English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

With the rapid growth of wind power penetration, wind farms (WFs) arerequired to implement frequency regulation that active power control to track agiven power reference. Due to the wake interaction of the wind turbines (WTs),there is more than one solution to distributing power reference among theoperating WTs, which can be exploited as an optimization problem for the secondgoal, such as fatigue load alleviation. In this paper, a closed-loop modelpredictive controller is developed that minimizes the wind farm trackingerrors, the dynamical fatigue load, and and the load equalization. Thecontroller is evaluated in a mediumfidelity model. A 64 WTs simulation casestudy is used to demonstrate the control performance for different penaltyfactor settings. The results indicated the WF can alleviate dynamical fatigueload and have no significant impact on power tracking. However, the uneven loaddistribution in the wind turbine system poses challenges for maintenance. Byadding a trade-off between the load equalization and dynamical fatigue load,the load differences between WTs are significantly reduced, while the dynamicalfatigue load slightly increases when selecting a proper penalty factor.

Model predictive control strategy in waked wind farms for optimal fatigue loads