Multi-Scenario and Stochastic Thermo-Electro-Mechanical Modeling of Failure in Power Transmission Lines

TL;DR

This paper presents a comprehensive thermo-electro-mechanical model for power transmission lines, incorporating stochastic analysis to evaluate failure risks under unpredictable environmental conditions like wildfire, ice, and high wind.

Contribution

It introduces a novel combined deterministic and stochastic modeling framework using phase field damage and probabilistic methods for transmission line failure analysis.

Findings

Temperature and damage evolution insights

Probabilistic failure risk assessments

Sensitivity analysis results

Abstract

Transmission lines, crucial to the power grid, are subjected to diverse environmental conditions such as wind, temperature, humidity, and pollution. While these conditions represent a consistent impact on the transmission lines, certain unpredictable conditions such as unexpected high wind, wildfire, and icing pose catastrophic risks to the reliability and integrity of the transmission lines. These factors in the presence of initial damage and electrical loads greatly affect the material properties. In this paper, we develop a comprehensive thermo-electro-mechanical model to investigate the long-term effect of unexpected high wind, wildfire, and ice on transmission lines. This study offers an in-depth perspective on temperature and damage evolution within the power lines by incorporating a phase field model for damage and fatigue, alongside thermal and electrical models. We define a state function to assess the failure, considering damage and temperature. We study three scenarios deterministically to establish a basic understanding and analyze the stochastic behavior using the Probabilistic Collocation Method (PCM). We utilize PCM for forward uncertainty quantification, conducting sensitivity analysis, and evaluating the probability of failure. This approach offers an in-depth examination of the potential risks associated with transmission lines under unfavorable circumstances.