Reducing the photovoltaic operation and maintenance costs through an autonomous control operation center

Abstract

An advanced control operation center to enable corrective, preventive and predictive maintenance, while also ensuring optimal photovoltaic (PV) plant performance was developed in this work. The developed software solution hosts innovative algorithms able to ensure data quality, while also allowing early failure and performance loss diagnosis without disrupting the normal operation of the PV plant. It is primarily based on real-time analysis of measurement data, machine learning and statistical analysis. The solution was validated experimentally against field measurements from an operating PV power plant of 1.8 MWp installed in Greece. The results showed technical availability and energy yield improvements of the test PV plant by handling intelligently the detected faults through the smart ticketing system. Optimal maintenance planning (e.g., optimum hardware replacement/maintenance, cleaning schedules, etc.) can thus lead to a reduction of operation and maintenance (O&M) costs and hence directly impacting positively the levelised cost of electricity (LCOE).