Energy efficient software and hardware configuration of the digital substation in accordance with IEC 61850

Al-Tibbi, Wisam

doi:10.1051/e3sconf/202127901024

Cited by 1 publication

(1 citation statement)

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“…The basics of the protocol configuration are described in [ 25 ], and its implementation is explained in [ 26 ] to automate substation operations and address the impact of communication delays on the automated system during peak loads. In addition, according to [ 27 ], the implementation of the protocol (together with the included GOOSE and SCADA systems) in a power distribution system will increase the system’s reliability by 1.5–2 times, and power losses by 10% or more. Finally, with the endorsement of the above protocol, the way has been opened for achieving what is defined as digital switchgear.…”

Section: The Broadening Of the Perspectivementioning

confidence: 99%

Switchgear Digitalization—Research Path, Status, and Future Work

Kaštelan

Vujović

Krčum

et al. 2022

Sensors

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To keep pace with global energy efficiency trends and, in particular, emission reduction targets in the maritime sector, both onshore and maritime power distribution systems need to be adapted to the relevant new technologies and concepts. As an important link in the distribution chain, medium-voltage switchgear (MV) is expected to be stable and reliable while operating as efficiently as possible. Failures of MV equipment, while rare because the equipment must be safe to handle and use, have far-reaching consequences. The consequences of such failures, whether to the shore or marine power system, present risks to the entire power plant, so an accurate assessment of equipment condition is required to identify potential failures early. The solution is an emerging concept of digital switchgear, where the implementation of sensor technology and communication protocols enables effective condition monitoring, and the creation of a database that, when combined with machine learning algorithms, enables predictive maintenance and/or fault detection. This paper presents, step by step, the previous challenges, the current research (divided into predictive maintenance, condition monitoring, and fault detection categories), and the future directions in this field. The use of artificial intelligence is discussed to eliminate the disadvantage of manually interpreting operational data, and recommendations for future work are formulated, such as the need to standardize test procedures and data sets to train and compare different algorithms before they are used in practice.

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Section: The Broadening Of the Perspectivementioning

confidence: 99%