Hurricane Fragility Assessment of Power Transmission Towers for a New Set of Performance-Based Limit States

Abstract

With the increasing reliance on the constant flow of electricity, risk-based management strategies are increasingly needed to ensure that with limited available resources, the grid can maintain high reliability and resilience. A growing concern in meeting this objective is the impact of climatic extremes, as the wide exposure of the power grid infrastructure has resulted in a system that is inherently vulnerable to extreme climatic hazards which are exacerbated by climate change. Analyzing the likelihood of damage induced by extreme hazards is critical for developing risk-informed strategies. Overhead structures, in particular, may experience a wide spectrum of damage types and degrees during hurricanes. Beyond the collapse state of transmission towers, which has been investigated in the past, non-collapse damage states in lattice towers require further attention as they can assist with performance-based design, grid recovery planning, and hardening decisions in preparation for extreme events. The present study establishes a set of performance-based limit states for lattice transmission towers subject to wind-induced extreme loadings. Specifically, five damage states including no damage, slight, moderate, and extensive damage, and collapse are defined. These limit states are founded on the nonlinear behavior of lattice towers and the type and severity of failures in tower elements and connections, as they relate to the repair or replacement requirements of towers. Focusing on a double circuit vertical steel lattice transmission tower as a case study, the proposed limit states are evaluated by generating a large number of random realizations of a diverse set of uncertain variables including those related to wind pressure and material properties using Latin Hypercube sampling method. The generated realizations are used in a set of nonlinear pushover analyses to investigate the performance of the tower at various loading levels. Subsequently, multi-state fragility functions are developed via logistic regression. These fragility models constitute a key step toward reliable extreme wind hazard risk assessment of the transmission grid and can assist with risk-informed decision-making in support of a resilient power grid.