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    Artificial Intelligence
    for Operation and
    Maintenance of PV Plants
    Find out more
    AI4PV digital solutions will contribute to increase the operational performance of
    photovoltaic (PV) power plants through the combination of Digital Twin,
    physics-informed machine learning and decision-aid tools that optimize operation and maintenance (O&M) tasks.
    AI4PV digital solutions will contribute to increase the operational performance of
    photovoltaic (PV) power plants through the combination of Digital Twin,
    physics-informed machine learning and decision-aid tools that optimize operation and maintenance (O&M) tasks.

    PROJECT INNOVATIONS AND SOLUTIONS

    Main objectives

    Increasing the operational reliability and efficiency at PV power plants

    High accuracy of early detection of faults and degradation problems and optimization of O&M activities.

    Enhance economic performance

    Reduction of downtimes of elements, detection of underperformance problems that can affect the energy production.

    PROJECT INNOVATIONS AND SOLUTIONS

    Digital Solutions

    Business Target 1
    Increase PV Plant reliability through development and validation of models, simulation tools and AI-based data analysis for fault prediction and detection

    Early fault detection tools, for critical elements of PV plant, through advanced monitoring, automated data analysis and comparison with model-generated values.

    Business Target 2
    Optimize PV Plant generation technical and economic performance

    Underperformance and degradation problems at PV plants can lead to a loss of production, but usually they don´t trigger an alarm so that the O&M or the Asset Management teams start a correction action. This way they are usually unnoticed until they get to a certain level, but meanwhile there has been loss of energy production during months. The objective is to detect this at early stages through advanced data analysis from Scada and sensor data.

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    This website has been developed with the support of the ERDF - European Regional Development Fund - through the Operational Programme for Competitiveness and Internationalisation COMPETE 2020 under the Portugal 2020 Partnership Agreement within project AI4PV, with reference POCI-01-0247-FEDER-111936.

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