Dynamic Transmission Reliability Margin Assessment Using Rolling Window Statistical Analysis for Enhanced Available Transfer Capability

This paper presents a dynamic approach to Transmission Reliability Margin (TRM) estimation, addressing challenges from load variability and uncertainties in modern power systems. Traditional methods use static confidence factors, often leading to inaccuracies. Using 24-hour real-world load profiles from the New Zealand electricity grid, a time-series rolling window analysis with hourly updates captures real-time load fluctuations. The framework dynamically optimizes the confidence factor based on recent load behavior, ensuring adaptive TRM values. Integrating these values into Available Transfer Capability (ATC) calculations enhances precision, improves transmission capacity utilization, and maintains reliability. Test scenarios show that this method mitigates over- and underestimation issues, supporting more dependable grid operations. This real-time TRM estimation framework offers a practical solution for modern power systems with high operational variability.