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Abstract
A new replacement analysis methodology is developed and demonstrated to determine system-level component replacement schedules for electricity distribution systems composed of sets of heterogeneous assets. The proposed model is an iterative combined dynamic programming and integer programming approach to obtain cost-efficient system-level component replacement schedules with the objective of minimizing the total net present value of unmet demand (considering the system availability), maintenance, and purchase costs over a finite planning horizon. There is an annual budget limiting total expenditures for maintenance and replacement costs that limits the selection of component replacement schedules.