A complete fault location formulation for distribution systems using the k-Nearest Neighbors for regression and classification

Autor:	G. Carrillo-Caicedo, German Morales-Espana, Juan Mora-Flórez
Rok vydání:	2010
Předmět:	business.industry Regression analysis Pattern recognition Fault (power engineering) k-nearest neighbors algorithm Electric power system Kernel (statistics) Noise (video) Artificial intelligence business Algorithm Electrical impedance Voltage Mathematics
Zdroj:	2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA).
DOI:	10.1109/tdc-la.2010.5762978
Popis:	This paper presents an alternative to the traditional impedance based fault location methods, using a simple technique of the learning approaches called k-Nearest Neighbors (k-NN), where besides the fault location distance, the multiple estimation problem is also addressed. This approach only uses the single end measurements of voltage and current available at the power substation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::64d51912c68c7fa19a772d74a2b2abbc https://doi.org/10.1109/tdc-la.2010.5762978 Zobrazit plný text záznamu