IOM-PV

Summary:

A challenge in the scope of facilitating further the uptake of photovoltaic (PV) technology is the reduction of levelised cost of energy (LCOE) by increasing the lifetime output, quality and sustainability as targeted by the Solar Europe Industry Initiative (SEII SET-Plan). This can be achieved by improving the lifetime energy yield and operation and maintenance (O&M) costs through online data-driven and statistical algorithms that will enable the analysis of measurements collected from constant monitoring of PV plants. In this sense, a main challenge for ensuring quality of PV power plant operation is to safeguard reliability and optimum performance by detecting, classifying and accurately quantifying performance losses and failures.

This project has been initiated to overcome these challenges by developing and commercializing a product that will enable preventive and predictive maintenance and ensure optimal PV plant performance while reducing costs associated to O&M. This will be achieved through the development of a cloud-based solution that will host innovative algorithms able to a) ensure data quality and b) allow failure and performance loss diagnosis (open- and short-circuit failures, inverter and bypass diode faults, shading, degradation, soiling, etc.) without disrupting the normal operation of the PV plant. The methodology will be primarily based on real-time analysis of measurement data, machine learning and statistical analysis and will be verified experimentally against field measurements from existing PV systems installed at the Universities of Cyprus (UCY) and Jaén (UJA) and other PV plants from around the world, currently monitored by the industrial partner Alectris Hellas IKE.