challenges & objectives of

the project

SERENDI-PV addresses two important challenges:

- To keep reducing the Levelized Cost of Energy (LCoE) for PV

- To make it possible to integrate a rapidly increasing share of PV power into the power networks, up to penetration levels of several dozens of percent

The objective of SERENDI-PV is to propose innovations on PV systems and their grid integration to improve:

- Lifetime, reliability, performance and profitability (including uncertainties) of PV generation;

- High-penetration of the PV generation in the grids with improved stability

Research & Development

the project's

R&D activities

SERENDI-PV project is addressing some of the main concerns which would enable the increase in the penetration of PV generated power on to the European grids. The project will address modelling, diagnostics and quality control.  

First, SERENDI-PV will provide higher accuracy of modelling for the new PV technologies (such as bifacial PV, floating PV and BIPV) allowing better energy yield assessments.

Second, the project will innovate in advanced fault diagnosis in PV plants, with special focus in fault diagnosis in the new technologies, and by using the predictive maintenance of the most complex components in PV system and with the highest impact on energy availability: PV inverter and batteries. This will be achieved by means of a better understanding of potential failures and aging processes of these components allowing to anticipate them.

Third, in addition to this, the better-quality controls in the field and in the lab will increase PV project’s quality & lifetime and reduce their performance uncertainty and improve bankability of the new PV technologies.

On the other hand, the project will address the technical challenges and opportunities that will come with the increase of the PV penetration in the grids. This will be managed, first, by means of improving PV power forecasting (mid-term, short-term and nowcasting) of the new PV technologies and in case of specific atmospheric events (snow, dust, frog). 

Second there will be the need for innovative monitoring and management of millions of distributed energy resources (PV plants) in order to maintain grid stability bringing in parallel the opportunity of additional revenues for PV (new business models). The PV data and the corresponding IT infrastructure will be utilized to develop and test several technical solutions to enable higher PV contribution and a utility friendly integration of it.


expected innovations

A selection of the innovations of the SERENDI-PV project:

Simulation, modelling and design for better PV reliability, performance and profitability. SERENDI-PV will tackle the new challenges of modelling on four aspects: losses and degradation modelling, new PV technology/configuration modelling (such as bifacial and floating), solar resource and uncertainties modelling, and financial risk modelling.

Monitoring and image-based fault diagnosis for higher PV performance and profitability. SERENDI-PV will develop solutions and services based on five technical approaches:

a) advanced fault diagnosis in large PV plants; b) fault diagnosis in new technologies (bifacial, floating); c) data analytics algorithms for diagnostics of medium/long trend processes  d) digital twins for predictive maintenance of the most complex components, such as inverters and batteries e) improved infrared thermography data analytics.

Quality Control (QC) equipment and procedures for PV components and systems reliability

To ensure an effective quality control throughout the whole supply chain, SERENDI-PV will develop instruments (testing equipment and procedures) for:
•    Laboratory facilities, providing indoor quality controls at the component level. SERENDI-PV will address two issues: a) soiling and cleaning on the one hand; b) PV module degradation and failures in the floating environment on the other hand.
•    Field testing toolboxes, providing outdoor quality controls at the component and system level. SERENDI-PV will address another two issues: c) soiling and d) PV strings ageing/degradation.
•    Quality control procedures for e) PV inverters and f) energy storage, providing a coherent frame to exploit field and laboratory testing. 

Further innovations:

Mid-term, short-term forecasting, and nowcasting for PV system aggregations. 

Collaborative platform for modelling, data analytics, QC, databases and grid integration.

Removing technical constraints for integrating large volumes of PV in the grids





the project's

Expected Impacts


Contribute to increasing the reliability of PV systems, by improving the knowledge of PV components’ and systems failure, providing better answers through operations and maintenance, developing virtual and digital twins at component level (inverters, batteries), and assessing the collective reliability of a PV fleet from a grid operators’ point of view.

Increase the real performances of PV systems by improving modelling tools for energy production forecasting and failure detection algorithms, especially for emerging applications such as the use of bifacial modules and floating PV systems.

Improve system management with high shares of PV electricity by allowing grid operators to get accurate data about the grid-connected PV fleet, energy production and service provision.

Accelerate the development of PV in Europe by improving a combination of technical and psychological factors improving its competitiveness, its ability to be seamlessly integrated into the distribution and transmission grids and to be dispatchable enough to increase its penetration in electricity grids, while providing ancillary services.

Increase the profitability of grid-connected PV systems by the reduction of some elements of the OPEX costs and influence indirectly the WACC.


demonstration activities

Simulation & Modelling, Data Analytics for O&M and On-Site Testing Equipment

Monitoring information for the project is being collected in operational conditions from heterogeneous portfolios of plants of different sizes. This data is used for the assessment of developed solutions in Simulation & Modelling for PV Systems and Components (WP2), Monitoring and Data Analytics for Fault Diagnosis and O&M (WP3) and On-Site Testing Equipment and Procedures for Quality Control (WP4). 

