TY - JOUR
T1 - A coordinated control strategy for active transient voltage support in DFIG-based wind farms
AU - Yuyan, Song
AU - Yang, Liu
AU - Yongjie, Zhang
AU - Shuai, Zhang
AU - Xiaodi, Wang
AU - Fang, Liu
AU - Yunche, Su
N1 - Publisher Copyright:
Copyright © 2025 Yuyan, Yang, Yongjie, Shuai, Xiaodi, Fang and Yunche.
PY - 2025
Y1 - 2025
N2 - During the implementation of active voltage support in wind farms, coordinating the operation of multiple wind turbines presents significant challenges. The dynamic response of the entire wind farm becomes complex during grid faults, making it difficult to achieve coordinated voltage support across different wind turbines. To address this, a coordination control strategy for doubly fed wind farms is here proposed which is based on Q-learning informed by the sensitivity of voltage. First, a method for calculating the voltage sensitivity of DFIG-based wind farms is introduced, utilizing the arbitrary polynomial chaos approach. Additionally, the operational constraints of wind farms are defined based on the average short-circuit ratio of reactive power. The voltage support characteristics of multi-machine wind farms under grid fault conditions are then thoroughly explored. Subsequently, an improved Q-learning algorithm is developed, based on the sensitivity of voltage. This algorithm aids in optimizing the control commands, thus enhancing the effectiveness of the voltage support system. Finally, adopting this voltage sensitivity as the basis for the coordinated control commands and applying the improved Q-learning algorithm as the implementation mechanism, a coordinated control strategy for active voltage support in DFIG-based wind farms is proposed. Simulation results demonstrate that the proposed control strategy can provide effective active voltage support during grid faults.
AB - During the implementation of active voltage support in wind farms, coordinating the operation of multiple wind turbines presents significant challenges. The dynamic response of the entire wind farm becomes complex during grid faults, making it difficult to achieve coordinated voltage support across different wind turbines. To address this, a coordination control strategy for doubly fed wind farms is here proposed which is based on Q-learning informed by the sensitivity of voltage. First, a method for calculating the voltage sensitivity of DFIG-based wind farms is introduced, utilizing the arbitrary polynomial chaos approach. Additionally, the operational constraints of wind farms are defined based on the average short-circuit ratio of reactive power. The voltage support characteristics of multi-machine wind farms under grid fault conditions are then thoroughly explored. Subsequently, an improved Q-learning algorithm is developed, based on the sensitivity of voltage. This algorithm aids in optimizing the control commands, thus enhancing the effectiveness of the voltage support system. Finally, adopting this voltage sensitivity as the basis for the coordinated control commands and applying the improved Q-learning algorithm as the implementation mechanism, a coordinated control strategy for active voltage support in DFIG-based wind farms is proposed. Simulation results demonstrate that the proposed control strategy can provide effective active voltage support during grid faults.
KW - active voltage support
KW - coordinated control
KW - DFIG-based Wind farm
KW - Q-learning
KW - reactive power voltage sensitivity
UR - http://www.scopus.com/inward/record.url?scp=105003551323&partnerID=8YFLogxK
U2 - 10.3389/fenrg.2025.1566923
DO - 10.3389/fenrg.2025.1566923
M3 - 文章
AN - SCOPUS:105003551323
SN - 2296-598X
VL - 13
JO - Frontiers in Energy Research
JF - Frontiers in Energy Research
M1 - 1566923
ER -