TY  - EJOU
AU  - Yang, Yinguo 
AU  - Ding, Lifu 
AU  - Liu, Yang 
AU  - Wang, Bingchen 
AU  - Wang, Weihua 
AU  - Chen, Ying 

TI  - A Partitioned Yaw Control Algorithm for Wind Farms Using Dynamic Wake Modeling
T2  - Energy Engineering

PY  - 2025
VL  - 122
IS  - 7
SN  - 1546-0118

AB  - 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.
KW  - Wind farm; wind turbine; yaw control; wind farm partition; distributed optimization

DO  - 10.32604/ee.2025.065716