scholarly journals A Hybrid Approach to Classify Power Quality Problems in Distribution Systems

2021 ◽  
Author(s):  
Okan Ozgonenel ◽  
◽  
Kubra Nur Akpinar ◽  
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Electromagnetic Interference ◽  
Distribution Systems ◽  
Electrical Power ◽  
Hybrid Approach ◽  
Principal Component ◽  
Discrete Wavelet ◽  
Time Data ◽  
Power Quality Disturbances

Electrical power systems are expected to transmit continuously nominal rated sinusoidal voltage and current to consumers. However, the widespread use of power electronics has brought power quality problems. This study performs classification of power quality disturbances using an artificial neural network (ANN). The most appropriate ANN structure was determined using the Box-Behnken experimental design method. Nine types of disturbance (no fault, voltage sag, voltage, swell, flicker, harmonics, transient, DC component, electromagnetic interference, instant interruption) were investigated in computer simulations. The feature vectors used in the identification of the different types of disturbances were produced using the discrete wavelet transform and principal component analysis. Our results show that the optimized feed forward multilayer ANN structure successfully distinguishes power quality disturbances in simulation data and was also able to identify these disturbances in real time data from substations.

scholarly journals Improvement of Power Quality using DVR by Different Control Techniques

2019 ◽  
Vol 8 (3) ◽  
pp. 7366-7369
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Power Distribution ◽  
Distribution Systems ◽  
Fuzzy Logic Controller ◽  
Electrical Power ◽  
Harmonic Distortion ◽  
Dynamic Voltage Restorer ◽  
Efficient Operation ◽  
Dynamic Voltage

Power quality has been an issue in electrical power systems. Disturbances occur in power quality which effects machines, some electric devices and severe cause will get very serious damages. For normal and efficient operation it’s necessary to compensate and acknowledge every type of the disturbances at earlier time of the power system. Many sorts of Custom Power Devices (CPD’s) are used to resolve these issues .Here at present, one in every of those devices, Dynamic Voltage restorer (DVR) is conferred. In power distribution systems this is often best and effective device employed. During this project new structure and control methodology of multifunctional DVRs for voltage quality correction are mentioned. Proportional Integral Controller and Fuzzy Logic Controller are used for the PQ improvement. The performance of the device and Total Harmonic Distortion is compared with each other. The performance of the device like voltage swell, sag is projected.

Power quality disturbance analysis using data-driven EMD-SVM hybrid approach

2021 ◽  
pp. 1-10
Author(s):  
Hasmat Malik ◽  
Abdulaziz Almutairi ◽  
Majed A. Alotaibi
Keyword(s):  
Power Quality ◽  
Electrical Power ◽  
Model Development ◽  
Hybrid Approach ◽  
Training Phase ◽  
Data Generation ◽  
Time Data ◽  
Electrical Power System ◽  
Decomposition Approach ◽  
Testing Phase

In the modern electrical power system network (EPSN), the power quality disturbances (PSDs) are the serious issue for the power engineer to maintain the uninterrupted and reliable power supply. Generally, PQDs are generated due to non-linear loading condition, perturb loading and other occurrences such as transient, harmonics, sag, swell and interruptions. These problems of PQDs effect the power demand mapping problem, which effect the reliability and stability of the EPSN operating condition. In this study, a novel approach for PQDs diagnosis (PQDD) is proposed, which includes real-time data generation, data pre-processing, feature extraction, feature selection, intelligent model development for PQDD. Data decomposition approach of EMD is utilized to generate the feature vector of IMFs. These features are utilized as an input variable to the intelligent classifiers. In this study PQDD is analyzed based on SVM method and obtained results are compared with conventional AI method of LVQ-NN. The results represent the higher acceptability of the proposed approach with diagnosis accuracy of 99.98% (training phase), 93.11% (testing phase) for SVM and 92.56% (training phase) and 91.0% (testing phase) for LVQ-NN based PQDD method.

scholarly journals A Novel Deep Learning-Based Diagnosis Method Applied to Power Quality Disturbances

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2839
Author(s):  
Artvin-Darien Gonzalez-Abreu ◽  
Miguel Delgado-Prieto ◽  
Roque-Alfredo Osornio-Rios ◽  
Juan-Jose Saucedo-Dorantes ◽  
Rene-de-Jesus Romero-Troncoso
Keyword(s):  
Deep Learning ◽  
Power Quality ◽  
Electrical Power ◽  
Synthetic Data ◽  
Industrial Sector ◽  
Industrial Facilities ◽  
Diagnosis Method ◽  
Neural Network Structure ◽  
Power Quality Disturbances ◽  
Disturbance Detection

Monitoring electrical power quality has become a priority in the industrial sector background: avoiding unwanted effects that affect the whole performance at industrial facilities is an aim. The lack of commercial equipment capable of detecting them is a proven fact. Studies and research related to these types of grid behaviors are still a subject for which contributions are required. Although research has been conducted for disturbance detection, most methodologies consider only a few standardized disturbance combinations. This paper proposes an innovative deep learning-based diagnosis method to be applied on power quality disturbances, and it is based on three stages. Firstly, a domain fusion approach is considered in a feature extraction stage to characterize the electrical power grid. Secondly, an adaptive pattern characterization is carried out by considering a stacked autoencoder. Finally, a neural network structure is applied to identify disturbances. The proposed approach relies on the training and validation of the diagnosis system with synthetic data: single, double and triple disturbances combinations and different noise levels, also validated with available experimental measurements provided by IEEE 1159.2 Working Group. The proposed method achieves nearly a 100% hit rate allowing a far more practical application due to its capability of pattern characterization.

Principal Component Analysis and CNN for Classification of Power Quality Disturbances

2021 ◽  
Author(s):  
Ananta Agarwalla ◽  
Diya Dileep ◽  
P. Jyothsana ◽  
Purnima Unnikrishnan ◽  
Karthik Thirumala
Keyword(s):  
Principal Component Analysis ◽  
Power Quality ◽  
Principal Component ◽  
Component Analysis ◽  
Power Quality Disturbances

Power Quality Issues and Solutions – Review

2015 ◽  
Vol 16 (4) ◽  
pp. 357-384 ◽  
Author(s):  
Suresh Mikkili ◽  
Anup Kumar Panda
Keyword(s):  
Power Quality ◽  
Power Distribution ◽  
Distribution Systems ◽  
Reactive Power ◽  
Electrical Power ◽  
Economic Loss ◽  
Nonlinear Loads ◽  
Broad Perspective ◽  
Three Phase ◽  
Quality Issues

Abstract Electrical power quality has been an important and growing problem because of the proliferation of nonlinear loads such as power electronic converters in typical power distribution systems in recent years. Particularly, voltage harmonics and power distribution equipment problems result from current harmonics produced by nonlinear loads. The Electronic equipment like, computers, battery chargers, electronic ballasts, variable frequency drives, and switch mode power supplies, generate perilous harmonics and cause enormous economic loss every year. Problems caused by power quality have great adverse economic impact on the utilities and customers. Due to that both power suppliers and power consumers are concerned about the power quality problems and compensation techniques. Power quality has become more and more serious with each passing day. As a result active power filter gains much more attention due to excellent harmonic and reactive power compensation in two-wire (single phase), three-wire (three-phase without neutral), and four-wire (three-phase with neutral) ac power networks with nonlinear loads. However, this is still a technology under development, and many new contributions and new control topologies have been reported in the last few years. It is aimed at providing a broad perspective on the status of APF technology to the researchers and application engineers dealing with power quality issues.

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