Abstract
Power electronic converters are one of failure sources in energy systems, and hence drivers of downtime costs in power systems. Different approaches can be employed for converter reliability enhancement including design/control for reliability methods, condition monitoring and fault diagnosis, and maintenance strategies. This paper proposes optimal preventive maintenance strategies based on wear-out failure model of converter components. The proposed approaches employ two different performance measures at converter-level and system-level. The converter-level measures take into account planned and unplanned maintenance times or costs in a single unit or small-scale system. Moreover, the system-level measure considers not only maintenance times, but also energy losses and additional maintenance costs induced by aging of the converter components. The outcome is optimal replacement time of converter and its components, which depends on the employed performance measure. Optimal replacement scheduling is of importance for risk management and decision-making during planning of modern power electronic based power systems. The applicability of the proposed approaches is illustrated by numerical analysis in a photovoltaic system.
Highlights
Power electronic converters are increasingly used in power systems in a wide range of applications
Reliability of power electronic converters is of paramount importance for economic planning and operation of power systems
The outcome is an optimal replacement time for the converter and its components based on their aging reliability model and the performance measure
Summary
Power electronic converters are increasingly used in power systems in a wide range of applications. This paper proposes a model-based preventive maintenance scheduling for converters considering aging failure of their components operating under a given mission profile. The outcome is an optimal replacement time for the converter and its components based on their aging reliability model and the performance measure. Following this approach, the converter wear-out failure probability can be predicted by a stress-strength analysis considering the physics of failures of fragile components. According to this approach, using the reliability model based on mission profile analysis will introduce more accurate estimation of replacement time of converter components. - Historical failure data - Add itio nal ma inte nance costs - Ene rgy interru ptio n costs
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