Power quality diagnosis in distribution networks using rule based S-transform method

Author(s):  
M. Faisal ◽  
A. Mohamed ◽  
H. Shareef
2011 ◽  
Vol 38 (10) ◽  
pp. 12592-12598 ◽  
Author(s):  
M. Faisal ◽  
A. Mohamed ◽  
H. Shareef ◽  
A. Hussain

2015 ◽  
Vol 51 (2) ◽  
pp. 1249-1258 ◽  
Author(s):  
Raj Kumar ◽  
Bhim Singh ◽  
D. T. Shahani ◽  
Ambrish Chandra ◽  
Kamal Al-Haddad

2015 ◽  
Vol 733 ◽  
pp. 662-665
Author(s):  
Lin Lin ◽  
Xiao Huan Wu ◽  
Jia Jin Qi ◽  
Hong Xin Ci ◽  
Zhi Yong Yu

The noise component in power quality signals affects the accuracy of analysis result. This paper presents a new approach for power quality signals de-noising. Firstly, the original signals are transformed by S-transform method. Then, the matrix which is get from S-transform result is processed as a two-dimension image. The global thresholding de-noising method is used to filtering the noise component in the power quality signals. The simulation results showed the effectiveness of the new approach.


2021 ◽  
Vol 17 ◽  
pp. 22-27
Author(s):  
Fouad R. Zaro

In this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (S-transform) and rule-based decision tree (DT) according to IEEE standards. The proposed technique based on the extracted features of the PQ events signals, which are extracted from the timefrequency analysis. Several PQ disturbances are considered with simple and complex disturbances to include spike, flicker, oscillatory transient, impulsive transient, and notch. The performance and robustness of the proposed technique for the recognition of PQ disturbances have been demonstrated through the results of the various disturbances. By comparing the performance of the proposed technique with other reported studies it was distinguished results under noiseless and noisy conditions


Author(s):  
Azah Mohamed ◽  
Mohamed E. Salem ◽  
Salina Abdul Samad

Detection and classification of power quality (PQ) disturbances in real-time is an important consideration to electric utilities and many industrial customers so that diagnosis and mitigation of such disturbances can be implemented quickly. This paper presents the design and development of an integrated hardware system for classification of PQ disturbances using the rule based system. A hardware system has been designed using advanced digital signal processor to provide fast data capture and processing of signals using the S-transform analysis. Distinct features of various disturbances are extracted from the S-transform analysis in which these features are used to formulate rules. A rule based expert system is developed to automate the process of classifying the various types of disturbances. The disturbance classification results prove that the developed rule based system is more accurate than the neural network approaches in classifying PQ disturbances such as voltage sag, swell, impulsive transient, notching and interruption.


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