We welcome collaboration on data monitoring and analytics. We offer free data analytics in exchange for monitoring data, which allows us to further develop and validation our novel modelling toolboxes.
SERENDI-PV is currently developing advanced data analytics procedures for the monitored PV data. The main technical objectives are:
1. to develop and integrate in commercial solutions advanced and automated functions for data
analysis, diagnosis and fault diagnosis at PV plant level in both:
a) Utility-large commercial scale PV plants from SCADA monitoring data, including higher
granularity of condition monitoring and specific data analytics for bifacial and floating PV.
b) Medium-size commercial and small-residential scale PV plants from energy meter
measurement data and through the development of a BIPV system digital twin.
2. to develop advanced digital twins for predictive maintenance of the components with the highest
complexity, uncertainty and impact on system reliability in current PV plants: inverter and batteries.
These developments aim to contribute to LCOE reduction through the progress on O&M:
• It will reduce supervision, inspection and preventive labour costs resulting in 20% OPEX reduction.
• It will increase main energy KPIs as Performance Ratio (PR) and Energy Availability.
These new data analytics will also contribute to grid integration by means of:
• A better knowledge about real performance and degradation processes will improve PV predictability
required for grid operation.
• A predictive maintenance of critical components will improve PV reliability avoiding grid
The overall objective of this collaborative work is the failure detection and diagnosis at system and component level:
• At system level developing and integrating in commercial solutions automated early fault detection
and diagnosis toolboxes based on:
o Analysis of energy meter measurements in commercial and residential PV systems.
o Development of a digital twin of BIPV systems.
o Analysis of complementary data including SCADA monitoring with different granularity
levels, testing campaigns, and specific data analytics for bifacial and floating.
• At component level developing advanced digital twins for predictive maintenance of the
components with the highest complexity, uncertainty and impact on system reliability:
o PV inverter
o Energy Storage System (ESS)
How to collaborate:
- We are looking for operational data from PV systems of all sizes to further develop and validate our data analytics toolboxes on a wide range of PV system typologies and operating conditions. If you possess interesting monitoring data, we would welcome a collaboration. This collaboration could include the data sharing, as well as collaboration on the development of the data analytics procedures. The results from these newly developed protocols could be shared with the data owners, and the results from collaboration on model development could produce joint scientific publications.
- We will also release some beta or demo versions of our data analytics toolboxes. If you are a PV asset owner or operation and if you would like to play the role of beta tester for these new software solutions, please contact us. You will be among to first to be informed about the latest developments happening at SERENDI-PV and with other collaborators from the PV community.