Liten is a major European research institute and a driving force behind the development of the sustainable energy technologies of the future. The institute is spearheading the EU’s efforts to limit dependency on fossil fuels and reduce greenhouse gas emissions in three key areas: renewable energy, energy efficiency/storage and development of materials.
Our platforms, sophisticated tools for industry & the scientific/technical infrastructure/expertise to overcome technological hurdles
Liten's research teams work across a vast portfolio of renewable energy technologies. Cutting-edge photovoltaic technologies are developed at INES, the French National centre for solar research and R&D with Hydrogen and Biomass activities being managed from the LITEN's main site in Grenoble, Rhone-Alpes.
“Radically improving energy efficiency will reduce the need for investment in energy infrastructure, cut fuel costs, increase competitiveness, lessen exposure to fuel price volatility, increase energy affordability for low-income households and cut local and global pollutants improving consumer welfare” Source OECD Energy report, 2014
From nanosecurity, nanocharacterisation,and anti-counterfeiting technology to the development of advanced materials and point of sale: a comprehensive offering.
Transverse activities help add value to our technology portfolio. An optimised modeling and characterisation model, for example, can help reduce time to market. Browse this section to find out more....
Solar photovoltaic energy: forecasting production and predicting system faults
Forecasting solar PV energy production is a strategic
challenge for government agencies, electric utilities, and managers of
facilities like parking garages with EV charging stations. Knowing in
advance how much solar photovoltaic energy will be available is crucial
to planning ahead for backup energy from other sources, using stored
energy to offset dips in production due to fluctuations in the weather
(for example in island and other highly-variable climates), and,
generally, to more effectively manage the different sources of available
energy to achieve greater savings and reduce CO2 emissions. Just as
important to PV plant operators is the capacity to predict potential
system faults and estimate their impact on production. This requires
measurable performance indicators (non-disruptive to production) that
can be used to determine the relevant predictive and curative
We have been researching PV system troubleshooting
since 2006 and forecasting since 2009. Our researchers developed a
forecasting solution under the ReactivHome project (financed by the
French National Research Agency). The solution was able to predict how
much solar PV energy would be available to a building the following day.
A platform with forecasting tools leveraging the physical operating
principles of a PV plant was developed—a break with the statistical and
mathematical models that were the state of the art at the time. Using
physical modelling on equipment data and actual measurement data results
in a highly-effective learning model that naturally corrects over time
the gaps between forecast data and actual measurements.The
technology was tested successfully during other research projects where
accurate forecasting was important, in fields like home energy systems,
mobility (electric vehicles), and energy management for commercial
properties. Rolling out the technology in such a broad range of
situations led to substantial improvements. "For example, a 24-hour
forecast does not meet all needs. Therefore, 3-hour, 6-hour, and
15-minute forecasting capabilities were developed," said the head of the
program. While the 24-hour forecast mainly uses meteorological data to
determine the solar irradiance on the panels, the 3- and 6-hour
forecasts use satellite data, a paid resource that provides irradiance
data at a given point in time as well as cloud movement speeds. The
15-minute forecast uses 360-degree images captured by a camera at the
site; the camera observes cloud formation and provides information that
helps generate forecasts. "Integrating the three types of data into a
learning model ensures that the solution becomes more and more robust
over 10, 20, 30, and 40-day time horizons. The error rate rapidly drops
to just 5% to 10% in European climates."The current challenge is to
improve the solution. Our researchers are leaving no stone unturned when
it comes to reducing the already-low error rates even further. We are
focusing on the 24-hour forecast, first by separating the direct and
diffuse radiation in the spectrum and by integrating temperature data.
So, rather than just using the primary data, the model also takes into
account what the panel is actually receiving and capturing. This makes
the meteorological data even more powerful. With each improvement
achieved by our photovoltaics experts, the solution gains a few tenths
of a point in terms of performance.
The CEA is also investing in
troubleshooting research, and funded its own program on electric arc
detection and termination in 2006. In 2009, under the DLD PV program
funded by the French National Research Agency, we investigated fault
signatures and identification and classification methods. Currently, we
are focusing on two promising alternatives, one that leverages thermal
images captured on-site, and another that entails plotting and analyzing
the IV curve for each panel.
Solutions already available on the energy market
The market for solar PV production forecasting is marked by fierce
competition; a number of companies offer very reliable 24-hour
forecasts. Liten's solution is different in that it combines three time
horizons (24-hour, 6-hour, 15-minute). Only two providers in France can
deliver this type of data.
SteadySun, a startup founded in
2012 by a Liten researcher, is carving out a position on a variety of
markets that could benefit from this technology. The company has already
signed contracts with a number of energy providers in Europe and the
United States seeking technologies to better predict demand and provide
the backup energy needed to keep the grid operating as intended. Two
additional solar-energy trading solutions are also available, providing
users with data crucial to their trading every fifteen minutes.
Liten's solar PV forecasting technology is being used in a number of
research projects at the national and EU levels, providing data that
will drive further advances in this field.
The ReactivHome project (2009), funded by the French National Research
Agency, laid the foundations for today's forecasting technology. The
goal of the project was to enhance energy production and consumption at
the individual-building level according to cost, environmental impact,
and peak demand. The project partners were Liten, G2Elab, G-SCOP,
Schneider Electric, and Orange Labs.
From 2009 to 2012,
several projects funded by French Energy Agency ADEME leveraged
technologies developed at Liten. One such project was Opera, which
focused on securing an island grid (Mayotte). Another was DHRT2, a
technology-development partnership between Toyota, the French National
Solar Energy Institute INES, and the CEA to improve the overall
building/vehicle energy system. Finally, the pioneering smart-grid
project Reflexe, also funded by ADEME under the French government's
economic stimulus package, was led by Veolia Environnement and brought
together four premier partners: Alstom Grid, Sagemcom, CEA-Liten, and
electrical engineering school Supélec.
The EU Horizon 2020
project Tilos, which kicked off in 2015, includes a forecasting-model
work package where Liten is contributing to solar irradiance
forecasting. This project brings together fifteen research institutes
and businesses from seven European countries.
In 2012 Liten
formed a partnership with Socomec to research electric arc detection.
The goal is to release a product on the US market in late 2015-early
In 2012, Liten also formed a partnership with Urbasolar to enhance troubleshooting and management tools for PV plants.
Around ten researchers
Contact an expert to find out more
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.