Xiaodong Wang

This paper addresses a critical and often overlooked challenge: drivetrain fatigue in wind turbines (WTs) induced by primary frequency regulation (PFR) operations, particularly below rated wind speed. While existing PFR strategies focus on grid support, they rarely offer mechanisms to simultaneously mitigate the mechanical stress they impose. To overcome this, a Model Predictive Control (MPC) strategy is proposed that adaptively adjusts the PFR gain in real time. First, the boundary characteristics of the de-loading factor under varying wind speeds and PFR gains are systematically analyzed. This analysis bridges a critical gap in prior studies, which predominantly adopted fixed-gain strategies without comprehensively evaluating their fatigue implications. Building on these boundary characteristics, an MPC framework is developed to optimally adjust the frequency regulation gain in real time. This approach achieves an optimization by minimizing drivetrain torque fluctuations for fatigue mitigation, critically informed by a comprehensive boundary analysis of de-loading factors, while rigorously ensuring essential PFR support capability through explicit operational constraints. Extensive simulations demonstrate the superior performance of the proposed MPC, achieving a simultaneous reduction of up to 27.99% in drivetrain fatigue load and 14.44% in frequency deviations compared to conventional methods. This work significantly enhances the mechanical reliability of WTs and facilitates their more sustainable integration into modern power grids by offering a unique solution to a long-standing trade-off.

A sub-synchronous oscillation (SSO) suppression strategy of attaching virtual resistance controllers to the rotor-side converter (RSC) of the doubly-fed induction generator (DFIG) is proposed in this study to suppress sub-synchronous oscillation (SSO) caused by series compensation and grid connection of DFIG. A DFIG-based frequency domain impedance model considering RSC control under small signal perturbations is developed in a three-phase stationary coordinate system. Subsequently, the factors and mechanisms of SSO in the system with different phase sequences are analyzed in combination with the equivalent RLC resonant circuit of a DFIG-based series-compensated grid-connected system (SCGCS). SSO occurs when RSC and rotor winding generate a large equivalent negative resistance at the SSO frequency, resulting in a negative total system resistance. Additionally, the influences of series compensation degree (SCD) of line and inner loop parameters (ILPs) of RSC related to the total impedance of the system on the SSO characteristics are analyzed to optimize the parameters and improve the system stability. Based on the causes of SSO, virtual resistance controllers are attached to RSC to provide positive resistance to the system and to offset the equivalent negative resistance of RSC and rotor winding at the SSO frequency, thereby avoiding SSO of the system. Finally, time-domain simulations using power system computer aided design/electromagnetic transients including dc (PSCAD/EMTDC) show that the SSO of the system is effectively suppressed.

This paper proposes an active power control method for supporting grid frequency regulation in wind farms (WF) considering improved fatigue load sensitivity of wind turbines (WT). The control method is concluded into two parts: frequency adjustment control (FAC) and power reference dispatch (PRD). On one hand, the proposed Fuzzy-PID control method can actively maintain the balance between power generation and grid load, by which the grid frequency is regulated when plenty of winds are available. The fast power response can be provided and frequency error can be reduced by the proposed method. On the other hand, the sensitivity of the WT fatigue loads to the power references is improved. The explicit analytical equations of the fatigue load sensitivity are re-derived to improve calculation accuracy. In the process of the optimization dispatch, the re-defined fatigue load sensitivity will be used to minimize fatigue load. Case studies were conducted with a WF under different grid loads and turbulent wind with different intensities. By comparing the frequency response of the WF, rainflow cycle, and Damage Equivalent Load (DEL) of the WT, the efficacy of the proposed method is verified.