Chadni, Farabi Hasan and Hossain, Md Shahdat (2023) Advanced Fault Analysis and Protection Strategies for Distribution Grids with High Renewable Energy Penetration. International Journal on Orange Technologies, 5 (8). pp. 139-148. ISSN 2615-8140

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Abstract

Background: The speed of renewable energy source implementation into distribution networks has brought about major changes which now affect both power system management. The growing number of distributed generation units now produces two-way power movement which creates unpredictable fault currents that disrupt standard protection system operations. Methods: The research employs a quantitative cross-sectional survey approach which analyzes responses from 265 participants work as engineers and researchers and grid operators and academicians and industry experts. The study gathered data through a structured questionnaire which focused on fault behavior and protection obstacles and technology recognition. Pearson correlation analysis to study the connections between major factors which consisted of fault complexity and adaptive protection and smart grid integration. Results: The analysis shows that line-to-ground faults account for 32.1%, followed by line-to-line faults (20.8%) and double line faults (15.1%). The system experiences bidirectional power flow as its primary operational challenge which affects 26.4% of users while 20.8% face power system challenges because of renewable power source fluctuations. Traditional protection systems receive a moderate effectiveness rating from 30.2% of survey participants. The correlation analysis shows adaptive protection systems achieve their highest positive correlation with grid reliability at 0.68 followed by smart grid integration at 0.63 but fault complexity produces a negative correlation of -0.45. Conclusion: The study demonstrates that renewable energy adoption creates major changes to distribution system protection when operating at the same time. Advanced adaptive protection systems together with intelligent systems to achieve better reliability and maintain stable system operation.

Item Type:	Article
Subjects:	A General Works > AI Indexes (General)
Depositing User:	admin eprints
Date Deposited:	28 Jun 2026 23:30
Last Modified:	28 Jun 2026 23:30
URI:	http://eprints.umsida.ac.id/id/eprint/16661

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