Fault Signal Formulation for Fault Analysis in DC Microgrid

With increasing demand of electricity and depleting non-renewable resources, the rising demand of energy is fulfilled by renewable energy sources (RES). Microgrids in power system integrate various RES, convectional grid and various type of loads. This leads to the progressing interests of scholars towards DC Microgrids (DCMG). Power system control, energy management, fault analysis, power quality and reliability are major area of concern in DCMG as these are extremely significant in power distribution sector. Study on various methods for Fault Diagnosis are being carried out by identifying different type of Fault Signatures. This paper focuses on extracting harmonics from inductor voltage during faults at various locations within the DCMG system and identifying the fault type and location based on the harmonic signatures.

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Published
2024-12-18
DOI
https://doi.org/10.1109/pedes61459.2024.10961767
Primary Topic
Power Systems Fault Detection
Type
article
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Fault Signal Formulation for Fault Analysis in DC Microgrid

Venkata R. Vakacharla, Narsa Reddy Tummuru, Aditi Thakur
Power Systems Fault Detection
article

Fault Signal Formulation for Fault Analysis in DC Microgrid

Venkata R. Vakacharla, Narsa Reddy Tummuru, Aditi Thakur
article en

Abstract

With increasing demand of electricity and depleting non-renewable resources, the rising demand of energy is fulfilled by renewable energy sources (RES). Microgrids in power system integrate various RES, convectional grid and various type of loads. This leads to the progressing interests of scholars towards DC Microgrids (DCMG). Power system control, energy management, fault analysis, power quality and reliability are major area of concern in DCMG as these are extremely significant in power distribution sector. Study on various methods for Fault Diagnosis are being carried out by identifying different type of Fault Signatures. This paper focuses on extracting harmonics from inductor voltage during faults at various locations within the DCMG system and identifying the fault type and location based on the harmonic signatures.

Indian Institute of Technology Mandi (IN)
Climate action
Openalex Percentile: Top 63%
Power Systems Fault Detection
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