scholarly journals Method for Estimating Harmonic Parameters Based on Measurement Data without Phase Angle

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 879 ◽  
Author(s):  
Fulin Zhou ◽  
Feifan Liu ◽  
Ruixuan Yang ◽  
Huanrui Liu
Keyword(s):  
Power Quality ◽  
Phase Difference ◽  
Measurement Data ◽  
Power Grids ◽  
Least Squares Regression ◽  
Phase Information ◽  
Point Of Common Coupling ◽  
Practical Engineering ◽  
General Power ◽  
Harmonic Voltage

The excessive use of power electronics makes power quality problems in power grids increasingly prominent. The estimation of the harmonic parameters of harmonic sources in the power grid and the division of harmonic responsibilities are of great significance for the evaluation of power quality. At present, methods for estimating harmonic parameters and harmonic responsibilities need to provide the amplitude and phase information of the current and voltage of the point of common coupling (PCC). However, in practical engineering applications, the general power quality monitor only provides the amplitude information of the voltage and current of the measured point and the phase difference information between them. Missing phase information invalidates existing methods. Based on the partial least squares regression method, the present work proposes a method for estimating harmonic parameters in the case of monitoring data without phase. This method only needs to measure the amplitude information of the harmonic voltage and current of the PCC and the phase difference between them, then use the measurable data to estimate the harmonic parameters and the harmonic responsibility of each harmonic source. It provides a new way to effectively solve the problem that the measured data of the project has no phase information. The feasibility and effectiveness of the proposed method are proved by simulation data and measured engineering data.

A Novel Method for Determining Harmonic Emission Responsibilities at the Point of Common Coupling

2013 ◽  
Vol 448-453 ◽  
pp. 2380-2383
Author(s):  
Xiao Jun Zhu ◽  
Xiang Li ◽  
Bin Fu ◽  
Ang Fu ◽  
Min You Chen ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares Regression ◽  
Least Squares Regression ◽  
Harmonic Emission ◽  
Point Of Common Coupling ◽  
Practical Engineering ◽  
Data Points ◽  
Harmonic Voltage ◽  
Novel Method ◽  
Common Coupling

This paper presents a novel method for determining the harmonic emission responsibilities of utility and customer at the point of common coupling (PCC). The proposed approach is based on robust partial least squares regression (robust PLS), which estimates system harmonic impedance by utilizing the signals of harmonic voltage and current measured synchronously at PCC. Consequently the harmonic emission responsibilities are calculated. The presented method reduces or removes the effect of outlying data points. The simulation and the practical engineering results indicate that the proposed method is valid and feasible.

Classification and Identification of Power System Disturbances Using Wavalet and Artificial Neural Network Technique

2005 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
Noraliza Hamzah ◽  
Wan Nor Ainin Wan Abdullah ◽  
Pauziah Mohd Arsad
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Probabilistic Neural Network ◽  
Microsoft Excel ◽  
Waveform Data ◽  
The Neural Network ◽  
Harmonic Voltage ◽  
Power Quality Disturbances ◽  
Electronic Load ◽  
Wavelet Technique

Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neural network to detect and classify power quality disturbances, which are harmonic, voltage sag, swell and oscillatory transient. The power quality disturbances are obtained from the waveform data collected from premises, which include the UiTM Sarawak, Faculty of Science Computer in Shah Alam, Jati College, Menara UiTM, PP Seksyen 18 and Putra LRT. Reliable Power Meter is used for data monitoring and the data is further processed using the Microsoft Excel software. From the processed data, power quality disturbances are detected using the wavelet technique. After the disturbances being detected, it is then classified using the Probabilistic Neural Network. Sixty data has been chosen for the training of the Probabilistic Neural Network and ten data has been used for the testing of the neural network. The results are further interfaced using matlab script code.  Results from the research have been very promising which proved that the wavelet technique and Probabilistic Neural Network is capable to be used for power quality disturbances detection and classification.

