Adaptive Sampled Value Differential Protection With High Penetration of Inverter-Based Resource Based on Error Function Fitting

As power systems continue to evolve and modernize, the integration level of renewable energy sources in distribution grids has been steadily increasing. Traditional protection schemes in distribution grids, such as directional current protection, are influenced by the fault characteristics of inverters, posing challenges such as fault current limiting and frequency deviation. Moreover, the conventional phasor-based protection principles struggle to accurately characterize non-fundamental frequency fault currents. While Sampled Value Differential Protection (SVD) overcomes these limitations, it remains vulnerable to measurement errors under low-current conditions, compounded by the absence of industry standards for error handling. This issue leads to a lack of foundation for setting of SVD and hinders quantitative operation, maintenance, and testing. To address these gaps, this paper introduced an adaptive sampled value differential protection (ASVD) scheme. The proposed method utilized pre-fault steady-state current for time-domain error estimation, establishing a floating threshold to dynamically adjust protection characteristics. The effectiveness and reliability of this scheme were successfully verified through simulations. Compared to conventional differential protection methods, the ASVD scheme demonstrates adaptability, sensitivity and reliability to different operating conditions of high penetration inverter-based resource (HPIB). This promising approach provides a new solution to address the practical engineering challenges posed by the high integration of inverter-based resource into distribution grids.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3592952
Citations
1
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
1.21

Funders

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

Adaptive Sampled Value Differential Protection With High Penetration of Inverter-Based Resource Based on Error Function Fitting

Hao Wang, Bing Luo, Wei Chen, Xiaopeng Li et al.
1 citations
IEEE Access
Power Systems Fault Detection
1.21
article

Adaptive Sampled Value Differential Protection With High Penetration of Inverter-Based Resource Based on Error Function Fitting

Hao Wang, Bing Luo, Wei Chen, Xiaopeng Li, Zhaowei Zhou, Wei Zhou
article en
1 citations

Abstract

As power systems continue to evolve and modernize, the integration level of renewable energy sources in distribution grids has been steadily increasing. Traditional protection schemes in distribution grids, such as directional current protection, are influenced by the fault characteristics of inverters, posing challenges such as fault current limiting and frequency deviation. Moreover, the conventional phasor-based protection principles struggle to accurately characterize non-fundamental frequency fault currents. While Sampled Value Differential Protection (SVD) overcomes these limitations, it remains vulnerable to measurement errors under low-current conditions, compounded by the absence of industry standards for error handling. This issue leads to a lack of foundation for setting of SVD and hinders quantitative operation, maintenance, and testing. To address these gaps, this paper introduced an adaptive sampled value differential protection (ASVD) scheme. The proposed method utilized pre-fault steady-state current for time-domain error estimation, establishing a floating threshold to dynamically adjust protection characteristics. The effectiveness and reliability of this scheme were successfully verified through simulations. Compared to conventional differential protection methods, the ASVD scheme demonstrates adaptability, sensitivity and reliability to different operating conditions of high penetration inverter-based resource (HPIB). This promising approach provides a new solution to address the practical engineering challenges posed by the high integration of inverter-based resource into distribution grids.

IEEE AccessVol. 13
Huazhong University of Science and Technology (CN)
Science and Technology Project of State Grid
Openalex Percentile: Top 19%
Power Systems Fault Detection
1.21
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.