电力系统自动化
電力繫統自動化
전력계통자동화
AUTOMATION OF ELECTRIC POWER SYSTEMS
2015年
13期
32-37
,共6页
李辉%杨东%杨超%胡姚刚%刘志祥%兰涌森
李輝%楊東%楊超%鬍姚剛%劉誌祥%蘭湧森
리휘%양동%양초%호요강%류지상%란용삼
风力发电%叶轮不平衡%双馈感应发电机%定子电流%故障诊断%故障特征频率
風力髮電%葉輪不平衡%雙饋感應髮電機%定子電流%故障診斷%故障特徵頻率
풍력발전%협륜불평형%쌍궤감응발전궤%정자전류%고장진단%고장특정빈솔
wind power generation%blade imbalance%doubly fed induction generator (DFIG)%stator current%fault diagnosis%fault feature frequency
针对双馈风电机组叶轮不平衡故障诊断,提出一种基于导数分析的定子单相电流故障特征分析方法。首先,基于双馈感应发电机以及风力机传动链模型,详细推导了叶轮不平衡故障下双馈感应发电机定子电流的表达式,并获得其对应的故障特征频率。其次,为了凸显定子电流故障特征频率,基于导数分析思路,引入叶轮不平衡下定子电流故障特征定义及其表达式,提出基于定子单相电流的叶轮不平衡故障诊断方法。最后,建立考虑叶轮不平衡故障的双馈风电机组仿真模型,对机组在不同风速和不平衡度下的故障特征进行仿真分析。结果表明与直接对定子电流、叶轮转速进行频谱分析相比,所述方法能够有效地提取出叶轮不平衡故障特征,且通过监测特征频率幅值的变化情况,可以有效地判断出不平衡故障严重程度。
針對雙饋風電機組葉輪不平衡故障診斷,提齣一種基于導數分析的定子單相電流故障特徵分析方法。首先,基于雙饋感應髮電機以及風力機傳動鏈模型,詳細推導瞭葉輪不平衡故障下雙饋感應髮電機定子電流的錶達式,併穫得其對應的故障特徵頻率。其次,為瞭凸顯定子電流故障特徵頻率,基于導數分析思路,引入葉輪不平衡下定子電流故障特徵定義及其錶達式,提齣基于定子單相電流的葉輪不平衡故障診斷方法。最後,建立攷慮葉輪不平衡故障的雙饋風電機組倣真模型,對機組在不同風速和不平衡度下的故障特徵進行倣真分析。結果錶明與直接對定子電流、葉輪轉速進行頻譜分析相比,所述方法能夠有效地提取齣葉輪不平衡故障特徵,且通過鑑測特徵頻率幅值的變化情況,可以有效地判斷齣不平衡故障嚴重程度。
침대쌍궤풍전궤조협륜불평형고장진단,제출일충기우도수분석적정자단상전류고장특정분석방법。수선,기우쌍궤감응발전궤이급풍력궤전동련모형,상세추도료협륜불평형고장하쌍궤감응발전궤정자전류적표체식,병획득기대응적고장특정빈솔。기차,위료철현정자전류고장특정빈솔,기우도수분석사로,인입협륜불평형하정자전류고장특정정의급기표체식,제출기우정자단상전류적협륜불평형고장진단방법。최후,건립고필협륜불평형고장적쌍궤풍전궤조방진모형,대궤조재불동풍속화불평형도하적고장특정진행방진분석。결과표명여직접대정자전류、협륜전속진행빈보분석상비,소술방법능구유효지제취출협륜불평형고장특정,차통과감측특정빈솔폭치적변화정황,가이유효지판단출불평형고장엄중정도。
To diagnose the blade imbalance fault for doubly fed wind turbines,a stator single-phase fault current derivative analysis method is proposed.First,based on the models of doubly fed induction generator (DFIG) and of wind turbine drive-train,the expression of DFIG stator current is derived under the wind blade imbalance fault to obtain the corresponding fault feature frequencies.Then,to highlight the fault feature frequency of the stator current,based on the derivative analysis idea, by introducing a new stator current fault feature definition and expression,the wind blade imbalance fault diagnosis method is proposed.Finally,simulation models of doubly fed wind turbines are presented considering the blade imbalance fault,and comparisons are performed under different wind speed conditions and blade imbalance degrees by using three different fault diagnosis methods.The results show that the proposed method can effectively extract blade imbalance fault feature and determine the fault severity by monitoring the trend of feature frequency amplitude,by comparing with the direct spectrum analysis methods of DFIG stator current and wind turbine speed. This work is supported by International Science & Technology Cooperation Program of China (No.2013DFG61520), National Natural Science Foundation of China (No.51377184),Integration and Demonstration Program of Chongqing (No.CSTC2013JCSF70003), Fundamental Research Funds for the Central Universities (No.CDJZR12150074), and Chongqing Graduate Student Research Innovation Project(No.CYB14014).