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| Title: | Predicting load harmonics in three phase systems using neural networks | |
| Author (s): | Mazumdar, J. Harley, R.G. Lambert, F. Venayagamoorthy, Ganesh K. | |
| Department/Lab Affiliations: | Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory | |
| Keywords: | artificial neural network harmonic distortion load harmonics neural nets nonlinear admittance nonlinear impedance power system analysis computing power system harmonics power system network three phase nonlinear loads | |
| Issue Date: | 2006 | |
| Publisher: | Institute of Electrical and Electronics Engineers | |
| Citation: | Mazumdar, J.; Harley, R.G.; Lambert, F.; Venayagamoorthy, G.K., "Predicting load harmonics in three phase systems using neural networks" APEC '06. Twenty-First Annual IEEE Applied Power Electronics Conference and Exposition, 2006. pp. 7 pp.-, 19-23 March 2006 | |
| Abstract: | This paper proposes a artificial neural network (ANN) based method for the problem of measuring the actual harmonic current injected into a power system network by three phase nonlinear loads without disconnecting any loads from the network. The ANN directly estimates or identifies the nonlinear admittance (or impedance) of the load by using the measured values of voltage and current waveforms. The output of this ANN is a waveform of the current that the load would have injected into the network if the load had been supplied from a sinusoidal voltage source and is therefore a direct measure of load harmonics. | |
| Type: | Article - Conference proceedings text | |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: | |
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| title | Predicting load harmonics in three phase systems using neural networks | |
| contributor.author | Mazumdar, J. | |
| contributor.author | Harley, R.G. | |
| contributor.author | Lambert, F. | |
| contributor.author | Venayagamoorthy, Ganesh K. | |
| contributor.deptlab | Electrical and Computer Engineering | |
| contributor.deptlab | Real-Time Power and Intelligent Systems Laboratory | |
| subject | artificial neural network | |
| subject | harmonic distortion | |
| subject | load harmonics | |
| subject | neural nets | |
| subject | nonlinear admittance | |
| subject | nonlinear impedance | |
| subject | power system analysis computing | |
| subject | power system harmonics | |
| subject | power system network | |
| subject | three phase nonlinear loads | |
| date.issued | 2006 | |
| date.submitted | 2007 | |
| publisher | Institute of Electrical and Electronics Engineers | |
| identifier.citation | Mazumdar, J.; Harley, R.G.; Lambert, F.; Venayagamoorthy, G.K., "Predicting load harmonics in three phase systems using neural networks" APEC '06. Twenty-First Annual IEEE Applied Power Electronics Conference and Exposition, 2006. pp. 7 pp.-, 19-23 March 2006 | |
| identifier.pub.URI | ||
| description.abstract | This paper proposes a artificial neural network (ANN) based method for the problem of measuring the actual harmonic current injected into a power system network by three phase nonlinear loads without disconnecting any loads from the network. The ANN directly estimates or identifies the nonlinear admittance (or impedance) of the load by using the measured values of voltage and current waveforms. The output of this ANN is a waveform of the current that the load would have injected into the network if the load had been supplied from a sinusoidal voltage source and is therefore a direct measure of load harmonics. | |
| type | Article - Conference proceedings | |
| type.DCMIType | text | |
| type.status | Final version | |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | |
| rights.URI | ||
| date.accessioned | 2007-04-05T14:26:45Z | |
| date.available | 2007-04-05T14:26:44Z | |
| identifier.persist.URI | ||
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