W4E: Weather 4 Energy & Infrastructure

Weather forecasting to inform energy and infrastructure
Thematic area: Earth/Climate, Projects
Financing: ICSC Innovation Grants
Enabling Technology: Advanced Modeling and Simulation, Artificial Intelligence, High Performance Computing, Machine Learning

The pivotal role played by weather forecasting to inform the energy sector and more generically, the infrastructural system, its qualitative and quantitative interpretation on the downstream impacts far from ideal. The scope of this project falls exactly within this gap. The consortium will develop a novel framework to generate accurate and granular forecasts as well as future climate projections of the underlying energy and infrastructural systems. Examples of these products are wind or photovoltaic power production at specific sites, changes in power lines ampacity across Italy, future scenarios where stress to the road and power assets network will be simulated. To achieve such targets, the project will utilize statistical techniques that will construct a quantitative and flexible approach. The expected impacts on the Italian infrastructure are multiple. First, the final products are expected to have a high TRL, which will grant the stakeholders the possibility to run the quantitative tools in semi-operational mode. These statistical tools are highly flexible and scalable, so that their application to other use-cases and/or sectors is envisaged. 

Italian Research Center on High Performance Computing Big Data and Quantum Computing (ICSC), project funded by European Union – NextGenerationEU – and National Recovery and Resilience Plan (NRRP) – Mission 4 Component 2. 

The goal

The project aims to develop a meteorological model that allows the transformation of meteorological information into impact forecasts for the Italian energy system. The main goal is to improve the planning and resilience of the Italian energy system with respect to climate change and its possible impacts.  

The project provides accurate forecasts and simulations for use in a wide variety of fields, from short-term photovoltaic and wind power generation to power line capacity, to the modelling of hydrogeological phenomena and the monitoring of road infrastructure in future climate scenarios. 

The initial challenge

The challenge of the project is to develop an innovative framework that efficiently translates meteorological information into impact information to obtain complete and accurate forecasts and simulations. 

The solution

Using machine learning and artificial intelligence techniques, the project provides accurate predictions and simulations at different time scales, from the short to the long term. This approach allows for a more comprehensive and detailed assessment of the challenges and opportunities associated with increasing dependence on renewables and the effects of climate change. The solution is aimed at improving the planning and resilience of the energy system, enabling more informed and timely decisions. 


Accurate, high-resolution weather forecasts can help optimize electricity distribution, thereby enabling informed market decisions for bidding. On short timescales, such as those covered by this project, accurate weather generation forecasts can help asset owners and market players such as Eni Plenitude bid better in electricity markets.  

For power system operators such as Terna, accurate short-term weather forecasts for renewable energy generation can improve unit commitment (operational planning of generating units) and operational planning, increase distribution efficiency, reduce reliability issues and, therefore, minimize the number of operational reserves needed in the system.  

Other benefits can be found in relation to public infrastructures such as highways. In this case, the impacts are mainly related to the development of a data analysis model to improve awareness of the state of the territory near highway assets, aimed at improving the ability to prevent risky events for the safety of people and the integrity of infrastructures; the ability to plan maintenance operations and to plan investments in existing parts of the infrastructure (e.g. monitoring) or new candidate segments of the motorway network.  


Participating Spoke


For further information, please contact: barbara.vecchi@ifabfoundation.org

Sustainable Development Goals

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