Optimal Sensor Placement for Contactless Medium- or High-Voltage Measurement

The paper presents a method for selecting the locations of field sensors under a medium- or high-voltage line or substation busbars, in a contactless voltage measurement system. The proposed method uses the condition number of a distance matrix, correlated with the capacitance matrix of a system, as an optimization criterion. As a robust optimization algorithm was expected to be necessary for this task, genetic algorithm and particle swarm optimization algorithm have been tested, both in regular and hybrid versions. The proposed method was tested in simulations, using four power line geometries based on real-life pylons. Optimization results were juxtaposed with reference values coming from a sensor placement that would most probably be selected by a human operator when not using optimization. The proposed method offers significantly better (although still not good) conditioning of a system equation compared to reference placements. The results also provide an interesting insight into the influence of popular line geometries on numerical properties (and thus one component of uncertainty) of a contactless measurement system.

Institutions

Publication Details

Journal
Energies
Published
2025-09-19
DOI
https://doi.org/10.3390/en18184982
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimal Sensor Placement for Contactless Medium- or High-Voltage Measurement

Energies
Geochemistry and Geologic Mapping
article

Optimal Sensor Placement for Contactless Medium- or High-Voltage Measurement

article en

Abstract

The paper presents a method for selecting the locations of field sensors under a medium- or high-voltage line or substation busbars, in a contactless voltage measurement system. The proposed method uses the condition number of a distance matrix, correlated with the capacitance matrix of a system, as an optimization criterion. As a robust optimization algorithm was expected to be necessary for this task, genetic algorithm and particle swarm optimization algorithm have been tested, both in regular and hybrid versions. The proposed method was tested in simulations, using four power line geometries based on real-life pylons. Optimization results were juxtaposed with reference values coming from a sensor placement that would most probably be selected by a human operator when not using optimization. The proposed method offers significantly better (although still not good) conditioning of a system equation compared to reference placements. The results also provide an interesting insight into the influence of popular line geometries on numerical properties (and thus one component of uncertainty) of a contactless measurement system.

EnergiesVol. 18(18)
Jagiellonian University (PL), AGH University of Krakow (PL)
Openalex Percentile: Top 34%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimal Sensor Placement for Contactless Medium- or High-Voltage Measurement · Energies (2025) | TGRS Research Map | TGRS