ANN-based hybrid state estimation and enhanced visualization of power systems
The paper presents an artificial neural network (ANN)-based hybrid state estimator for estimating the states of a power system in the presence of conventional asynchronous as well as synchronous phasor measurements. Case studies on test systems show promising results for the ANN-based estimator. The...
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Published in | ISGT2011-India pp. 78 - 83 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.12.2011
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Subjects | |
Online Access | Get full text |
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Summary: | The paper presents an artificial neural network (ANN)-based hybrid state estimator for estimating the states of a power system in the presence of conventional asynchronous as well as synchronous phasor measurements. Case studies on test systems show promising results for the ANN-based estimator. The paper also presents methodologies to enhance the visualization of the power system during the intervals between successive outputs of the conventional state estimator. The ANN-based state estimators trained with measurements from phasor measurement units (PMUs) are shown to be useful for enhancing the visualization of the power system during such intervals. |
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ISBN: | 9781467303163 146730316X |
DOI: | 10.1109/ISET-India.2011.6145359 |