Monitoring information from large PV plants are taken from 3 different portfolios: 

  • PORTFOLIO 1 provided by AKUO and Compagnie Nationale du Rhone (CNR) for the development and demonstration of modelling and diagnostics of new PV applications (bifacial, floating and BIPV) and energy losses currently not well evaluated (soiling, snow and degradation) utilizing SCADA monitoring information and drone IR imaging. Also, field testing of the QC procedures for solar radiation and meteorological measurements and new soiling kits will be validated.
  • PORTFOLIO 2 provided by Qualifying Photovoltics (QPV ) and GALP for the development and demonstration of modelling and diagnostics of bifacial PV applications (bifacial) and energy losses currently not well evaluated (soiling, snow and degradation) utilizing higher granularity SCADA monitoring, drone IR imaging, inverters data, locally installed sensors and local weather stations and stepping on appropriate data analytics algorithms. Also, field testing of QC procedures (for bifacial and solar radiation and meteorological measurements) and the soiling kits and the capacitive I-V tracer at 1,500V developed during the project.
  • PORTFOLIO 3 provided by Ingeteam (ING) for the development and assessment of PV inverter digital twin. Monitoring data from utility scale inverters installed worldwide. 

Monitoring information from small (residential) and mid-size PV plants are taken from 5 different portfolios: 

  • PORTFOLIO 4 provided by Mylight Systems (MLS) for the assessment of modelling and diagnostics of small (residential) PV installations (roof PV) across Central Europe, Portugal and UK utilizing the energy meter measurements.
  • PORTFOLIO 5 provided by CEGESA (CEG) for the assessment of predictive maintenance of batteries based on digital twin approach: (1) Demo site 1 -– iSARE will be held at iSare, a 400kW microgrid designed to test new energy solutions, where CEG will install a Li-ion battery (around 100kWh); and (2) Demo site 2 – CEGASA a Li-ion battery, around 30kWh. In both cases, batteries will be equipped with required condition monitoring to validate the digital twin approach.
  • PORTFOLIO 6 provided by CNR for the assessment of modelling and diagnostics of mid-size PV systems and energy losses currently not well evaluated (soiling, snow and degradation) utilizing SCADA monitoring information.
  • PORTFOLIO 7 provided by Cythelia (CYT) on 80 PV systems for the assessment of modelling and diagnostics of mid-size PV plants (commercial buildings) and energy losses (soling and snow) utilizing SCADA monitoring information. 
  • PORTFOLIO 8 provided by CYT for the assessment of modelling and diagnostics of new PV applications (bifacial and BIPV) and demonstration of the BIPV digital twin and PV inverter efficiency characterization

During the starting phase of the project, each portfolio’s responsible detailed the monitoring system set in place and the additional equipment they have to install to satisfy the monitoring requirements needed to validate the developments. Besides, the way the monitored data will be accessed by the developers is explained. Finally, each portfolio´s responsible has crosschecked the validation plans proposed by the technology providers, from the plant operator´s point of view, identifying the PV plant in which each individual project innovation developed will be validated. In this way, the project ensures that all developments are demonstrated in at least one PV plant of those portfolios.

Power Forecasting and High PV Integration into Utility Grids


Monitoring information for the project is being collected in operational conditions from heterogeneous portfolios of plants of different sizes. This data is used for the assessment of developed solutions in Power Forecasting and High PV integration into utility grids and markets.

The conclusions drawn from the monitoring will be completed systematically and confirmed by field testing exercises on the following 4 demo sites:

  • Residential PV fleet of 18,000 systems monitored by MLS in Europe for assessment of: 
    • Forecasting: a) Short term PV power forecasting; b) PV power nowcasting; c) improved power forecasting in presence of snow, dust, fog, and other extreme events; d) forecasting for spatial averaging and PV aggregation
    • Solutions for further penetration of PV into grid: a) integration of v2g g2v into self-consumption optimisation software; b) integration of virtual batteries into self-consumption optimisation software
  • Demo site provided by ING, consisting of several Spanish PV self-consumption installations of medium-scale commercial and residential to demonstrate the automated PV data registration with local TSO/DSO
  • Local grids of Freiburg area (provided by Fraunhofer Institute for Solar Energy Systems), Ulm-Hittistetten (provided by Technische Hochschule Ulm) and Güssing area (provided by FIB) for assessment of: 
    • Advanced forecasting techniques and predictive control
    • Automated PV data registration, grid digital twin and live control of medium-scale commercial and residential PV plants for higher integrability: grid management in the context of small German villages with very high-penetration of PV
  • PV aggregation/portfolio operated by Next Kraftwerke in Germany, Belgium and Netherlands for demonstrating that it is technically feasible to provide ancillary services but also FCR from PV and PV participation in tertiary reserves.




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