Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/22754
Title: | High Impedance Fault and Heavy Load under Big Data Context |
Authors: | Lai, CS |
Keywords: | High Impedance Fault;Heavy Load;Big Data;Grid Analytics |
Issue Date: | 2015 |
Publisher: | IEEE |
Citation: | Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015, 2016, pp. 653 - 658 |
Abstract: | Detecting and identifying High Impedance Fault (HIF) in distribution system is an essential task for a secure and reliable grid. The ability for relaying system to differentiate HIF and heavy load condition is still a challenging problem as their current and voltage characteristics are very similar. This paper demonstrates how discrete wavelet transform can be used to identify the two cases. It also reviews how big data analytics could be used to improve this long standing problem. A simple power system model constructed in Dig SILENT Power Factory performs the short circuit analysis for the HIF and the open circuit islanding for the heavy load conditions. MATLAB will be used for discrete wavelet transform analysis for the output from the power system model. |
URI: | http://bura.brunel.ac.uk/handle/2438/22754 |
DOI: | http://dx.doi.org/10.1109/SMC.2015.124 |
ISBN: | 9781479986965 |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
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