@Article{ee.2025.065716,
AUTHOR = {Yinguo Yang, Lifu Ding, Yang Liu, Bingchen Wang, Weihua Wang, Ying Chen},
TITLE = {A Partitioned Yaw Control Algorithm for Wind Farms Using Dynamic Wake Modeling},
JOURNAL = {Energy Engineering},
VOLUME = {122},
YEAR = {2025},
NUMBER = {7},
PAGES = {2571--2587},
URL = {http://www.techscience.com/energy/v122n7/62685},
ISSN = {1546-0118},
ABSTRACT = {This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn (FLOW Redirection and Induction Dynamics) dynamic wake model. First, the impact of wakes on turbine effective wind speed is analyzed, leading to a quantitative method for assessing wake interactions. Based on these interactions, a partitioning method divides the wind farm into smaller, computationally manageable zones. Subsequently, a heuristic control algorithm is developed for yaw optimization within each partition, reducing the overall computational burden associated with multi-turbine optimization. The algorithm’s effectiveness is evaluated through case studies on 11-turbine and 28-turbine wind farms, demonstrating power generation increases of 9.78% and 1.78%, respectively, compared to baseline operation. The primary innovation lies in coupling the higher-fidelity dynamic FLORIDyn wake model with a graph-based partitioning strategy and a computationally efficient heuristic optimization, enabling scalable and accurate yaw control for large wind farms, overcoming limitations associated with simplified models or centralized optimization approaches.},
DOI = {10.32604/ee.2025.065716}
}