A Novel Power Quality Disturbances Detection and Classification Method

2015 ◽  
Vol 737 ◽  
pp. 193-198
Author(s):  
Fei Jin Peng ◽  
Xiao Yun Huang ◽  
Hong Yuan Huang ◽  
Zhi Wen Xie

Power quality disturbance detection and identification is the prerequisite and basis for the power quality management and control. This paper presents a new power quality disturbance detection and classification method. Firstly, the time-time transform is applied to power quality disturbance signal analysis. According to spectrum analysis results of the diagonal elements of time-time transform matrix, a preliminary judge about whether the disturbance signal contains harmonics and inter harmonic was given. For disturbances with non-harmonics, based on time-time transform modulus matrix diagonal sequence, the beginning and ending time of the disturbance is located, and the disturbance amplitude is calculated. For the disturbances which contain harmonics, time-time transform is perform twice to get the row mean value curve and the column mean value curve, which are required by disturbance time location and amplitude measurement. Finally, disturbance classification had realized by using rule tree. Simulation results reveal that this method is very robust and adaptable, which can identify transient power quality disturbance with minor magnitude under noisy environment, and the recognition rate is satisfactory.

2021 ◽  
Vol 5 (3) ◽  
pp. 1-10
Author(s):  
Robson Rosserrani De Lima ◽  
Danton Diego Ferreira ◽  
José Manoel de Seixas ◽  
Leonardo Silveira Paiva

Voltage disturbances are the most frequent cause of a large range of disruption in industrial, commercial, and residential power supply systems. These disturbances are often referred to as power quality problems and affect the Power Systems causing substantial losses. To avoid the storage of a large amount of data, the first task in monitoring the power quality is the realtime detection of disturbances, which must be performed by an accurate and low-complexity system. This paper proposes a low-complexity system for power quality disturbance detection. The method makes innovative use of simple features extracted from reduced segments of the monitored voltage waveform. The extract features (the mean value, variance, energy, and the maximum and minimum values of the filtered voltage signals) require low computational effort and allow a considerable dimensional reduction of the signals, leading to simple detection algorithms. The proposed method achieves high detection rates on both simulated and real signals.


2014 ◽  
Vol 700 ◽  
pp. 99-102
Author(s):  
Meng Da Li ◽  
Yu Bo Duan ◽  
Yan Wang

This paper uses the method of S transformation to test the starting time, the end of the time, frequency and amplitude characteristics of common transient power quality signal disturbance. Through error analysis and simulation show that this method can accurately determine the disturbance occurred time and duration, and the identification and determination of disturbance can be simple and intuitive. It has the practical value and realistic significance to power quality signal interference analysis.


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