Subset Simulation–Based Reliability Assessment of Integrated Electricity and Gas System

ABSTRACT

The difference in time constants between electric power systems and natural gas networks poses a fundamental challenge to the reliability assessment of integrated electricity and gas systems (IEGS). While steady‐state approximations fail to capture critical buffering effects, dynamic solvers often suffer from computational intractability and numerical instability under discontinuous fault conditions, hindering further reliability assessment. To resolve this, this paper presents a reliability assessment framework that integrates high‐accuracy dynamic modelling and efficient simulation. We first introduce an approximate analytical method (AAM) that overcomes the limitations of traditional spatial discretisation by solving nonlinear partial differential‐algebraic equations of the IEGS. By coupling this solver with subset simulation (SS), the proposed approach effectively overcomes the curse of dimensionality, allowing for the rapid and statistically accurate estimation of failure events in the IEGS. Case studies verified the superiority of the AAM over discretisation‐based numerical methods and highlighted the efficiency advantages of the SS algorithm for reliability assessment.