for Operation and
Maintenance of PV Plants
the latest news about the project
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.
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
Solution 1.1
Early fault detection tools, for critical elements of PV plant, through advanced monitoring, automated data analysis and comparison with model-generated values.
Solution 1.2
Predictive maintenance tools for increased reliability by optimizing the O&M tasks and procedures through an AI based recommendation engine tasks based on the impact of failures or underperformance.
Business Target 2
Optimize PV Plant generation technical and economic performance
Solution 2.1
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.
Solution 2.2
Root cause analysis for prescriptive maintenance tools: based on faults/failures and trend based losses detection, the objective is to translate it into actions from the O&M teams, prioritizing them with a ROI-based action plan.
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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.
