Search

This paper presents the implementation of a simple model of resistive Superconducting Fault Current Limiters (r-ScFCL) based on High Temperature Superconductor (HTS) in the software ATP/EMTP for different transient conditions appearing in distribution networks. The use of fault current limiters (FCL) is rather appealing since they can provide reduction of the short-circuit levels during faults while consuming negligible power in nominal regime. Thus far, a lot of efforts have been dedicated to the design of the equipment and lately only a few works have been focused on the impact of the device in the electrical networks. Topics of interest for the electrical sector cover the study of protection coordination and transient analysis during fault conditions. Both topics ought to be studied from the perspective of power system engineering including new technologies such as ScFCL, for instance. In the present work, part of this effort is carried out. A simplified r-ScFCL model is adopted to evaluate the dynamic performance of a given r-ScFCL under different transient conditions such as faults, transformer energisations and re-closing for distribution systems.

In this paper, a Multi Scale Recurrence Quantification Analysis (MSRQA) method is proposed to clustering harmonics on microgrid systems. MSRQA is composed by the Variational Mode Decomposition algorithm and the Recurrence Quantification Analysis (RQA). MSRQA decomposes a signal into a finite number of Mono-Component Signals (MCSs), then a feature extraction is carry out by the RQA on each MCS. Finally, the identification of the optimal number of clusters based on the features extracted by RQA and the Davies-Bouldin index is carry out on the monitored microgrid system test signals. At the end an index based on the cluster information and the RQA measure is proposed to identify the harmonics present on the dynamic system behavior.

Interturn faults are a critical problem in power transformers that can eventually escalate into catastrophic faults and probably result in an overall network failure. Also, failures in transformer windings are still a major cause of transformer outages, and failure rates vary widely between different countries and systems, depending on many factors. Therefore, in this work, interturn faults with various levels of severity were imposed on the winding of a 120 VA, 24/125 V dry type transformer to diagnose it. The obtained signals during the experiments are processed using the Wavelet Transform and correlation modes. This technique only takes into account the high frequency information produced during the energization of a winding with interturn faults.