DOCTOR PV
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Description and objectives
DOCTOR-PV will lay the foundation for the implementation of optimal predictive maintenance and operation for different types of PV plants.
The project combines the two most promising techniques related to predictive maintenance: condition-based maintenance of all plant elements and maintenance based on electroluminescence (EL) and infrared thermography (TIR) measurements which are intended to be implemented by drone flights.
Value proposition
DOCTOR-PV's main objective is the optimization and maintenance of photovoltaic plants through the development of advanced tools and the application of machine learning techniques that allow: automatic inspections of the state of the plants, predictive maintenance of the main components and improvement of the operation. The main objective will be achieved through the following developments:
- Predictive maintenance algorithms.
- An optimal monitoring system.
- A polarization system for EL measurements.
- An EL and TIR measurement equipment supported by drone.
- Algorithms for detecting board failures using EL and TIR techniques.
- A methodology for optimal maintenance and operation of a photovoltaic installation.
CIRCE, given its experience in the management of R+D+i projects, will assume the technical direction together with MAETEL.
In addition, it will work mainly in the development of predictive maintenance algorithms and in the identification of the monitoring intensity level of new plants, reducing costs and ensuring the committed performance.
It will also participate in the integration of EL and TIR techniques in the same methodology, DOCTORPV, which will be validated in pilot projects.
Project partners
MAETEL, Gas Natural Fenosa Engineering, Iberdrola Renovables, PARIVER, Visiona, la Universidad Pública de Navarra, la Universidad de Valladolid y CIRCE.