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

Authors : Mohamed HASSAN ALI, Aamir MEHMOOD

Pages : 673-680

Doi:10.2339/politeknik.587253

View : 40 | Download : 12

Publication Date : 2021-06-01

Article Type : Research Paper

Abstract :This article proposes a prognostic and diagnostic coupling framework based on the OSA-CBM insert ignore into journalissuearticles values(Open System Architecture for Condition Based Maintenance); for photovoltaic generators insert ignore into journalissuearticles values(PVG);. At First, this work presents some PVGs performance degradation studies and the main degradation indicators. We select the Corrected performance ratio insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(PEDS);, Integrated Predictive Maintenance Systems insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(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

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