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Highlighting of local Power Quality states with the new QuEEN system, enhanced with Deep Learning and Machine Learning algorithms

Related tags

#Electricity Network #Quality of Supply

Publications - Paper

Highlighting of local Power Quality states with the new QuEEN system, enhanced with Deep Learning and Machine Learning algorithms

The enhancement of the new QuEEN system, with the integration of Deep Learning and Machine Learning algorithms for assessing the validity and origin of voltage sags, has allowed for the identification and highlighting of specific situations concerning Power Quality.

The enhancement of the new QuEEN system, integrating Deep Learning and Machine Learning algorithms for assessing the validity and origin of voltage sags, has enabled the identification and highlighting of specific situations related to Power Quality.

 

Regional comparisons have been made between the outcomes of the new algorithms and those historically implemented in QuEEN, cross-referencing the results with network data. While nationally the comparison results confirm previous assumptions, locally, specific situations regarding the frequency of false voltage sags and hence single-phase earth faults are observed. These situations are analyzed in relation to network characteristics.

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Rif.RSE​

22008522

Destination​

114th Edition AEIT International Annual Conference, Rome, October 3-5, 2022

Publication Date

05 October 2022

Authors​

M. Zanoni, R. Chiumeo, L. Tenti, M. Volta (RSE S.p.A.)

Publication Type

Paper

Projects

Evolution, planning, scheduling and operation of power grids (Networks)

Target​

Research

Related tags

#Electricity Network #Quality of Supply

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