Assessment of power quality parameters and indicators at the point of common coupling in a low voltage power grid with photovoltaic generation emulated

2022 ◽  
Vol 203 ◽  
pp. 107679
Author(s):  
Oscar Pinzón-Quintero ◽  
Daniel Gaviria-Ospina ◽  
Alejandro Parrado-Duque ◽  
Rusber Rodríguez-Velásquez ◽  
German Osma-Pinto
Keyword(s):  
Power Quality ◽  
Low Voltage ◽  
Power Grid ◽  
Quality Parameters ◽  
Photovoltaic Generation ◽  
Point Of Common Coupling ◽  
Common Coupling

Power Quality Assessment and Enhancement in a Grid Connected Renewable Energy System Using Dynamic Voltage Restorer

2014 ◽  
Vol 573 ◽  
pp. 716-721
Author(s):  
S. Rajeshbabu ◽  
B.V. Manikandan
Keyword(s):  
Neural Network ◽  
Renewable Energy ◽  
Power Quality ◽  
Energy System ◽  
Dynamic Voltage Restorer ◽  
Renewable Energy System ◽  
Voltage Restorer ◽  
Point Of Common Coupling ◽  
Dynamic Voltage ◽  
Common Coupling

Renewable energy sources provide the additional/satisfy the power to the consumer through power electronics interfaces and integrated with the grid. In grid integration power quality is one of the important parameter that need to be paying more attention. This proposed work focuses on power quality issues in a grid connected renewable energy system. Power quality issues will arises due to many factors here with the by introducing a fault condition in a grid connected renewable energy system the measurements were made at the point of common coupling and the mitigation is done with the help of a dynamic voltage restorer. The dynamic voltage restorer is a device which offers series compensation activated by neural network based controller. The sag improvement and the total harmonic assessment were made at the point of common coupling. Keywords: Neural network, Point of common coupling, Renewable energy source, Power quality, Dynamic voltage restorer ,electric grid.

scholarly journals A DSE-Based SMC Method of Sensorless DFIG Wind Turbines Connected to Power Grids for Energy Extraction and Power Quality Enhancement

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 76596-76605 ◽  
Author(s):  
Samson Shenglong Yu ◽  
Guidong Zhang ◽  
Tyrone Fernando ◽  
Herbert Ho-Ching Iu
Keyword(s):  
Power Quality ◽  
Wind Turbines ◽  
Power Grids ◽  
Quality Enhancement ◽  
Energy Extraction

Design and Implementation of Wireless Ad Hoc Smart Metering System for Power Quality

2013 ◽  
Vol 431 ◽  
pp. 247-252
Author(s):  
Yi Zhong ◽  
Yuan Ming Li ◽  
Yun Cao ◽  
Wen Hua Wu ◽  
Cheng Chen ◽  
...  
Keyword(s):  
Real Time ◽  
Power Quality ◽  
Ad Hoc ◽  
Power Grids ◽  
Quality Information ◽  
Smart Metering ◽  
Time Interaction ◽  
Energy Metering ◽  
Hoc Networks ◽  
Energy Information

In order to facilitate the advanced measurement system with real-time interaction in smart grid and to satisfy the requirements for power quality management, a wireless ad hoc smart metering system for power quality using Internet of things (IoTs) technology is presented in the paper. By utilizing the energy metering module to collect energy information, the ZigBee ad hoc networks to transmit energy information, and the user monitoring terminal to support power grids management, the proposed system is able to efficiently realize the power quality information collection, transmission, processing and sharing. Experimental results demonstrate that the system performs real-time and precious monitoring of the distributed client power quality information, together with friendly and intelligent interaction capability.

A Possibility Estimation Model and its Application

2013 ◽  
Vol 475-476 ◽  
pp. 423-427
Author(s):  
Lin Na Ji ◽  
Feng Bao Yang ◽  
Xiao Xia Wang
Keyword(s):  
Measurement Data ◽  
Engineering Application ◽  
Transformation Method ◽  
Estimation Model ◽  
Property Estimation ◽  
New Methods ◽  
Proposed Model ◽  
Practical Engineering ◽  
New Ideas ◽  
Possibility Distributions

Aiming at some uncertainty problems such as quality inspection of adhesive structure and risk assessment in the practical engineering application, a possibility estimation model is established. Firstly, according to the fuzziness, randomness and uncertainty of the measurement data, a transformation method of possibility distribution with non-single peak values and nonlinearity is proposed from probability density function. Secondly, for possibility distributions of measurement data of each sensor, a kind of possibility fusion rules is put forward, then the fusion distribution is estimated by the possibility mean. Finally the model is applied to the mechanical property estimation of adhesive structure, and the result forecasts the quality. The proposed model with strong applicability, not only provides convenience for the operations among possibility distributions, but also offers new ideas and new methods to deal with uncertain problems.

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