Real-time voltage sag detection and classification for power quality diagnostics

Measurement ◽  
2020 ◽  
Vol 164 ◽  
pp. 108097
Author(s):  
Erick A. Nagata ◽  
Danton D. Ferreira ◽  
Math H.J. Bollen ◽  
Bruno H.G. Barbosa ◽  
Eduardo G. Ribeiro ◽  
...  
Keyword(s):  
Real Time ◽  
Power Quality ◽  
Voltage Sag ◽  
Voltage Sag Detection ◽  
Quality Diagnostics

Voltage Sag Detection Method Based on Wavelet Information

2015 ◽  
Vol 740 ◽  
pp. 470-473
Author(s):  
Da Hai Zhang ◽  
Cheng Yu Ge ◽  
Chen Chen ◽  
Xian He Han
Keyword(s):  
Wavelet Analysis ◽  
Power Quality ◽  
Detection Method ◽  
Voltage Sag ◽  
Major Power ◽  
Wavelet Method ◽  
Quality Problem ◽  
Local Maxima ◽  
Multi Scale ◽  
Voltage Sag Detection

Voltage sag is the major power quality problem and receives wide attention. Although wavelet analysis works well for detecting voltage sag features, the existence of noise can reduce the advantages of wavelet method or even make it ineffective. To solve the problem, the paper uses multi-scale wavelet information by multiplying the results of several scales, and then searches the local maxima from the product to find the transition moment of voltage sag. The proposed method can suppress the noise and improve the accuracy for detecting voltage sag features. Simulation result validates the effectiveness of the proposed method.

scholarly journals An Implementation of Exploratory Start for Power Quality Disturbance Pattern Recognition

2016 ◽  
Vol 1 (3) ◽  
pp. 86
Author(s):  
Turgay Yalcin ◽  
Muammer Ozdemir
Keyword(s):  
Pattern Recognition ◽  
Decision Tree ◽  
Power System ◽  
Real Time ◽  
Power Quality ◽  
Smart Grids ◽  
Voltage Sag ◽  
Calculation Error ◽  
System Monitoring ◽  
Power System Monitoring

Identification of system disturbances and detection of them guarantees smart grids power quality system reliability and long lasting life of the power system. The key goal of this study is to generate non - time consuming features for CPU, for recognizing different types of non-stationary and non-linear smart grid faults based on signal processing techniques. This paper proposes a new solution for real time power system monitoring against power quality faults focusing on voltage sag and noise. EEMD is used for noise reduction with first intrinsic mode function (imf1). Hilbert Huang Transform (HHT) is used for generating instantaneous amplitude (IA) and instantaneous frequency (IF) feature of real time voltage sag power signal. The proposed power system monitoring system is able to detect power system voltage sag disturbances and capable of recognize and remove EMI (Electromagnetic Interference)-Noise.  In this study based on experimental studies, Hilbert Huang based pattern recognition technique was used to investigate power signal to diagnose voltage sag in power grid. SVM and Decision Tree (C4.5) were operated and their achievements were matched for calculation error and CPU time. According to the analysis, decision tree algorithm without dimensionality reduction produces the best solution.

Based on Lifting Wavelet Voltage Sag Detection Algorithm and Achieve

2013 ◽  
Vol 378 ◽  
pp. 335-339
Author(s):  
Xin Liang Yin ◽  
Gui Tang Wang ◽  
Zhi Wen Feng ◽  
Xiong Hui Lai
Keyword(s):  
Wavelet Transform ◽  
Power Quality ◽  
Hardware Implementation ◽  
Detection Algorithm ◽  
Voltage Sag ◽  
Lifting Wavelet Transform ◽  
Voltage Sag Detection ◽  
Lifting Wavelet ◽  
The Fourier Transform ◽  
Transient Power Quality

Voltage sag belongs to a kind of transient power quality problems, it possesses short mutations, non-stationary characteristics and the detection on the interference is difficult. Wavelet transform is a better signal analysis method and it is very suitable for analysis of mutations in the signal. Compared with traditional wavelet transform algorithm, Wavelet transform algorithm does not depend on the ascension of the Fourier transform and it reduces the computation complexity, so it is very suitable for hardware implementation. This paper introduces a design based on 9/7 of lifting wavelet transform of the voltage sag detection algorithm, and realized in the FPGA and modeling the transient power quality signal in the Matlab. To make hardware implementation easier, a series of optimization to the coefficient of ascension of 9/7 of lifting wavelet transform was carried out. The results show that 9/7 of the lifting wavelet transform algorithm can effectively test the end time of the voltage sag happens.

Improved Voltage Sag Detection Method and Optimal Design for the Digital Low-Pass Filter in Small UAVs

2015 ◽  
Author(s):  
Shuiqiang Pei ◽  
Xiaoguang Hu ◽  
Guofeng Zhang ◽  
Li Fu
Keyword(s):  
Real Time ◽  
Detection Method ◽  
Voltage Sag ◽  
Dynamic Voltage Restorer ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Voltage Restorer ◽  
Voltage Sag Detection ◽  
Low Pass ◽  
Dynamic Voltage

Real-time and accurate detection of the voltage sag characteristics is the premise to achieve dynamic voltage restorer compensation. An improved αβ-dq transformation detection method is presented for the limitations of traditional detection methods. In this method, the α-axis component of the αβ static coordinate system is deduced according to the single-phase voltage. The virtual β-axis component is constructed from the derivative of the α-axis component. The magnitudes, duration, phase-angle jump of the voltage sag are detected quickly and accurately by αβ-dq transformation and low-pass filter. The original data is real-time, which ensures faster detection response speed and reduces the computation greatly. In addition, an optimization design method for digital low-pass filter is presented against the contradictions existing in real-time and filtering effect of common low-pass filter. This adopts inertial filter to improve the characteristics of Butterworth low-pass filter and enable them to better adapt to the needs of the voltage sag detection thus improving the real-time quality and precision of dynamic voltage restorer.

scholarly journals Research of Microgrid Stability with Voltage Sag Detection using Instantaneous Features Extraction

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1239-1241
Keyword(s):  
Power Quality ◽  
Negative Impact ◽  
Features Extraction ◽  
System Stability ◽  
Voltage Sag ◽  
Power Sources ◽  
Energy And Environment ◽  
Fault Ride Through ◽  
Voltage Sag Detection ◽  
Sustainable Power

With the inexorably serious energy shortage and environment contamination, the wide utilization of the well known sustainable power sources are considered as successful approaches to improve the energy and environment circumstance. The negative impact on the system stability couldn't be overlooked for their irregular, fluctuant and arbitrary attributes. Intending to think about the strength of microgrid with access of Instantaneous Features Extraction is one of the most productive methods for successful utilization of these grids. In this way a proactive tracking, counteract fault ride-through the sustainable sources, bring about limiting downtime and improving the profitability. In this unique situation, this paper proposes Instantaneous Features Extraction calculation for the identification of voltage droops as they are the most frequently experienced power quality aggravations. Hence takes into consideration early discovery of power quality degeneration improves the profitability.

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