TITLE: Sensor Driven Condition Based Maintenance Models for Generator Fleets

ABSTRACT:

We provide a framework that links low-level performance and condition monitoring data with high-level operational and maintenance decisions for generators. The operational decisions identify the optimal commitment and dispatch to satisfy demand and transmission constraints. Maintenance decisions focus on arriving at an optimal condition based maintenance (CBM) schedule that accounts for optimal asset-specific CBM schedules driven by the condition monitoring data. We propose new mixed-integer optimization models and efficient algorithms that exploit the special structure of the proposed formulation. We present extensive computational experiment results to show proposed models achieve significant improvements in cost and reliability. This is a joint work with Andy Sun and Nagi Gebraeel.