The objective of TRUSTPV is to reach a demonstrated increase in performance and reliability of solar PV components (through O&M-friendly PV module design, robust reliable inverter solutions, aftermarket coatings), solar PV systems (disruptive engineering concepts, accurate design, construction, operation, repowering and decommissioning), and in large portfolios of distributed and utility-scale solar PV (digital twins, advanced forecasting, statistical analysis). The TRUSTPV results will be tested and demonstrated from fab to field and all data gathered along the value chain will flow into a decision support system platform with enhanced decision-making using AI based on and beyond Industry 4.0 concepts.
To increase the reliability and lifetime of systems components by reducing the number of failures and failure lifetime.
To increase the knowledge on the performance and establish cost-effective fault diagnostic models of medium-size commercial-residential systems.
To increase the design accuracy and the reliability and performance of utility-scale and large commercial solar PV systems through the use of advances and automated functions for data analysis, diagnosis and fault detection.
To allow higher solar PV penetration levels by improving the operational stability at the point of connection and ensure grid friendliness.
To combine all the information coming from various stakeholders along the whole PV value chain into a platform for enhanced decision-making using Artificial Intelligence (AI) and the invaluable human field experience.
To increase the sustainability of utility-scale and large commercial systems through progressive repowering interventions to reduce environmental impact and guarantee yield for an extended lifetime.
LAYER 1 | COMPONENTS
O&M and grid-friendly solar PV components.
Application and climate-tailored testing beyond existing standards
Context-sensitive PV plant components benchmarking based on monitoring data from over 6 GW of PV plants under operation and Big Data analytics.
LAYER 2 | system
More accurate energy yield prediction for PV systems with novel technologies and system layout.
Augmented Reality for improved skills of O&M operators and disruptive concepts for PV systems engineering.
Wireless Sensor Networks using Narrowband Internet of Things (IoT) and 5G
technology for on-site sensors such as energy meters for combined AI – physics based diagnostic
Automated fault diagnostic based on combined image analysis (PL/IR/EL/UV) and
Large database for failure rates calculation, mitigation measures and failure rate reduction functional to a fully integrated CPN methodology including grid and novel PV plant design
Decision support platform from fab to field
LAYER 3 – Point of connection / solar PV fleet