Abstract
Transmission lines of any electrical power system are a crucial means to provide electricity continuously to the end consumers. However, since these transmission lines are vulnerable to their surroundings, there are higher chances of an event leading to a run down. Such a disruption needs to be remedied quickly to protect the power system and continue the flow of electricity as per demand. Therefore, this paper has an objective to present a valid solution to control such a situation for betterment of the power system. The work attempted in this paper is an absolute, reliable and swift technique using the artificial neural network (ANN) to detect and classify the faults that occur in electrical transmission lines. The proposed idea takes into account an IEEE 9 bus system for generating data sets for training the ANN. Implementation of the presented method is done on the IEEE 9 bus system for detection and identification of fault types to provide evidence of its credibility.
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Terang, P.P., Bisoyi, S.K., Ranjan, C., Krishna, A., Rai, A.R., Singh, A. (2022). Detection and Classification of Transmission Line Faults Using ANN. In: Panda, G., Naayagi, R.T., Mishra, S. (eds) Sustainable Energy and Technological Advancements. Advances in Sustainability Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-16-9033-4_18
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DOI: https://doi.org/10.1007/978-981-16-9033-4_18
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