Reliability Modeling and Analysis of Main‐Auxiliary Systems Considering Performance Sharing

ABSTRACT Driven by technological advances, main‐auxiliary systems consisting of main and auxiliary components have attracted increasing attention. Unlike traditional systems where components function equally, main components provide basic performance supply while auxiliary components provide additional support, making reliability analysis more challenging. However, existing studies largely focus on reliability assessment under fixed configurations, while adaptive reliability enhancement through auxiliary support and performance sharing remains insufficiently investigated. To address this issue, this paper investigates a star‐topology main‐auxiliary system with performance sharing mechanism. The system consists of a central station and terminal subsystems. Each subsystem includes one main component and multiple heterogeneous auxiliary components. Considering stochastic demands under multiple operating conditions, different types of auxiliary components are dynamically activated according to the demand requirements of each condition. Subsystems with surplus performance transfer excess to the central station for redistribution to deficient subsystems. A reliability evaluation model based on the universal generating function (UGF) is developed, and a genetic algorithm is used to optimize auxiliary component configuration. The proposed model is validated through a power system example.