1C4PV is an industry-driven demonstration project that will contribute to achieve the reduction of the total costs of photovoltaic (PV) generation and the Levelized Cost of Electricity (LCoE), providing advanced and automated functions for data analysis for the early fault diagnosis (detection and classification) and maintenance planning for PV assets.

Those functions will be part of a cloud platform that collects data from the Supervisory Control and Data Acquisition (SCADA), Internet of Things (IoT), sensors and information systems, such as maintenance management or inspections and facilitates the decision making for optimum Operations and Maintenance (O&M). Machine learning algorithms and other Artificial Intelligence techniques are the back-bone of early and reliable fault diagnosis.

The working plan includes the standardization of a prototype solution, the testing phase in laboratory and the demonstration in real operating environment. The plan covers the following technical actions: analyze technologies and application, modeling PV plants and data characterization for multiple topologies, algorithms development for problem diagnosis and maintenance decision support systems.

As a result, 1C4PV will face the main challenges of the PV industry (LCoE reduction) through the optimization of O&M processes in PV plants while maximizing production using the available resources.

To achieve the project’s objectives, the partners will bring on board their extensive experience and expertise in the field, starting the project from a leading position.

Isotrol (Spain), Tegnatia (Turkey) and Research Centre for PV generation optimization (FOSS, UCY, Cyprus)

Execution period: 2020 – 2022

Project Web site


Project 1C4PV is supported under the umbrella of SOLAR-ERA.NET Cofund 2 by the Center for Industrial Technological Development (CDTI) in Spain, the Scientific and Technological Research Council of Turkey (TUBITAK) and the Research and Innovation Foundation in Cyprus. SOLAR-ERA.NET is supported by the European Commission within the EU Framework Programme for Research and Innovation HORIZON 2020 (Cofund ERA-NET Action, N° 786483).