Self-tuning fuzzy logic based active power control of wind turbines with pitch and drive train fatigue optimization
Year: 2025
Type: article
Abstract: With the increase in wind power penetration, the stability of power systems faces significant challenges. Existing active power control (APC) strategies, which are crucial for dynamic grid balance, exhibit limitations in balancing the loads of the pitch system and the drive train during active power tracking. To address this issue, this paper proposes a novel APC strategy that incorporates a self-tuning mechanism for fuzzy logic. First, a fuzzy logic-based pitch controller with a dynamic variable-speed range (VSR) is proposed to fully utilize the entire variable-speed region for energy buffering, significantly reducing the load on the pitch system. On this basis, a fuzzy logic-based pitch compensation mechanism is designed to coordinate the pitch controller in balancing the loads between the pitch system and the drive train. By appropriately compensating for pitch signals in response to real-time rotor speed deviations within the VSR, fluctuations in torque are effectively mitigated, thereby significantly reducing the load on the drive train. Furthermore, an online self-tuning strategy is implemented to dynamically update the fuzzy controller’s scaling factors based on changes in the rotor speed regulation error, enhancing the system’s responsiveness under complex wind conditions. Finally, we validate the effectiveness of the proposed strategy through the OpenFAST simulation platform.
Source: AIP Advances
DOI: 10.1063/5.0288398
Authors: Hao Luo, Xuguo Jiao, Ruihua Wang, Lin Wang, Li Gong
Language: English
Topic: Wind Turbine Control Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,350
Awards: G5644715724, G8651826097
OpenAlex ID: W4416364931