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Drone-aided electrical current sensing - a breakthrough for smart grids

Publication date
2024-12-20
Document type
Sammelbandbeitrag oder Buchkapitel
Author
Alosmani, Khaled 
Schulz, Detlef 
Organisational unit
Elektrische Energiesysteme 
DTEC.bw 
DOI
10.24405/16785
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/16785
ISBN
978-3-86818-329-0
Project
Digitalisierte, rechtssichere und emissionsarme flugmobile Inspektion und Netzdatenerfassung mit automatisierten Drohnen 
Book title
dtec.bw-Beiträge der Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg : Forschungsaktivitäten im Zentrum für Digitalisierungs- und Technologieforschung der Bundeswehr dtec.bw : Band 2 – 2024
First page
105
Last page
110
Is part of
https://openhsu.ub.hsu-hh.de/handle/10.24405/16768
Peer-reviewed
✅
Part of the university bibliography
✅
Files
 openHSU_16785.pdf (1.8 MB)
  • Additional Information
Keyword
dtec.bw
Drone
Intelligent sensor
Smart grid
Remote surveillance
Abstract
This paper serves as an overview of the current progress concerning the DNeD (Digitalized, legally safe and low-emission airborNe inspection and grid data acquisition using automated Drones) project. DNeD aims to provide a full solution of an intelligent current sensor, integrable inside a dedicated drone-embedded sensor box. The research began with a brief survey of non-invasive current sensing technologies as a guide for the selection of the optimum current sensing physics. Afterwards, an all-optical sensor (MICATU RG235) was tested under laboratory conditions. The results from these tests were systematically tabulated. Concurrently, a study on magnetic field-based current sensing was performed using Finite Element Analysis (FEA) in COMSOL. This dual approach allows for a comprehensive evaluation of different sensing technologies. Ultimately, the study concludes that magnetic-based sensing, utilizing Hall effect sensors (e.g. DRV5055), is by far the most suitable approach. Additionally, the design of the sensor-box housing considered crucial mechanical factors such as robustness and weight. The design process utilized CAD models developed in SolidWorks, which form the backbone for real sensor-box manufacturing. Overall, the circuitry suggestions consisted of the development of analogue modulation electronic circuits, incorporating low pass filters, voltage dividers, and additional protective circuitry to ensure the reliability and accuracy of the sensor data. A prototype was developed, featuring Bluetooth as the communication protocol between the sensor-box and a remote system running MATLAB. Preliminary results indicate that the prototype effectively transfers dummy analogue voltage signals over distances up to 30 metres, demonstrating the feasibility of the design for practical applications. This comprehensive study not only addresses the mechanical and physical design aspects of embedding an intelligent sensor in a drone but also explores various current sensing technologies and their practical implementation. The findings provide a robust framework for future development and optimization of intelligent sensor systems in aerial applications.
Version
Published version
Access right on openHSU
Open access

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