A logistic-Lasso-regression-based seismic fragility analysis method for electrical equipment considering structural and seismic parameter uncertainty

Abstract

Damage to electrical equipment in an earthquake can lead to power outage of power systems. Seismic fragility analysis is a common method to assess the seismic reliability of electrical equipment. To further guarantee the efficiency of analysis, multi-source uncertainties including the structure itself and seismic excitation need to be considered. A method for seismic fragility analysis that reflects structural and seismic parameter uncertainty was developed in this study. The proposed method used a random sampling method based on Latin hypercube sampling (LHS) to account for the structure parameter uncertainty and the group structure characteristics of electrical equipment. Then, logistic Lasso regression (LLR) was used to find the seismic fragility surface based on double ground motion intensity measures (IM). The seismic fragility based on the finite element model of an ±1000 kV main transformer (UHVMT) was analyzed using the proposed method. The results show that the seismic fragility function obtained by this method can be used to construct the relationship between the uncertainty parameters and the failure probability. The seismic fragility surface did not only provide the probabilities of seismic damage states under different IMs, but also had better stability than the fragility curve. Furthermore, the sensitivity analysis of the structural parameters revealed that the elastic module of the bushing and the height of the high-voltage bushing may have a greater influence.