In response to the severe challenges posed by extreme sandstorm weather to the operational safety of WTs and grid stability, this paper proposes an MPC-based power optimization control strategy for WFs. Simulation results indicate that, compared with the traditional PD strategy, the proposed MPC strategy significantly reduces the active power fluctuations of individual WTs, smoothly tracks grid dispatch orders with an overall power tracking accuracy improvement, and effectively lowers the operational risk index of turbines across the farm (ranging from 6.90% to 57.14% for the ten evaluated turbines). Furthermore, the proposed strategy substantially mitigates the angular acceleration fluctuation amplitude of the drive train components (e.g., reducing peak angular accelerations of drive-train masses by up to 35%) and reduces the fore-aft and lateral displacement oscillations of the tower top (reducing peak displacement variations by approximately 25% and 40%, respectively), providing comprehensive structural load mitigation while ensuring WF power output stability and grid safety. This study provides a theoretical basis and technical approach for the intelligent operation and risk prevention and control of WFs under extreme meteorological conditions.
Jun Zhao, Yu-Xiang Li, Xue-Ting Cheng et al.· Technologies· 0 citations
The polishing head is one of the most important components in the chemical mechanical polishing (CMP) process, used to achieve an ultra-smooth surface on the wafer. Due to the effect of the retaining ring and the replacement of the polishing pad, the polishing process is subjected to drift and shift interference. The CMP head with partition pressure is designed to exert pressure separately according to the situation of the wafer edge being affected, and compensate for the disturbance caused by slight changes in different areas inside the wafer. A run-to-run (R2R) control method based on deep reinforcement learning (DRL) is proposed to adjust the process parameters between runs. A dual experience replay mechanism is adopted to effectively utilize the interactive information between the agent and the CMP environment designed. Simulation experiments are conducted under the conditions of pad drift and pad replacement. Results demonstrate that the proposed method achieves superior performance in MRR optimization. The WIWNU is optimized to a minimum of 0.3%, and the maximum difference of the polished wafer thickness under the two experimental conditions is below 25 nm. Thus, the proposed method can effectively compensate for the drift caused by equipment aging, and can sense environmental changes and adjust process parameters.
