Discrete-Wavelet-Transform and Stockwell-Transform-Based Statistical Parameters Estimation for Fault Analysis in Grid-Connected Wind Power System

Mukherjee, Niladri; Chattopadhyay, Surajit; Chattopadhyay, Surajit; Sengupta, Samarjit

doi:10.1109/jsyst.2020.2984132

Cited by 27 publications

(16 citation statements)

References 22 publications

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“…Even it can be combined with other mathematical models to analyze the THD component and detect faults effectively. 115 For ultra-fast response and specifically in busbar protection it can be applied along with a decision algorithm. 133 The range of protective solutions S transform offers can easily be observed from Table 13.…”

Section: S-transform Based Protection Schemementioning

confidence: 99%

“…The HIF can be detected by S‐transform using a zone‐based method integrated with IED to lessen the dependency on the relay as described in Reference 132. Even it can be combined with other mathematical models to analyze the THD component and detect faults effectively 115 . For ultra‐fast response and specifically in busbar protection it can be applied along with a decision algorithm 133 .…”

Section: Other Miscellaneous Schemesmentioning

confidence: 99%

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Review of distributed generator integrated AC microgrid protection: issues, strategies, and future trends

Sarangi

Sahu

Rout

2021

Intl J of Energy Research

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In the recent power system scenario, the concept of microgrid is evolving rapidly. The architecture should be robust enough to cater the complexity of integration of distributed generation sources, demand-side management, and storage. The fast growth of embedded generation with other advanced power electronic interfaces and components along with energy storage devices change the operating pattern of the integrated power system scenario. In this context, protection is the vital aspect for qualitative uninterrupted power and making the system resilient to adverse, and faulty conditions. Many associated issues, particularly related to AC microgrid systems like the large difference in the short-circuit level between integrated and isolated mode of operation, bidirectional power flow, unsynchronized reclosing, the blindness of protection, lack of natural zero-crossing current, and false tripping are needed to be focused. In light of the above factors, it motivates us to survey the previous research works on the existing protection strategies to redesign and present the critical analysis of the predicted protection issues of microgrid protection with upcoming advanced technology and methodology. This article presents a critical review of the issues and protection schemes for the DG integrated AC microgrid extensively. Here, the merits, and demerits of each protection scheme, and visible possibilities for any advancement in protection strategies to enhance the reliability, selectivity, and security of AC microgrid is emphasized keeping in mind the different connections and configurations. In addition, this work also focuses on integrating the intelligent approaches/devices that help to elevate the current protection schemes to be smarter and efficient.

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Section: S-transform Based Protection Schemementioning

confidence: 99%

Section: Other Miscellaneous Schemesmentioning

confidence: 99%

Review of distributed generator integrated AC microgrid protection: issues, strategies, and future trends

Sarangi

Sahu

Rout

2021

Intl J of Energy Research

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“…The two main tasks of FDP methods are incipient failure detection and remaining useful life estimation through prognostics techniques [1]. The FDP approaches can be applied in different critical systems as wind turbine [2], gas turbines [3], power systems [4,5], and transmission lines [6].…”

Section: Introductionmentioning

confidence: 99%

“…Journal of Sensors wavelet is the main CWT parameter, as it may significantly influence the performance of the transformation. Recent works have proposed wavelet transform for damage detection and localization [4,6,30]. However, these works do not investigate a quantitative approach for mother wavelet selection.…”

Section: Introductionmentioning

confidence: 99%

A Damage Detection Method Using Neural Network Optimized by Multiple Particle Collision Algorithm

et al. 2021

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A critical task of structural health monitoring is damage detection and localization. Lamb wave propagation methods have been successfully applied for damage identification in plate-like structures. However, Lamb wave processing is still a challenging task due to its multimodal and dispersive characteristics. To address this issue, data-driven machine learning approaches as artificial neural network (ANN) have been proposed. However, the effectiveness of ANN can be improved based on its architecture and the learning strategy employed to train it. The present paper proposes a Multiple Particle Collision Algorithm (MPCA) to design an optimum ANN architecture to detect and locate damages in plate-like structures. For the first time in the literature, the MPCA is applied to find damages in plate-like structures. The present work uses one piezoelectric transducer to generate Lamb wave signals on an aluminum plate structure and a linear array of four transducers to capture the scattered signals. The continuous wavelet transform (CWT) processes the captured signals to estimate the time-of-flight (ToF) that is the ANN inputs. The ANN output is the damage spatial coordinates. In addition to MPCA optimization, this paper uses a quantitative entropy-based criterion to find the best mother wavelet and the scale values. The presented experimental results show that MPCA is capable of finding a simple ANN architecture with good generalization performance in the proposed damage localization application. The proposed method is compared with the 1-dimensional convolutional neural network (1D-CNN). A discussion about the advantages and limitations of the proposed method is presented.

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“…The energy (or magnitude) at a specific frequency can be viewed as a function of time. The spectral localisation properties of the ST has led to applications in many fields, such as biomedical engineering [10–16]; geophysics [17, 18]; biometric [19]; electrical engineering [20–26]; image processing [27, 28], etc. The ST has also been extended to design generalised ST [29], fractional ST [30, 31] and canonical ST [32].…”

Section: Introductionmentioning

confidence: 99%

Compact S‐transform for analysing local spectrum

Pradhan

Mansinha

2020

IET signal process.

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The Fourier transform of a N point time series is a N point complex series, while the S‐transform (ST) of the same time series is a N×N 2D time–frequency complex matrix. The computation and storage of N2−N additional points are a major drag on the usage of ST. In this study the compact S‐transform (cST) is presented, with efficiencies brought about through computation of only selected voices (frequencies). The cST spectrum has uncomputed voice gaps that increase in width towards the higher frequencies. Plot of the cST magnitude spectrum is virtually indistinguishable from the ST magnitude plot. Local spectrum at any spot on the cST can be quickly examined in detail through interpolation. The cST requires the computation of approximately 3N voices compared to falsefalse⌊N/2falsefalse⌋+1 for the ST. The proportion of computed voices decrease for larger N. For N=1024, ∼20% of the voices in the time‐frequency spectrum is computed; for N=2048 only 14% of the voices is computed. For applications, such as audio and speech signal processing where segments of one million samples are not uncommon, <1% of the voices are computed, thereby reducing the computation time by ∼99%.

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Discrete-Wavelet-Transform and Stockwell-Transform-Based Statistical Parameters Estimation for Fault Analysis in Grid-Connected Wind Power System

Cited by 27 publications

References 22 publications

Review of distributed generator integrated AC microgrid protection: issues, strategies, and future trends

Review of distributed generator integrated AC microgrid protection: issues, strategies, and future trends

A Damage Detection Method Using Neural Network Optimized by Multiple Particle Collision Algorithm

Compact S‐transform for analysing local spectrum

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