Multiple-feedback control of power output and platform pitching motion for a floating offshore wind turbine-generator system

Energy ◽  
2017 ◽  
Vol 141 ◽  
pp. 563-578 ◽  
Author(s):  
Tetsuya Wakui ◽  
Motoki Yoshimura ◽  
Ryohei Yokoyama
2016 ◽  
Vol 41 (1) ◽  
pp. 26-42 ◽  
Author(s):  
Tetsuya Wakui ◽  
Motoki Yoshimura ◽  
Ryohei Yokoyama

Novel parameter settings for gain-scheduled feedback control of rotational speed using collective blade pitch manipulation in a spar-buoy floating offshore wind turbine–generator system were developed in order to reduce both power-output fluctuation and platform motion. The development was conducted through numerical simulation using the aeroelastic simulation model (FAST), measured high wind speed data, and simulated irregular sea waves. In this gain-scheduled feedback control of rotational speed, a proportional-plus-integral action was employed, and the proportional gain was varied to the blade pitch angle. First, the sensitivity analysis of the control parameter settings, that is, the proportional gain, integral time, and the generator torque manipulation strategy, to the system performances was carried out. Then, a new guideline of parameter settings for the gain-scheduled feedback control was theoretically revealed by investigating the damped oscillation characteristics of the feedback control loop. Novel parameter settings yielded a natural frequency of the feedback control loop higher than that of the platform pitching motion and a damping coefficient larger than 1.0. Under these parameter settings, the platform pitching motion was similar to that under settings previously developed for this floating offshore system, while the power-output fluctuation was drastically reduced. High power–generation performance and a significant reduction in the damage equivalent fatigue loads at the main parts of the system were also obtained.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Mingzhu Tang ◽  
Zijie Kuang ◽  
Qi Zhao ◽  
Huawei Wu ◽  
Xu Yang

In response to the unbalanced sample categories and complex sample distribution of the operating data of the pitch system of the wind turbine generator system, this paper proposes a method for fault detection of the pitch system of the wind turbine generator system based on the multiclass optimal margin distribution machine. In this method, the power output of the wind turbine generator system is used as the main status parameter, and the operating data history of the wind turbine generator system in the wind power supervisory control and data acquisition (SCADA) system is subject to correlation analysis with the Pearson correlation coefficient, to eliminate the features that have low correlation with the power output status parameter. Secondary analysis is performed to the remaining features, thus reducing the number and complexity of samples. Datasets are divided into the training set for training of the multiclass optimal margin distribution machine fault detection model and test set for testing. Experimental verification was carried out with the operating data of one wind farm in China. Experimental results show that, compared with other support vector machines, the proposed method has higher fault detection accuracy and precision and lower false-negative rate and false-positive rate.


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