| 1. |
- Ferreira, Danton D., et al.
(author)
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A new power quality deviation index based on principal curves
- 2015
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In: Electric power systems research. - : Elsevier BV. - 0378-7796 .- 1873-2046. ; 125, s. 8-14
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Journal article (peer-reviewed)abstract
- In this paper, a new power quality deviation index based on principal curves is proposed. The index provides a quantitative measure, which gives an idea of how much the monitored electrical signal has deviated from the nominal one. Differently of existing indices, the proposed index is a general index, i.e., it can be used for any type of disturbance in the monitored signal. In addition, the proposed index is used to perform a direct approach for detecting disturbances in power signals. This approach is able to detect the beginning and localize the disturbance by analyzing non-overlapping signal windows of one cycle of the fundamental component, leading to a simple method in terms of computational complexity
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| 2. |
- Ferreira, Danton D., et al.
(author)
-
Extracting the transient events from power system signals by independent component analysis
- 2016
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In: International Transactions on Electrical Energy Systems. - : Hindawi Limited. - 2050-7038. ; 26:4, s. 884-900
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Journal article (peer-reviewed)abstract
- This paper presents a method for extracting transient events from the power system signal based on independent component analysis. The extraction of transients is important to diagnose the system in terms of power quality, because the computation of power quality indices from the extracted events is more efficient and easier to be carried out. Furthermore, the proposed method can be applied as a preprocessing tool for transient characterization in disturbance detection, classification, and identification systems. Both qualitative and quantitative analyses demonstrate the efficiency and the advantages of the proposed method in comparison with other approaches commonly used for the same purpose.
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| 3. |
- Nagata, Erick A., et al.
(author)
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Real-Time Voltage Sag Detection and Classification for Power Quality Diagnostics
- 2020
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In: Measurement. - : Elsevier. - 0263-2241 .- 1873-412X. ; 164
-
Journal article (peer-reviewed)abstract
- This work proposes an innovative approach to detect, segment and classify voltage sags according to their causes. To detect and segment, Independent Component Analysis is used, with the advantage of being fast and with low computational effort in the operational stage, once it uses only 1/8 cycle of the fundamental component. For classification purposes, Higher-Order Statistics are used for feature extraction and the classifiers are based on Neural Networks and Support Vector Machines. It was tested signal windows of 1, 1/2, 1/4 and 1/8 cycle. For both detection/segmentation design and feature selection, it was used the metaheuristics Teaching-Learning-Based Optimization. Encouraging results were achieved for the simulated signals. In addition, real signals were used to evaluate the detection and segmentation method and good results were achieved in which a detection error rate of 0.86% was achieved.
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