Overload Risk Assessment of Transmission Lines Considering Dynamic Line Rating

Abstract

Dynamic line rating (DLR) technology dynamically adjusts the current-carrying capacity of transmission lines based on real-time environmental parameters and plays a critical role in maximizing line utilization, alleviating power flow congestion, and enhancing the security and economic efficiency of power systems. However, the strong coupling between the dynamic capacity and environmental conditions increases the system’s sensitivity to multiple uncertainties and causes complications in the overload risk assessment. Furthermore, conventional evaluation methods struggle to meet the minute-level risk refresh requirements in ultrashort-term forecasting scenarios. To address these challenges, in this study, an analytical overload risk assessment framework is proposed based on the second-order reliability method (SORM). By transforming multidimensional probabilistic integrals into analytical computations and establishing a multiscenario stochastic analysis model, the framework comprehensively accounts for uncertainties such as component random failures, wind power fluctuations, and load variations and enables the accurate evaluation of the overload probabilities under complex environmental conditions with DLR implementation. The results from this study provide a robust theoretical foundation for secure power system dispatch and optimization using multiscenario coupled modeling. The effectiveness of the proposed methodology is validated using case studies on a constructed test system.