealand
CityAuckland
Period26/08/202330/08/2023
SeriesIEEE International Conference on Automation Science and Engineering
ISSN2161-8070

Keywords

  • Wind Farm
  • Flow Control
  • Yaw control
  • Power
  • Load reduction

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