Comparison of electromagnetic fields emitted by typical overhead power line towers

Bendík, Jozef; Cenký, Matej; Eleschová, Žaneta; Beláň, Anton; Cintula, Boris; Janiga, Peter

doi:10.1007/s00202-020-01140-1

Cited by 7 publications

(1 citation statement)

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“…Determination of the magnetic flux density distribution near overhead lines is usually performed by measurements or calculations applying the Biot-Savart (BS) law-based method or numerical methods for solving Maxwell's equations [21][22][23][24][25]. Recently, ANNs [26][27][28] and genetic algorithm [29] have been applied for the overhead lines' electric and magnetic field determination.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network-based method for overhead lines magnetic flux density estimation

Alihodžić,

Mujezinović,

Turajlić

2024

Journal of Electrical Engineering

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This paper presents an artificial neural network (ANN) based method for overhead lines magnetic flux density estimation. The considered method enables magnetic flux density estimation for arbitrary configurations and load conditions for single-circuit, multi-circuit, and also overhead lines that share a common corridor. The presented method is based on the ANN model that has been developed using the training dataset that is produced by a specifically designed algorithm. This paper aims to demonstrate a systematic and comprehensive ANN-based method for simple and effective overhead lines magnetic flux density estimation. The presented method is extensively validated by utilizing experimental field measurements as well as the most commonly used calculation method (Biot - Savart law based method). In order to facilitate extensive validation of the considered method, numerous magnetic flux density measurements are conducted in the vicinity of different overhead line configurations. The validation results demonstrate that the used method provides satisfactory results. Thus, it could be reliably used for new overhead lines’ design optimization, as well as for legally prescribed magnetic flux density level evaluation for existing overhead lines.

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Section: Introductionmentioning

confidence: 99%

Artificial neural network-based method for overhead lines magnetic flux density estimation

Alihodžić,

Mujezinović,

Turajlić

2024

Journal of Electrical Engineering

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Three-phase and single-phase measurement of overhead power line capacitance evaluation

et al. 2023

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Sustainable Futures in a Changing World – Reflections from the 5th International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2024)

Kiv,

Semerikov,

Nechypurenko

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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This paper presents an overview of the 5th International Conference on Sustainable Futures: Environmental, Technological, Social, and Economic Matters (ICSF 2024), held in May 2024. The conference brought together over 250 researchers, practitioners, and educators from 19 countries to share cutting-edge research and innovative solutions across a wide range of sustainability-related disciplines. The proceedings cover diverse topics, including climate change, disaster risk reduction, sustainable infrastructure, education for sustainability, environmental engineering, and sustainable business practices. Key themes that emerged include the integration of digital technologies in sustainability efforts, the impacts of global crises on sustainable development, and the importance of interdisciplinary approaches. The conference showcased both theoretical advancements and practical applications, with a particular focus on addressing the United Nations Sustainable Development Goals. This overview highlights the conference’s role in fostering global dialogue and collaboration to address pressing sustainability challenges and shape a more sustainable future.

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Comparison of electromagnetic fields emitted by typical overhead power line towers

Cited by 7 publications

References 10 publications

Artificial neural network-based method for overhead lines magnetic flux density estimation

Artificial neural network-based method for overhead lines magnetic flux density estimation

Three-phase and single-phase measurement of overhead power line capacitance evaluation

Sustainable Futures in a Changing World – Reflections from the 5th International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2024)

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