Detection of power quality disturbances in presence of DFIG wind farm using wavelet transform based energy function

2011 ◽  
Author(s):  
Rahul Dubey ◽  
S. R. Samantaray ◽  
B. Chitti Babu ◽  
S. Nandha Kumar
Keyword(s):  
Wavelet Transform ◽  
Power Quality ◽  
Energy Function ◽  
Wind Farm ◽  
Power Quality Disturbances

New Research on Identification and Classification of Grid Power Quality Disturbances

2014 ◽  
Vol 986-987 ◽  
pp. 1431-1434
Author(s):  
Ning Xia Yang ◽  
Mao Fa Gong ◽  
Xiao Fei Wang ◽  
Hui Ting Ge ◽  
Yu Qing Lin ◽  
...  
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Wavelet Transform ◽  
Power Quality ◽  
Particle Swarm ◽  
Interference Signal ◽  
Swarm Optimization ◽  
Frequency Information ◽  
Power Quality Disturbances

To improve accuracy and speed of recognising and classifying grid power quality disturbances, this paper presents a new method which combines complex wavelet transform and particle swarm optimization (PSO) neural network to identify and classify the disturbance . This method extract both amplitude-frequency and phase frequency information of the interference signal to make up for the lack of traditional wavelet transform which only extract the amplitude-frequency information. And on this basis, using particle swarm optimization, we seek the optimal solution of neural network weights and thresholds for the identification and classification of power quality. The MATLAB simulation result has verified the accuracy and rapidity of this method compared with the traditional method .

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