Optimization Strategy for Condition-Based Maintenance of Aging Equipment Considering Service Life Retirement

Considering the prevalent issue of a high proportion of aging equipment within power grid enterprises, this manuscript delineates an advanced condition-based maintenance optimization strategy for such aged infrastructure. Initially, the study delves into the conventional methodology of assessing equipment failure rates, culminating in the formulation of a specialized failure rate regression model tailored for aging equipment. Subsequently, the analysis extends to the implications of comprehensive maintenance interventions on the economic viability of the equipment and the overall reliability of the power systems. The optimization endeavor seeks to harmonize the economic and reliability considerations, thereby enhancing the operational efficiency and system dependability. The discourse further evolves by identifying maintenance scheduling and methodologies for aging equipment as pivotal optimization variables. A sophisticated condition-based maintenance optimization framework is developed, targeting the reduction of cumulative costs while conforming to established maintenance quality benchmarks as constraints. The resolution of the proposed framework is achieved through the deployment of a particle swarm optimization algorithm. The utility and effectiveness of the proposed optimization strategy are substantiated through a case study focusing on transformer units within a regional distribution network.