电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
POWER SYSTM PROTECTION AND CONTROL
2013年
17期
44-48
,共5页
电能质量%谐波检测方案%BP神经网络%快速傅里叶变换%离散傅里叶变换
電能質量%諧波檢測方案%BP神經網絡%快速傅裏葉變換%離散傅裏葉變換
전능질량%해파검측방안%BP신경망락%쾌속부리협변환%리산부리협변환
power quality%harmonic detecting scheme%BP neural network%FFT%DFT
通常的谐波检测方案是对各次谐波(如1~50次)使用快速傅里叶变换(FFT)进行检测,然而用电单位往往并不关心所有次数谐波的具体数值,而仅关心关键次数的谐波或几个总体指标。为此,设计了一套新的谐波检测方案,以 BP 神经网络作为实现算法,不需要计算各次谐波即可实现对用户所关心的个别指标或总体指标的检测,而且要实现上述检测目标,通过对BP算法、DFT算法、FFT算法进行计算量分析,证明了该方案在计算量方面的优越性。使用一组实测谐波数据对方案进行仿真验证,结果表明该方案简单可行,可达到与FFT相近的检测精度。
通常的諧波檢測方案是對各次諧波(如1~50次)使用快速傅裏葉變換(FFT)進行檢測,然而用電單位往往併不關心所有次數諧波的具體數值,而僅關心關鍵次數的諧波或幾箇總體指標。為此,設計瞭一套新的諧波檢測方案,以 BP 神經網絡作為實現算法,不需要計算各次諧波即可實現對用戶所關心的箇彆指標或總體指標的檢測,而且要實現上述檢測目標,通過對BP算法、DFT算法、FFT算法進行計算量分析,證明瞭該方案在計算量方麵的優越性。使用一組實測諧波數據對方案進行倣真驗證,結果錶明該方案簡單可行,可達到與FFT相近的檢測精度。
통상적해파검측방안시대각차해파(여1~50차)사용쾌속부리협변환(FFT)진행검측,연이용전단위왕왕병불관심소유차수해파적구체수치,이부관심관건차수적해파혹궤개총체지표。위차,설계료일투신적해파검측방안,이 BP 신경망락작위실현산법,불수요계산각차해파즉가실현대용호소관심적개별지표혹총체지표적검측,이차요실현상술검측목표,통과대BP산법、DFT산법、FFT산법진행계산량분석,증명료해방안재계산량방면적우월성。사용일조실측해파수거대방안진행방진험증,결과표명해방안간단가행,가체도여FFT상근적검측정도。
General harmonic detecting scheme uses the Fast Fourier Transform (FFT) to detect all the harmonics (such as from 1st harmonic to 50th harmonic). Power consumers often do not care about the specific values of all the harmonics, but only some key harmonics or several overall indicators. For the above reasons, a new harmonic detecting scheme based on the algorithm of BP neural network is presented. It does not need to calculate all the harmonics and can detect individual indicators or overall indicators which are concerned by users. To achieve the above-mentioned detection target, the computation analysis of BP, DFT and FFT algorithm is made, and the superiority of the scheme in terms of computation is proved. After the simulation of the scheme is done using a set of measured harmonic data, the results validate that the above scheme is simple and feasible, and its detecting accuracy is close to that of FFT. <br> This work is supported by National Natural Science Foundation of China (No. 50707010).