Assessment of Transmission Reliability Margin: Existing Methods and Challenges and Future Prospects

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation fluctuations, and network dynamics. The traditional deterministic TRM methods often fail to capture the stochastic nature of modern grids, leading to inaccurate estimations. This paper reviews the TRM assessment methodologies, emphasizing probabilistic approaches that enhance accuracy in high-RES environments. It explores adaptive statistical techniques, such as rolling window analysis, for dynamic TRM computation. Key challenges, emerging trends, and potential solutions are discussed to support the development of robust ATC modeling frameworks for secure and efficient renewable energy integration.

Authors

Institutions

Publication Details

Journal
Energies
Published
2025-04-29
DOI
https://doi.org/10.3390/en18092267
Primary Topic
Power System Reliability and Maintenance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of Transmission Reliability Margin: Existing Methods and Challenges and Future Prospects

M. A. Mahmud, Tek Tjing Lie, Uchenna Emmanuel Edeh
1 links
Energies
Power System Reliability and Maintenance
article

Assessment of Transmission Reliability Margin: Existing Methods and Challenges and Future Prospects

M. A. Mahmud, Tek Tjing Lie, Uchenna Emmanuel Edeh
article en

Abstract

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation fluctuations, and network dynamics. The traditional deterministic TRM methods often fail to capture the stochastic nature of modern grids, leading to inaccurate estimations. This paper reviews the TRM assessment methodologies, emphasizing probabilistic approaches that enhance accuracy in high-RES environments. It explores adaptive statistical techniques, such as rolling window analysis, for dynamic TRM computation. Key challenges, emerging trends, and potential solutions are discussed to support the development of robust ATC modeling frameworks for secure and efficient renewable energy integration.

EnergiesVol. 18(9)
Flinders University (AU), Auckland University of Technology (NZ)
Openalex Percentile: Top 90%
Power System Reliability and Maintenance
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.