FAULT LOCATING IN HVDC TRANSMISSION LINES USING GENERALIZED REGRESSION NEURAL NETWORK AND RANDOM FOREST ALGORITHM

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FARSHAD M.; SADEH J.

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Paper Information

Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2013 | Volume:4 | Issue:2 Page(s): 1-14

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Information Journal Paper

Title

FAULT LOCATING IN HVDC TRANSMISSION LINES USING GENERALIZED REGRESSION NEURAL NETWORK AND RANDOM FOREST ALGORITHM

Author(s)

FARSHAD M. | SADEH J. | Issue Writer Certificate

Keywords

FAULT LOCATIONQ2

HVDC TRANSMISSION LINESQ2

GENERALIZED REGRESSION NEURAL NETWORKQ2

RANDOM FOREST ALGORITHMQ2

Abstract

This paper presents a novel method based on machine learning strategies for fault locating in high voltage direct current (HVDC) transmission lines. In the proposed fault-location method, only post-fault voltage signals measured at one terminal are used for feature extraction. In this paper, due to high dimension of input feature vectors, two different estimators including the GENERALIZED REGRESSION NEURAL NETWORK (GRNN) and the random forest (RF) algorithm are examined to find the relation between the features and the FAULT LOCATION. The results of evaluation using training and test patterns obtained by simulating various fault types in a long overhead transmission line with different FAULT LOCATIONs, fault resistance and pre-fault current values have indicated the efficiency and the acceptable accuracy of the proposed approach.

Cites

GROUNDWATER POTENTIAL MAPPING USING SHANNON'S ENTROPY AND RANDOM FOREST MODELS IN THE BOJNOURD PLAIN

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APA: Copy

FARSHAD, M., & SADEH, J.. (2013). FAULT LOCATING IN HVDC TRANSMISSION LINES USING GENERALIZED REGRESSION NEURAL NETWORK AND RANDOM FOREST ALGORITHM. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 4(2), 1-14. SID. https://sid.ir/paper/203049/en

Vancouver: Copy

FARSHAD M., SADEH J.. FAULT LOCATING IN HVDC TRANSMISSION LINES USING GENERALIZED REGRESSION NEURAL NETWORK AND RANDOM FOREST ALGORITHM. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2013;4(2):1-14. Available from: https://sid.ir/paper/203049/en

IEEE: Copy

M. FARSHAD, and J. SADEH, “FAULT LOCATING IN HVDC TRANSMISSION LINES USING GENERALIZED REGRESSION NEURAL NETWORK AND RANDOM FOREST ALGORITHM,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 4, no. 2, pp. 1–14, 2013, [Online]. Available: https://sid.ir/paper/203049/en

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