Superimposed modal voltage based passive islanding detection of grid tied distributed generation using Wigner distribution function

The integration of distributed generation (DG) into modern electric grids has garnered considerable interest due to its potential to enhance energy resiliency, reduce carbon emissions, and improve security. However, a critical challenge arises in the form of unintentional islanding. Islanding refers to a situation when DG systems, disconnected from the main network, continue supplying nearby loads. Such events pose risks to grid stability by resulting in deviations in voltage and frequency levels, equipment damage, and network safety. To address these challenges, this study introduces a novel approach for detecting islanding events in grid-tied DG systems using Wigner distribution functions and alienation index. First, a modal voltage signal is extracted from three-phase voltage measurements. Next, delta filters capture superimposed components of modal voltage. An islanding detection index (IDI) is then developed by utilising the Wigner distribution and alienation coefficient to effectively characterize islanding signatures. Finally, the IDI is evaluated against a predetermined threshold to differentiate islanding events from non-islanding conditions. Simulations are performed in MATLAB/SIMULINK on a standard IEC microgrid to validate the effectiveness of the proposed method. The results show superior performance over traditional techniques in speed, accuracy, and non-detection zones.

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Publication Details

Journal
Scientific Reports
Published
2025-08-05
DOI
https://doi.org/10.1038/s41598-025-13244-4
Citations
1
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
0.73
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article

Superimposed modal voltage based passive islanding detection of grid tied distributed generation using Wigner distribution function

Hani A. Albalawi, Aadel M. Alatwi, Syed Basit Ali Bukhari, Abdul Wadood
1 citations
Scientific Reports
Islanding Detection in Power Systems
0.73
article

Superimposed modal voltage based passive islanding detection of grid tied distributed generation using Wigner distribution function

Hani A. Albalawi, Aadel M. Alatwi, Syed Basit Ali Bukhari, Abdul Wadood
article en
1 citations

Abstract

The integration of distributed generation (DG) into modern electric grids has garnered considerable interest due to its potential to enhance energy resiliency, reduce carbon emissions, and improve security. However, a critical challenge arises in the form of unintentional islanding. Islanding refers to a situation when DG systems, disconnected from the main network, continue supplying nearby loads. Such events pose risks to grid stability by resulting in deviations in voltage and frequency levels, equipment damage, and network safety. To address these challenges, this study introduces a novel approach for detecting islanding events in grid-tied DG systems using Wigner distribution functions and alienation index. First, a modal voltage signal is extracted from three-phase voltage measurements. Next, delta filters capture superimposed components of modal voltage. An islanding detection index (IDI) is then developed by utilising the Wigner distribution and alienation coefficient to effectively characterize islanding signatures. Finally, the IDI is evaluated against a predetermined threshold to differentiate islanding events from non-islanding conditions. Simulations are performed in MATLAB/SIMULINK on a standard IEC microgrid to validate the effectiveness of the proposed method. The results show superior performance over traditional techniques in speed, accuracy, and non-detection zones.

Scientific ReportsVol. 15(1)
University of Tabuk (SA)
Affordable and clean energy
Openalex Percentile: Top 25%
Islanding Detection in Power Systems
0.73
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Superimposed modal voltage based passive islanding detection of grid tied distributed generation using Wigner distribution function — Hani A. Albalawi, Aadel M. Alatwi, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS