Current Issue : January-March Volume : 2024 Issue Number : 1 Articles : 5 Articles
Extreme weather events can severely affect the operation and power generation of wind farms and threaten the stability and safety of grids with high penetration of renewable energy. Therefore, it is crucial to forecast the failure and capacity loss of wind farms under extreme weather conditions. To this end, considering the disaster-causing mechanism of severe weather and the operational characteristics of wind farms, this paper first uses the density-based spatial clustering of applications with noise algorithm to cluster the units in the wind farm based on the operating characteristics affected by the weather, and uses correlation analysis methods to extract key disaster-causing factors in extreme weather; then proposes a prediction model based on feature-weighted stacking integration. The model adopts the stacking-integrated learning architecture to support multiple learners and performs feature weighting according to the prediction accuracy of each learner in the base learner, thereby improving the training effect of the meta-learner and improving the prediction accuracy of the model. The prediction model is used to predict each wind turbine group based on the extracted key features and to predict the failure and capacity loss of the wind farm. Finally, an example analysis is performed based on actual data from a wind farm, and the results show that the proposed prediction method can effectively predict the operational reliability of wind farms....
To supply resident loads far from the grid, a stand-alone wind system with a small-scale wind turbine and battery storage can be used. The traditional configuration of the system has a permanent-magnet synchronous generator (PMSG). Other alternative configurations use doubly fed induction generator (DFIG). The systems with DFIG have variable speed operation with a limited speed range which reduces the captured power from the wind turbine. Also, there is a rotor-side converter (RSC) which carries the reactive power of DFIG, in addition to the slip power. In this paper, an improved system configuration with DFIG is controlled by an advanced control scheme. By this advanced scheme, the speed range is increased such that maximum power operation of wind turbine is obtained for complete range of wind speed, and volt-ampere (VA) requirements of RSC are reduced by the operation at nearly zero-slip power....
China currently boasts the largest installed capacity of wind power; however, its output is unstable and highly dependent on weather variability. Despite this, the influence of extreme weather events on wind energy production at the interprovincial scale in China has not been fully characterized. This study aims at investigating the daily variations and regional differences in wind power output during heat wave (HW) and cold wave (CW) days in six regions of China. In addition, the study projects the monthly changes in HW and CW days in the coming decades by utilizing a stacking ensemble machine learning method. The projections are under a real-world warming scenario that incorporates current and long-term actions or policies. The findings of the study reveal that, for most regions, the daily cumulative wind power generation on HW days is close to that on normal days; however, there is a lower output during the daytime and a higher output at night. Furthermore, the number of HW days is projected to increase by 2.3 to 21.8 days during the periods of 2031–2040, 2041–2050, and 2051–2060 in these regions. By comparison, the daily cumulative wind power generation increases significantly on CW days, and the monthly distribution of CW days is expected to undergo notable changes in the future. These findings provide valuable insights into wind resource planning and operation under extreme weather conditions in China....
Fatigue life is a crucial design factor which dictates the safe operation of the wind turbines, but it is influenced by uncertain factors such as environmental loads, analytical models, material properties, and manufacturing methods. In this study, a 1.5MW wind turbine was monitored in operation to understand the fatigue mechanism and enhance wind turbine design. The influence of different operating conditions on fatigue damage was analyzed by correlating strain monitoring data with supervisory control and data acquisition (SCADA) data. Furthermore, a fatigue evaluation method based on measured strain data was proposed. Fatigue damage increases with the increase of wind and rotation speed. More than 50% of the damage occurred at the rated rotation speed state, the corresponding wind speed was greater than the rated wind speed and the pitch control system was active. The findings of this study provide insights for investigating the real fatigue state of similar wind turbine towers and improving the return on investment by closely estimating their service life....
During the actual wind power generation process, wind turbines are often affected by side effects such as blade vibrations, input constraints, and actuator faults. This can lead to a reduction in power generation efficiency and even result in unforeseen losses. This study discusses a robust adaptive fault-tolerant boundary control approach to address the issues of input-constrained and actuator-fault problems in wind turbine blade vibration control. By employing projection mapping techniques and hyperbolic tangent functions, a novel robust adaptive controller based on online dynamic updates is constructed to constrain vibrations, compensate for unknown disturbance upper bounds, and ensure the robustness of the coupled system. Additionally, considering the possibility of actuator faults during the control process, a fault-tolerant controller is proposed to effectively suppress elastic vibrations in the wind turbine blade system even in the presence of actuator faults. The effectiveness of the proposed controller is validated through numerical simulations....
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