Paper Info
Title
Framework of Gradient Descent Least Squares Regression-Based NN Structure for Power Quality Improvement in PV-Integrated Low-Voltage Weak Grid System
Abstract
This paper proposes a novel gradient descent least squares regression (GDLSR)-based neural network (NN) structure for the control of grid-integrated solar photovoltaic (PV) system with improved power quality. Here, a single-layer neuron structure is used for the extraction of fundamental component (FC) from the load current. During FC extraction, GDLSR-based NN structure attenuates harmonic components, noise, dc offsets, bias, notches and distortions from the nonlinear current, which improves the power quality under normal as well as under abnormal grid conditions. This single-layer GDLSR-based NN structure has a very simple architecture, which decreases the computational burden and algorithm complexity. Therefore, it is easy in implementation. In this work, the GDLSR-based control technique is tested on a single-phase single-stage grid-integrated PV topology with the nonlinear loads. The prime objective of the GDLSR-based NN structure is to provide reactive power compensation, power factor correction, harmonics filtering and mitigation of other power quality issues. Moreover, when solar irradiation is zero, the dc-link capacitor and voltage-source converter act as a distribution static compensator, which enhances the utilization factor of the system. The proposed system is modeled, and its performances are verified experimentally on a developed prototype in different grid disturbances as well as solar insolation variation conditions, which performances have satisfied the motive of the proposed technique as well as the IEEE-519 standard.
Year
DOI
Venue
2019
10.1109/TIE.2018.2886765
IEEE Transactions on Industrial Electronics
Keywords
DocType
Volume
Artificial neural networks,Harmonic analysis,Power quality,Power harmonic filters,Radiation effects,Reactive power,Band-pass filters
Journal
66
Issue
ISSN
Citations 
12
0278-0046
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Nishant Kumar114.75
Bhim Singh2448113.14
Bijaya Ketan Panigrahi323828.17