This paper presents a new active power control algorithm designed to maximize the power reserve of the individual turbines in a farm, in order to improve the tracking accuracy of a power reference signal. The control architecture is based on an open-loop optimal set-point scheduler combined with a feedback corrector, which actively regulate power by both wake steering and induction control. The methodology is compared with a state-of-the-art PI-based controller by means of high-fidelity LES simulations. The new wind farm controller reduces the occurrence of local saturation events, thereby improving the overall tracking accuracy, and limits fatigue loading in conditions of relatively high-power demand.
@article{arxiv.2307.04366,
title = {A New Wind Farm Active Power Control Strategy to Boost Tracking Margins in High-demand Scenarios},
author = {Simone Tamaro and Carlo L. Bottasso},
journal= {arXiv preprint arXiv:2307.04366},
year = {2023}
}