Prognostic and Diagnostic Coupling Framework Based on OSA-CBM strategy for Photovoltaic Generators

Abstract

This article proposes a prognostic and diagnostic coupling framework based on the OSA-CBM (Open System Architecture for Condition Based Maintenance) for photovoltaic generators (PVG). At First, this work presents some PVGs performance degradation studies and the main degradation indicators. We select the Corrected performance ratio (CPR) as degradation indicator associated with the Loess data analysis method to avoid aberrations and errors from acquisition system. Then, the main methods of coupling diagnostic and prognostic processes are explained: Watch Dog, Prognostic Enhancements to Diagnosis Systems (PEDS), Integrated Predictive Maintenance Systems (SIMP) and OSA-CBM. This last strategy with its seven specialized layers permits the interoperability of both processes. The monitoring system provides health indicators of PVGs and results are returned to human operator. The annual reduction rate of the CPR and reduction rate (Rd), allows us controlling the proposed coupling framework. This approach is validated with experimental data collected on four photovoltaic installations from the IEA PVPS Task13 database.

Keywords

• Framework
• prognostic
• diagnostic
• corrected performance ratio
• loess

References

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