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The increasing size, aging equipment, and complexity of power systems, coupled with present day financial constraints, have made the use of probabilistic methods and reliability indices a necessity for maintaining continuity and quality of service to customers. Proper maintenance-related decisions should address all of these issues to improve system reliability while meeting limited budget constraints. This paper proposes algorithms that enable system-level reliability assessment with detailed modeling of maintenance for aging equipment. Stochastic-based reliability modeling of substations with aging equipment is presented, which enables the study of equipment aging, failures, and maintenance and their effect on substation-level availability and frequency of failure. Several case studies are provided which describe optimization of maintenance activities and the impact on maximum substation reliability. The algorithms provide a valuable tool for processing detailed models of aging equipment and maintenance of individual pieces in system reliability assessment applications. These algorithms are consistent with existing reliability models and are capable of being integrated into utility asset-management programs.