Fast fault detection and classification based on a combination of wavelet singular entropy theory and fuzzy logic in distribution lines in the presence of distributed generations

Dehghani, Moslem; Khooban, Mohammad Hassan; Niknam, Taher

doi:10.1016/j.ijepes.2015.11.048

Cited by 155 publications

(69 citation statements)

References 27 publications

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“…This fact is used to discriminate between permanent and temporary faults. It is robust against noise but fuzzy logic needs predefined logic sets which cannot be improved once established [43,44].…”

Section: Time-frequency Domain Analysis Basedmentioning

confidence: 99%

A review of single phase adaptive auto-reclosing schemes for EHV transmission lines

Khan

2019

Prot Control Mod Power Syst

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Statistics shows that transients produced by lightning or momentary links with external objects, have produced more than 80% of faults in overhead lines. Reclosing of circuit breaker (CB) after a pre-defined dead time is very common however reclosing onto permanent faults may damage the power system stability and aggravate severe damage to the system. Thus, adaptive single-phase auto-reclosing (ASPAR) based on investigating existing electrical signals has fascinated engineers and researchers. An ASPAR blocks CB reclosing onto permanent faults and allows reclosing permission once secondary arc is quenched. To address the subject, there have been many ASPARs techniques proposed based on the features trapped in a faulty phase. This paper presents a critical survey of adaptive auto-reclosing schemes that have hitherto been applied to EHV transmission lines.

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Section: Time-frequency Domain Analysis Basedmentioning

confidence: 99%

A review of single phase adaptive auto-reclosing schemes for EHV transmission lines

Khan

2019

Prot Control Mod Power Syst

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“…In [17,18], WT was applied to develop the reclosing algorithm in a distribution system. In [19,20], WT was applied to fault detection and classification. In [21], WT was applied to microgrid protection.…”

Section: Introductionmentioning

confidence: 99%

New Protection Scheme Based on Coordination with Tie Switch in an Open-Loop Microgrid

Seo¹

2019

Energies

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Owing to the increase in renewable energy, microgrids (MGs) are increasing. A MG has a small loop-type grid configuration. In the loop MG, challenges in protection such as maloperation of protection relay may occur owing to bidirectional current flow. Herein, we propose a new protection scheme in the loop MG. Considerations for protection in loop MG and fault characteristics are analyzed. Based on these, a new index to solve the considerations for MG protection are proposed using a wavelet transform. Furthermore, the new protection scheme based on the coordination with tie switch using the proposed new index is proposed. To verify the proposed scheme, the MG and the proposed scheme are modeled using the electromagnetic transients program and MATLAB. Various simulations according to the fault location and the success/failure of fault section separation are performed. Simulation results indicate that the power supply on the original feeder can be maintained by proposed method.

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“…In [17], a Slantlet transform in combination with Ridgelet probabilistic neural network was presented to detect grid faults in a grid-tied photovoltaic system. Wavelet singular entropy theory in combination with fuzzy logic was proposed to detect faults in a multiple distributed generation (DG) system [18]. In [19], a methodology based on probabilistic neural network and wavelet packet transform was presented to predict and classify grid faults in a PV system.…”

Section: Introductionmentioning

confidence: 99%

A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine

et al. 2019

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A new protection scheme based on applying a combination of wavelet multi-resolution singular spectrum entropy and support vector machine is proposed to identify different types of grid faults in a three-phase grid-tied photovoltaic system. In this technique, discrete wavelet transform with multi-resolution singular spectrum entropy is utilized to extract the unique features of three-phase voltage signals at the point of common coupling. The three-phase voltage signals are decomposed to provide detail and approximation coefficients of wavelet transform. Then, various features between different types of grid faults can be extracted by a combination of multi resolution analysis and spectrum analysis with entropy as the output. The constructed features vector is utilized as input data of a support vector machine classifier to identify and classify various types of faults. The results illustrate that the proposed intelligent technique not only recognizes different types of grid faults correctly, but also performs quickly in identifying grid faults in a grid-connected photovoltaic system. Apart from this, a graphical investigation is executed to observe the effects of different types of grid faults in photovoltaic (PV) operation which highlight the necessity of intelligent protection methods to protect PV systems.

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Fast fault detection and classification based on a combination of wavelet singular entropy theory and fuzzy logic in distribution lines in the presence of distributed generations

Cited by 155 publications

References 27 publications

A review of single phase adaptive auto-reclosing schemes for EHV transmission lines

A review of single phase adaptive auto-reclosing schemes for EHV transmission lines

New Protection Scheme Based on Coordination with Tie Switch in an Open-Loop Microgrid

A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine

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