SmartRIVER, a global AI-based Digital Twin solution for AI-driven hydropower energy
intelligence and optimal production forecasting under the coordination of GECOsistema srl in Italy,
it will be providing solutions for AI applications in energy.
Who will help implement the AI solution?
GECOsistema is a specialist company
providing advanced engineering cloud-web, data-science and
modeling studies and services in the
field of environmental, climate risk and geospatial intelligence.
We combine advanced data science and machine learning, environmental modelling, GIS and Geospatial
Analysis tools, remote sensing, predictive analytics, to give you the critical insight you need into
environmental, climate and geospatial issues.
What is the AI solution the project plans to implement?
SmartRIVER is a Digital Twin of the plant catchment, relying on worldwide available forecasts, big
open climate, geospatial and satellite data, and AI at the core for efficient energy forecasting,
with major advantages over complex models:
- No specialist hydrologist skills, no physical model to tune.
- New upstream services (e.g., Copernicus Data Store forecasts) can be used immediately.
- Lightweight cloud deployment, just a web browser is required to users. One forecast service
ranging from single Hydropower plant to multiple assets everywhere, to optimize resources
(reservoir management and energy production strategy) and to save money (energy trading).
SmartRIVER value proposition is exploited as Software as a Service (SaaS), with on demand
subscription, for technicians and for energy traders; to be activated in a few steps for any
hydropower plant of interest, supporting water resources management and energy production.
The I-ENERGY project will support GECOsistema in developing a new SmartRIVER showcase concept in one
river station that serves hydropower generation. This will demonstrate potential of the service to
go far beyond actual approaches, mainly based on traditional complex hydrological models with long
Modeling chains, huge data requirements (soil type, topography, geology, snow depth...).
Within I-NERGY we will move much further to a fully functional prototype at TRL 6, demonstrating a
running and operational forecast service, relying on state-of-art backend AI components, in a
relevant case study area, but with high replicability worldwide.