Power Quality Engineering Research Center

Hefei, China

Power Quality Engineering Research Center

Hefei, China
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Cheng Z.,Power Quality Engineering Research Center | Cheng Z.,Anhui University | Wang X.,Anhui University | Wang X.,Anhui Sun Create Electronic Co. | Xu J.,Anhui University
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2016

Voltage sag is currently one of the most important power quality problems in power system, which has become increasingly a focus of attention in society. Due to the defects of traditional algorithm that has complex operation and poor precision, this paper proposes a voltage sag detection method based on complex impedance. Firstly, Hilbert transform is used to construct the analytic signals for detected voltage and current signals separately, and then their corresponding complex impedance will be calculated, making use of the specialty that when the voltage sag happened, its impedance and phase angle will jump at the same time, and combining overrun discriminator, the proposed method can locate the occurrence time of voltage sag, and detect its time duration. Finally, the effectiveness of the proposed method in this paper is verified by several experiments, the experimental results show that this method has high accuracy and easy to distinguish, it has wide promotional value. © 2016, Power System Protection and Control Press. All right reserved.


Cheng Z.-Y.,Power Quality Engineering Research Center | Cheng Z.-Y.,Anhui University | Zuo J.-K.,Anhui University | Liang D.,Power Quality Engineering Research Center | And 3 more authors.
Huadong Ligong Daxue Xuebao/Journal of East China University of Science and Technology | Year: 2012

In power system, harmonic detection is the basis of the analysis and control of power quality, e.g., reactive power compensation and harmonic filtration. In order to overcome the shortcoming of the traditional methods, this paper proposes a harmonic detection method by combining Gerschgorin disk criterion and Toeplitz approximation method (TAM). This method is based on the models of signal spaces. Gerschgorin disk criterion is employed to detect the source number. Besides, both the orthogonality of signal sub-space and noise sub-space and the rotational invariance of subspaces are combined to estimate the signal frequency. And then, the signal amplitude is obtained by utilizing total least squares (TLS) algorithm. Finally, it is shown from simulation experiments and real data analysis that the proposed algorithm can attain higher speediness and better precision.


Cheng Z.-Y.,Power Quality Engineering Research Center | Cheng Z.-Y.,Anhui University | Cheng C.,Power Quality Engineering Research Center | Liu Y.,Power Quality Engineering Research Center | Zuo J.-K.,Power Quality Engineering Research Center
Huadong Ligong Daxue Xuebao/Journal of East China University of Science and Technology | Year: 2011

Aiming at the shortcoming of traditional harmonic detection method, this paper applied TAM method to the harmonic detection. Basing on the signal space model, the harmonics in power system was detected by combining the subspace rotational invariance and least squares method. Firstly, the covariance matrix of the sampled signal data matrix was solved. And then, the covariance matrix was decomposed through singular value. Meanwhile, the noise effect was lessened by means of the least squares method such that the accurate frequency and amplitude parameters were derived. The simulation results show that the proposed algorithm is accurate and effective. Moreover, the real-time data analysis shows that the present algorithm has better application prospects.


Cheng Z.-Y.,Power Quality Engineering Research Center | Cheng Z.-Y.,Anhui University | Zuo J.-K.,Anhui University | Liang D.,Power Quality Engineering Research Center | And 3 more authors.
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | Year: 2014

Applied beamspace root-MUSIC, with signal spaces as the models, to do harmonic detection to overcome the drawbacks of the traditional methods. Firstly, Gerschgorin disk criterion was employed to detect the source number, then the data acceptable to the array was transformed to get the data of the beamspace, which was further decomposed to noise subspace and signal subspace. Next, a polynomial was constructed with the use of the orthogonality of these two subspaces. By solving this polynomial, the estimate frequency value of the signal was attained. Lastly, with the extension of the PRONY method, the amplitude of the signal was achieved. Simulation experiments and real data analysis show that this algorithm in power system harmonic detection is feasible.


Cheng Z.-Y.,Power Quality Engineering Research Center | Cheng Z.-Y.,Anhui University | Wang J.-Q.,Anhui University | Zuo J.-K.,Anhui University
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2013

Since the ESPRIT algorithm can not analyze non-stationary power quality disturbances, we present a time-frequency analysis method based on adaptive sliding window-ESPRIT algorithm. According to the characteristics of non-stationary power quality signal, the signal is firstly divided into small blocks by the adaptive sliding window. In order to get the frequencies and amplitudes of each block, an ESPRIT algorithm is then applied. Next, it receives the whole information of time-frequency distribution with the parameters of each block. At last, simulations of several non-stationary signals are conducted; the results have strongly indicated that the proposed method is very suitable for the detection of power quality disturbance with practical application prospect.


Cheng Z.,Power Quality Engineering Research Center | Cheng Z.,Anhui University | Cheng C.,Power Quality Engineering Research Center | Fu X.,Power Quality Engineering Research Center | Wang J.,Anhui University
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | Year: 2013

In this paper, a new algorithm conjugate signal parameters via rotational invariance techniques to estimate the frequency of the harmonics is presented. The C-SPRIT employs all element outputs to form separate sub-arrays which are fully overlapped. It uses the conjugate of rotation matrix instead of rotation matrix in array signal processing. The total least squares (TLS) is also employed here to decrease the influence of noise. The simulation examples demonstrate that the algorithm is capable of having higher precision and stronger anti-noise capacity. Real-time data analysis shows that the algorithm is feasible and available. It has some prospects in future.

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