This March, Reuniwatt's team will be attending the 11th edition of Paris Space Week. Take a seat in our spaceship and join us for brilliant discussions on March 12th and 13th, 2024! Cloud cover forecasts for Space & Defence applications Paris Space Week 2024 is just around the corner and we are delighted to invite you to discover Reuniwatt's trusted products and services. Reuniwatt
Reuniwatt regularly publishes scientific findings, participates at international conferences and welcomes the exchange with fellow scientists in the fields of cloud observation and forecasting, Energy Meteorology, and Atmospheric Sciences. We're looking forward to the AMS 104th Annual Meeting dedicated to the theme "Living in a Changing Environment", taking place in Baltimore, Maryland, US, from 28 January to 1 February, 2024. Supporting basic climate research &
The Solar Quality Summit will take place on January 23-24, 2024 in Barcelona with some great sessions in collaboration with TRUSTPV. Meet Reuniwatt and many other team members from the TRUSTPV consortium to discuss the reduction of the number of failures through preventive mitigation measures and advanced data driven monitoring. TRUSTPV: Combining information along the whole PV value chain Quality assurance best practices are
[Webinar] No Clouds on the Horizon: The Future Looks Bright for FSOC In the last decade free space optical communications (FSOC), also called laser communications, has evolved from a niche to a mature technology. Recent successes have pushed this technology forward, with the aim of providing global broadband coverage. However, FSOC still faces two major challenges to providing similar performance to terrestrial "backbone
Reuniwatt provides Sunology with weather data for its STREAM app for the real-time monitoring of solar production: Sunology, the French leader in residential solar systems that require no complicated work or assembly, has selected Reuniwatt, the market leader for estimating and forecasting solar irradiance, for a collaboration. Supporting residential solar power producers STREAM is Sunology's brand new mobile application. It helps residential solar plant
On Dec 13-14, Reuniwatt's team will be present at Energaia 2023 in Montpellier, France. You can find our team on Booth F58 in Hall B2. Portfolio monitoring and forecasting SunSat Live is Reuniwatt's tool for real-time monitoring. It that can be quickly deployed anywhere on the planet. It allows for an unbiased and independent vision of the estimated irradiance over a portfolio of installations.
Meet us at the MTWE 2023 in Geneva, Switzerland, October 3-5 at booth 1012. Book your slot with our team, including experts Damien Ceus, PhD, and Laurent Sauvage, PhD. Whether you are an existing customer, or would like to get an overview of our portfolio or a tailored product recommendation - we are looking forward to seeing you there!
[Webinar] Weather data: a key element in assessing the actual performance of your solar farms Meteorological data, particularly solar irradiance, is a key element in ensuring the profitability of a solar power farm, from the development phase through to the operational phase. These data are derived both from ground measurements, collected using in-situ equipment, and from assessments based on satellite images. In both cases,
Reuniwatt's CTO Nicolas Sébastien will represent Reuniwatt during the World Meteorological Organization's 7th International Conference on Energy & Meteorology, ICEM, which will take place in Padova, Italy, from 27-29 June. ICEM 2023 The purpose of ICEM 2023 is to provide a dedicated forum where scientists, engineers, economists, policy makers, social scientists, and other specialists and practitioners involved in research and implementation of weather and
Meet our team at The smarter E 2023 in Munich, Germany, at booth A3.540. As a leader in cloud cover observation and forecasting, Reuniwatt offers a clear overview of the amount of solar power production available in the next minutes, hours, days, and weeks. Based on solid R&D work, Reuniwatt has been improving traditional irradiance estimation methods by the application of deep learning techniques.