DOCTOR PV

Relevant project information

Dates

July 2018 - December 2021

Project website

Project completed

Role of CIRCE

Partner

Grant agreement number

RTC-2017-6712-3

Funded by

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.

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Technical

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Customization cookies allow us to remember your preferences, to customize certain characteristics and general options of our website to your liking each time you access it (for example, the language in which information is presented to you, sections marked as favorites, your type of browser, etc).

Therefore, these cookies do not have an advertising purpose, but by activating them, you will improve the functionality of the website (for example, adapting it to your type of browser) and its customization based on your preferences (for example, presenting information in the language you have chosen on previous occasions), which will contribute to the ease, usability, and convenience of our website during your navigation.

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Analysis cookies allow us to study the navigation of users of our website in general (for example, which sections of the website are the most visited, which services are used more and if they work correctly, etc.).

Based on statistical information about navigation on our website, we can improve both the operation of the website itself and the various services it offers. Therefore, these cookies do not have an advertising purpose, but only serve to make our website work better, adapting it to our users in general. By activating them, you will contribute to this continuous improvement.

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Relevant project information

Description and objectives

Value proposition

Project partners

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