Journal Article

FZJ-2019-05331

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Measurement Selection for Data-Driven Monitoring of Distribution Systems

Ferdowsi, M. ; Benigni, A. (Corresponding author)FZJ* ; Monti, A. ; Ponci, F.

2019
IEEE New York, NY

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Please use a persistent id in citations: doi:10.1109/JSYST.2019.2939500

Abstract: This article investigates the problem of measurement selection for data-driven monitoring approaches. Several approaches to input variable selection (IVS) are analyzed, and a general procedure for finding the optimal order for the selection of candidate measurements is presented. The method is based on the extensions of partial correlation and minimal redundancy maximum relevance criteria to support IVS problems involving multiple outputs. This method can be used to find the minimal set of measurements for achieving a target estimation accuracy. The results demonstrate the advantages and limits of the introduced method in comparison to the other approaches discussed in this article.

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Contributing Institute(s):

1. Modellierung von Energiesystemen (IEK-10)

Research Program(s):

1. 899 - ohne Topic (POF3-899) (POF3-899)

Appears in the scientific report 2019

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Database coverage:
Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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