This paper introduces a simple solution, based on neural networks, to the problem of the on-line and adaptive harmonic component analysis in power systems. A single neuron is used whose synaptic weights are directly related to the signal's dc component and to the magnitudes and phases of the harmonic components present in the signal. In addition, deviation from the nominal fundamental frequency is accounted for in the same context. The simulation of a realistic test case shows a very efficient and precise estimation of the present harmonic
In this paper, artificial neural networks are employed in a novel approach to identify harmonic comp...
An alternative method is presented in this paper to identify the harmonic components of non-linear l...
This thesis proposes identifying approaches and recognition of current harmonics that are based on m...
This paper introduces a simple solution, based on neural networks, to the problem of the on-line and...
The importance of the electric power quality (PQ) demands new methodologies and measurement tools in...
A collaborative work between Northumbria University and University of Peradeniya (Sri Lanka). It pre...
[[abstract]]The widespread application of power electronic loads has led to increasing harmonic poll...
This study presents an artificial neural network based intelligent monitoring algorithm to detect of...
The paper presents a new approach for the estimation of harmonic components of a power system using ...
This research presents a new approach to analyze harmonics in electrical power distribution network ...
This research presents a new approach to analyze harmonics in electrical power distribution network ...
This research presents a new approach to analyze harmonics in electrical power distribution network ...
The joint time-frequency analysis of power system quantities is a powerful approach to monitor the d...
In this paper, an adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to estima...
Harmonic estimation is the foundation of every active noise canceling method in low-voltage power sy...
In this paper, artificial neural networks are employed in a novel approach to identify harmonic comp...
An alternative method is presented in this paper to identify the harmonic components of non-linear l...
This thesis proposes identifying approaches and recognition of current harmonics that are based on m...
This paper introduces a simple solution, based on neural networks, to the problem of the on-line and...
The importance of the electric power quality (PQ) demands new methodologies and measurement tools in...
A collaborative work between Northumbria University and University of Peradeniya (Sri Lanka). It pre...
[[abstract]]The widespread application of power electronic loads has led to increasing harmonic poll...
This study presents an artificial neural network based intelligent monitoring algorithm to detect of...
The paper presents a new approach for the estimation of harmonic components of a power system using ...
This research presents a new approach to analyze harmonics in electrical power distribution network ...
This research presents a new approach to analyze harmonics in electrical power distribution network ...
This research presents a new approach to analyze harmonics in electrical power distribution network ...
The joint time-frequency analysis of power system quantities is a powerful approach to monitor the d...
In this paper, an adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to estima...
Harmonic estimation is the foundation of every active noise canceling method in low-voltage power sy...
In this paper, artificial neural networks are employed in a novel approach to identify harmonic comp...
An alternative method is presented in this paper to identify the harmonic components of non-linear l...
This thesis proposes identifying approaches and recognition of current harmonics that are based on m...