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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Bibliographic Details
Published inISGT2011-India pp. 78 - 83
Main Authors Kumar, A., Chakrabarti, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2011
Subjects
Artificial neural networks
Current measurement
Hybrid state estimation
Phasor measurement units
Power measurement
power system visualization
Power systems
radial basis function networks
synchrophasors
Training
Vectors
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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.
ISBN:9781467303163
146730316X
DOI:10.1109/ISET-India.2011.6145359