HIF Detection and Classification in Distribution Systems using Wavelet Transforms
B. Baddu Naik1, M. Hemanth Sai2, B. Bala Sai Babu3
1B. Baddu Naik., Department of Electrical & Electronics Engineering, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, A.P., India.
2M. Hemanth Sai, Department of Electrical & Electronics Engineering, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, A.P., India.
3B. Bala Sai Babu, Department of Electrical & Electronics Engineering, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, A.P., India.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 10008-10013 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8614118419/2019©BEIESP | DOI: 10.35940/ijrte.D8614.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: High Impedance Faults (HIF) are generally occurs on distribution line. HIFs are, by and large, hard to recognize through traditional assurance, for example, distance or over current relays. This is primarily because of hand-off inhumanity toward the low level fault currents as well as constraints on other hand-off settings forced by HIFs. Regular assurance hand-off framework won’t have the option to distinguish the HIFs and excursion the security transfer. HIFs on electrical transmission and dissemination systems include arcing as well as nonlinear attributes of flaw impedance which cause repeating example and contortion. Subsequently, the goal of most discovery plans is to recognize extraordinary highlights in examples of the voltages and current related with HIFs. Most traditional flaw discovery strategies for HIF for the most part include preparing data dependent on the component extraction of post HIF current and voltage. Wavelet transform is most appropriate for HIF location and for fault classification. This paper depicts another shortcoming location procedure which includes catching the present sign created in a framework under HIFs. The identification procedure depends on ascertaining the total entirety of the wavelet transform detail coefficients for one period. Wavelet transform is utilized for the disintegration of sign and highlight extraction.
Keywords: About High Impedance Faults, Distribution Lines and Wavelet Transform.
Scope of the Article: Knowledge Modelling, Integration, Transformation, and Management.