An Adaptive Injection-Based Protection Method for Distribution Networks Considering Impacts of High-Penetration Distributed Generation

Driven by the goal of sustainable energy transitions, the integration of Inverter-Interfaced Distributed Generation (IIDG) has led to a continuous decline in the accuracy of single-phase grounding fault line selection in neutral non-effectively grounded distribution networks. Protection methods based on characteristic signal injection currently struggle to balance the differentiated requirements of fault detection sensitivity and equipment safety in networks with high-penetration IIDG. To address this issue, a high-frequency equivalent circuit model of the IIDG is established. The distribution patterns of the high-frequency characteristic current (HFCC) in distribution networks under high-penetration IIDG are analyzed. Subsequently, an adaptive HFCC injection strategy is proposed, which accounts for IIDG low-voltage ride-through (LVRT) requirements, fault identification sensitivity, and equipment safety constraints. Based on the amplitude and phase differences in the HFCC between faulty and healthy feeders, a fault line selection criterion is established. Consequently, an adaptive injection-based protection method for single-phase grounding fault is developed, considering the impact of high-penetration IIDG. Simulation results demonstrate that the proposed method accurately identifies the faulty feeder under various fault locations, transition resistances, and quantities of integrated IIDG units. The results further confirm the high adaptability and reliability of the method, thereby providing a robust technical foundation for the safe, reliable, and sustainable operation of modern power grids.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-03-14
DOI
https://doi.org/10.3390/su18062863
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Adaptive Injection-Based Protection Method for Distribution Networks Considering Impacts of High-Penetration Distributed Generation

YanBo Diao, Zixin Li, Shoudong Xu, Jinxin Ouyang
Sustainability
Power Systems Fault Detection
article

An Adaptive Injection-Based Protection Method for Distribution Networks Considering Impacts of High-Penetration Distributed Generation

YanBo Diao, Zixin Li, Shoudong Xu, Jinxin Ouyang
article en

Abstract

Driven by the goal of sustainable energy transitions, the integration of Inverter-Interfaced Distributed Generation (IIDG) has led to a continuous decline in the accuracy of single-phase grounding fault line selection in neutral non-effectively grounded distribution networks. Protection methods based on characteristic signal injection currently struggle to balance the differentiated requirements of fault detection sensitivity and equipment safety in networks with high-penetration IIDG. To address this issue, a high-frequency equivalent circuit model of the IIDG is established. The distribution patterns of the high-frequency characteristic current (HFCC) in distribution networks under high-penetration IIDG are analyzed. Subsequently, an adaptive HFCC injection strategy is proposed, which accounts for IIDG low-voltage ride-through (LVRT) requirements, fault identification sensitivity, and equipment safety constraints. Based on the amplitude and phase differences in the HFCC between faulty and healthy feeders, a fault line selection criterion is established. Consequently, an adaptive injection-based protection method for single-phase grounding fault is developed, considering the impact of high-penetration IIDG. Simulation results demonstrate that the proposed method accurately identifies the faulty feeder under various fault locations, transition resistances, and quantities of integrated IIDG units. The results further confirm the high adaptability and reliability of the method, thereby providing a robust technical foundation for the safe, reliable, and sustainable operation of modern power grids.

SustainabilityVol. 18(6)
Chongqing University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 21%
Power Systems Fault Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.