电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
POWER SYSTM PROTECTION AND CONTROL
2014年
14期
38-44
,共7页
江辉%邹崇杰%谢兴%彭建春
江輝%鄒崇傑%謝興%彭建春
강휘%추숭걸%사흥%팽건춘
电能质量%暂态电压扰动%集合Kalman滤波%背景集合%扰动起止时刻
電能質量%暫態電壓擾動%集閤Kalman濾波%揹景集閤%擾動起止時刻
전능질량%잠태전압우동%집합Kalman려파%배경집합%우동기지시각
power quality%transient voltage disturbance%Ensemble-Kalman filtering%background ensemble%beginning and ending times of disturbance
随着电力系统中非线性负荷的增加,由暂态电压扰动引起的电能质量问题越来越严重,对暂态电压扰动信号的检测成为改善电能质量的关键。基于集合Kalman滤波方法进行暂态电压扰动检测分析,结合暂态电压扰动特点,构造了集合Kalman滤波的背景集合。由k-1,k-2时刻的电压状态修正值组成背景集合,然后进行递归运算,提取出实时的电压幅值,从而定位暂态扰动发生的起止时刻以及跟踪突变的幅值。仿真结果表明,所提方法能快速检测到电压暂降/突升、暂态电压脉冲信号发生的起止时刻,跟踪到突变幅值。其对谐波加电压暂降混合扰动信号的扰动起止时刻以及混合扰动信号中基波、谐波的幅值的跟踪也非常有效。所提方法总体优于传统的Kalman滤波法和有效值法。
隨著電力繫統中非線性負荷的增加,由暫態電壓擾動引起的電能質量問題越來越嚴重,對暫態電壓擾動信號的檢測成為改善電能質量的關鍵。基于集閤Kalman濾波方法進行暫態電壓擾動檢測分析,結閤暫態電壓擾動特點,構造瞭集閤Kalman濾波的揹景集閤。由k-1,k-2時刻的電壓狀態脩正值組成揹景集閤,然後進行遞歸運算,提取齣實時的電壓幅值,從而定位暫態擾動髮生的起止時刻以及跟蹤突變的幅值。倣真結果錶明,所提方法能快速檢測到電壓暫降/突升、暫態電壓脈遲信號髮生的起止時刻,跟蹤到突變幅值。其對諧波加電壓暫降混閤擾動信號的擾動起止時刻以及混閤擾動信號中基波、諧波的幅值的跟蹤也非常有效。所提方法總體優于傳統的Kalman濾波法和有效值法。
수착전력계통중비선성부하적증가,유잠태전압우동인기적전능질량문제월래월엄중,대잠태전압우동신호적검측성위개선전능질량적관건。기우집합Kalman려파방법진행잠태전압우동검측분석,결합잠태전압우동특점,구조료집합Kalman려파적배경집합。유k-1,k-2시각적전압상태수정치조성배경집합,연후진행체귀운산,제취출실시적전압폭치,종이정위잠태우동발생적기지시각이급근종돌변적폭치。방진결과표명,소제방법능쾌속검측도전압잠강/돌승、잠태전압맥충신호발생적기지시각,근종도돌변폭치。기대해파가전압잠강혼합우동신호적우동기지시각이급혼합우동신호중기파、해파적폭치적근종야비상유효。소제방법총체우우전통적Kalman려파법화유효치법。
With the increase of nonlinear loads in power system, power quality problems caused by transient voltage disturbance is more and more serious, the detection of transient voltage disturbance signal becomes the key to improve power quality. This paper proposes a transient voltage disturbance detection method based on Ensemble-Kalman filtering, the elements of Ensemble-Kalman filtering’s background ensemble are reformed according to the characteristics of transient voltage disturbance. The modified values of voltage state atk - 1 andk - 2 form the background ensemble, then the real-time voltage’s amplitude is obtained by recursive computation, thus the beginning and ending times of transient disturbances are positioned and abrupt amplitude is traced out. Simulation results show that the proposed method can quickly detect voltage’s sag/swell, precisely position the beginning and ending times of transient voltage disturbance, and track down the abrupt amplitude. The proposed method is more effective than the traditional Kalman filter (KF) and root-mean-square (RMS) algorithm. This work is supported by National Natural Science Foundation of China (No. 51177102).