相似分群方法在風場風機故障檢測的應用研究

Study on the Application of Similar Clustering Approach in Wind Turbine Fault Detection

謝佩鈞(Pei-Chun, Hsieh)

指導教授 ： 蔡進發

國立臺灣大學/工學院/工程科學及海洋工程學研究所/碩士(2017年)

https://doi.org/10.6342/NTU201703624

摘要

本研究以相似分群方法建立風場中風機故障檢測與性能評估之流程，並分為風場集群分析與風場風機性能評估與異常偵測兩部分進行。其中風場集群分析利用每部風機量測的風速與風向資料，透過高斯混合模型建立風況模型後以信心值量測彼此間的相似性，並利用聚合階層式分群法分群。再根據分群結果針對同群内風機的功率、轉子轉速、葉片旋角與偏航誤差之資料，同樣透過高斯混合模型與信心值做相似性的測量，並逐日比對群內不同風機間行為是否相異。
　　本研究利用台電彰濱風場23部風機資料進行分析，結果顯示風場在這季中的風況可分為風向偏北方的群集一以及風向偏東北方的群集二。並且在群集一中22號風機異常發生次數最多而7號風機無偵測出異常；群集二則是4號風機最多異常而12號風機無偵測出異常。同時比較各項參數之信心值發現，同群中有風機葉片旋角信心值在0.6以下者大多功率信心值也低於0.5；而轉子轉速與葉片旋角無異常發生，但偏航誤差信心值較低者功率信心值也低於0.5。

關鍵字

風力發電機 ； 相似分群方法 ； 高斯混合模型

並列摘要

A method of fault detection based on similar clustering approach for the wind turbines within a wind farm is proposed in this study. The SCADA datas were used for the clustering and fault detection. The wind speed and wind direction were used for the clustering approach. The Gaussain distribution was derived for each turbine with the parameters of wind speed and wind direction. Then the confidence values (CV) were calculated between turbines based on the Gaussian distribution of wind speed and direction. The turbines were clustered by the hierarchical clustering method with the value of 1-CV. Then the Gaussian distributions of power, rotor speed, pitch angle of balde and yawing misalightment were calculated within the same cluster. The confidence value of these parameters between turbines were used to figure out the abnormal operation turbine.
The SCADA datas of 23 wind turbines of Taipower which is located in Chang Hua Costal Industry Park were used for the analysis in this study. The turbines can be clustered into two groups. The first group has the wind direction from the north and the second group has the wid direction from northeast based on the wind datas from SACDA. The fault analysis shows that the No. 22 wind turbine of group 1 had most abnormal operations and the No.7 wind turbine of group 1 had no abnormal operation. It also shows that the No. 4 wind turbine of group 2 had most abnormal operations and the No. 12 wind turbine of group 2 operated smoothly without any abnormal operation. It is found that the confidence value of power is smaller than 0.5 when the confidence value of pitch angle is smaller than 0.6. And the confidemce value of power is low when the confidence value of the yawing misalightment is smaller than 0.5.

並列關鍵字

Wind Turbines ； Similar Clustering Approach ； Gaussian Mixture Model

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