{"title":"ANFIS Approach for Locating Faults in Underground Cables","authors":"Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat","volume":90,"journal":"International Journal of Electrical and Computer Engineering","pagesStart":905,"pagesEnd":911,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/9998531","abstract":"
This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.<\/p>\r\n\r\n
Different faults and locations are simulated by ATP\/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.<\/p>\r\n","references":"[1]\tNingkang and Yuan Liao. 2010, Fault Location Estimation Using Current Magnitude Measurements. , Proceedings of the IEEE Southest Conference (SECON 10).\r\n[2]\tJ. Moshtagh, R. K. Aggarwal, A new approach to fault location in a single core underground cable system using combined fuzzy logic & wavelet analysis, The Eight IEE International Conference on Developments In Power System Protection, pp. 228-231, April 2004.\r\n[3]\tJavad Sadeh, Hamid Afradi, A new and accurate fault location algorithm for combined transmission lines using Adaptive Network-Based Fuzzy Inference System, Electric Power Systems Research vol. 79 (2009), pp. 1538\u20131545.\r\n[4]\tJ. J. Mora, G. Carrillo , Fault Location in Power Distribution Systems using ANFIS Nets and Current Patterns, 2006 IEEE PES Transmission and Distribution Conference and Exposition Latin America, Venezuela.\r\n[5]\tRasli, Hussain and Fauzi (2012), Fault Diagnosis in Power Distribution Network Using Adaptive Neuro-Fuzzy Inference System (ANFIS), Fuzzy Inference System - Theory and Applications.\r\n[6]\tInternational Cables Co. SAE, Web Site: http:\/\/www.intlcables.com\/aProducts\/MVCables.aspx \r\n[7]\tIEEE Guide for Determining Fault Location on AC Transmission and Distribution Lines , Jun. 2005, IEEE Standard C37.114\u20132004.\r\n","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 90, 2014"}