Title:	Improving the Performance of Distance Relay-Based Artificial Neural Network
Authors:	Dashtdar, Masoud Bělík, Milan Yadav, Arvind Hosseinimoghadam, Seyed Mohammad Sadegh Bajaj, Mohit Rubanenko, Olena
Citation:	DASHTDAR, M. BĚLÍK, M. YADAV, A. HOSSEINIMOGHADAM, SMS. BAJAJ, M. RUBANENKO, O. Improving the Performance of Distance Relay-Based Artificial Neural Network . In 2022 IEEE 3rd KhPI Week on advanced Technology (KhPI Week 2022) : conference proceedings. Piscaway: IEEE, 2022. s. nestránkováno. ISBN: 979-8-3503-9920-2
Issue Date:	2022
Publisher:	IEEE
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85141488620 http://hdl.handle.net/11025/51688
ISBN:	979-8-3503-9920-2
Keywords in different language:	distance relay;fault location;artificial neural network;transmission network
Abstract in different language:	Distance relays for protection of power transmission lines used, which can be based on fixed stings Adjusted. But usually, the amplitude of operation of these relays changes with changing network conditions (network topology, load value, output value, etc.) and causes the relay to malfunction, using methods that can process information and pattern recognition, such as the use of fine processors and intelligent algorithms can use new relays that have high accuracy and thus achieve proper protection. In this paper, a distance relay is simulated by a neural network and it is observed that the neural relay has higher accuracy than a normal relay. In addition to fault detection and location, the type and phase of the fault can perform simultaneous protection of three phases. As a result, the number of line relays can be reduced by using neural relays. The MLP neural network is used to simulate the distance relay.
Rights:	Plný text je přístupný v rámci univerzity přihlášeným uživatelům © IEEE
Appears in Collections:	Konferenční příspěvky / Conference papers (RICE) Konferenční příspěvky / Conference Papers (KEE) OBD

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