scholarly journals Cost-Sensitive Extremely Randomized Trees Algorithm for Online Fault Detection of Wind Turbine Generators

2021 ◽  
Vol 9 ◽  
Author(s):  
Mingzhu Tang ◽  
Yutao Chen ◽  
Huawei Wu ◽  
Qi Zhao ◽  
Wen Long ◽  
...  
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Feature Selection Method ◽  
Misclassification Cost ◽  
Imbalanced Classification ◽  
Extremely Randomized Trees ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Doubly Fed ◽  
The Cost

The number of normal samples of wind turbine generators is much larger than the number of fault samples. To solve the problem of imbalanced classification in wind turbine generator fault detection, a cost-sensitive extremely randomized trees (CS-ERT) algorithm is proposed in this paper, in which the cost-sensitive learning method is introduced into an extremely randomized trees (ERT) algorithm. Based on the classification misclassification cost and class distribution, the misclassification cost gain (MCG) is proposed as the score measure of the CS-ERT model growth process to improve the classification accuracy of minority classes. The Hilbert-Schmidt independence criterion lasso (HSICLasso) feature selection method is used to select strongly correlated non-redundant features of doubly-fed wind turbine generators. The effectiveness of the method was verified by experiments on four different failure datasets of wind turbine generators. The experiment results show that average missing detection rate, average misclassification cost and gMean of the improved algorithm better than those of the ERT algorithm. In addition, compared with the CSForest, AdaCost and MetaCost methods, the proposed method has better real-time fault detection performance.

scholarly journals Improved Low Voltage Ride Through Capability of Wind Farm using STATCOM

2021 ◽  
Author(s):  
Miad Mohaghegh Montazeri
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Reactive Power ◽  
Low Voltage ◽  
Steady State Condition ◽  
Low Voltage Ride Through ◽  
Induction Generators ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Doubly Fed

Using power electronic converters with reduced capacity in doubly-fed induction generator (DFIG) based wind turbines make them vulnerable to over-current during grid disturbances. This thesis aims to analyze the behaviour of doubly-fed induction generators based wind farm for various timing schemes of crowbar deactivation and resumption of rotor side converter (RSC) in the case of grid fault. Also, usage of a static synchronous compensator (STATCOM) for the purpose of stabilizing the grid voltage after a three-phase fault is studied in this these. Moreover, finding minimum capacity of STATCOM which ensures low-voltage ride through (LVRT) of wind farm is studied. Finally, coordination of reactive power from wind turbine generators and STATCOM in steady-state condition is performed. All the results in this thesis show that STATCOM improves low voltage ride through (LVRT) capability of wind farm and assists for an uninterrupted operation of wind turbine generators during grid faults.

Bayesian Networks in Electric Reliability Assessment of Doubly-Fed Wind Turbine Generator

2014 ◽  
Vol 494-495 ◽  
pp. 1791-1794 ◽  
Author(s):  
Hai Ning Pan ◽  
Ming Qin ◽  
Jun Zhang ◽  
Chao Chang ◽  
Pan Lei
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Reliability Assessment ◽  
Turbine Generator ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Reliability Methods ◽  
Doubly Fed ◽  
Electrical Components ◽  
Large Wind

For the development of large wind turbines, the approach of trial and error is also not adequate for mass produced wind turbines, a reliability-concerned manufacturing must be involved for the future development. An approach which introduces probabilistic reliability assessment which incorporates reliability methods into wind turbine engineering is described. Fault Tree of wind turbine generators electrical components is firstly built. Then it is transformed to the Bayesian network and probabilistic distribution is preceded using Markov chain Monte Carlo inference. Finally a set of qualitative and quantitative reliability is given according to a specific probabilistic input.

scholarly journals Cost-Sensitive LightGBM-Based Online Fault Detection Method for Wind Turbine Gearboxes

2021 ◽  
Vol 9 ◽  
Author(s):  
Mingzhu Tang ◽  
Qi Zhao ◽  
Huawei Wu ◽  
Zimin Wang
Keyword(s):  
Fault Detection ◽  
False Alarm ◽  
Wind Turbine ◽  
False Alarm Rate ◽  
Detection Rate ◽  
Rank Correlation ◽  
Spearman Rank Correlation ◽  
Misclassification Cost ◽  
Spearman Rank ◽  
The Cost

In practice, faulty samples of wind turbine (WT) gearboxes are far smaller than normal samples during operation, and most of the existing fault diagnosis methods for WT gearboxes only focus on the improvement of classification accuracy and ignore the decrease of missed alarms and the reduction of the average cost. To this end, a new framework is proposed through combining the Spearman rank correlation feature extraction and cost-sensitive LightGBM algorithm for WT gearbox’s fault detection. In this article, features from wind turbine supervisory control and data acquisition (SCADA) systems are firstly extracted. Then, the feature selection is employed by using the expert experience and Spearman rank correlation coefficient to analyze the correlation between the big data of WT gearboxes. Moreover, the cost-sensitive LightGBM fault detection framework is established by optimizing the misclassification cost. The false alarm rate and the missed detection rate of the WT gearbox under different working conditions are finally obtained. Experiments have verified that the proposed method can significantly improve the fault detection accuracy. Meanwhile, the proposed method can consistently outperform traditional classifiers such as AdaCost, cost-sensitive GBDT, and cost-sensitive XGBoost in terms of low false alarm rate and missed detection rate. Owing to its high Matthews correlation coefficient scores and low average misclassification cost, the cost-sensitive LightGBM (CS LightGBM) method is preferred for imbalanced WT gearbox fault detection in practice.

Sign in / Sign up

Export Citation Format

Share Document