Insights
CVA Group is one of Italy’s leading renewable energy producers, with more than 1.3 GW of installed capacity across hydropower, wind and solar plants. Fully publicly owned and controlled by the Autonomous Region of Aosta Valley, the Group operates across the entire green energy value chain and, through its subsidiary DEVAL, manages almost the entire regional electricity distribution network.
As part of a growth path that also aims to double installed capacity, CVA chose to strengthen the climate resilience of its infrastructure with tools able to read risk in a more quantitative, granular and forward-looking way.
For those managing electricity networks in mountainous areas, climate risk has a specific layer of complexity. Infrastructure runs through narrow valleys, crosses areas with high hydrogeological hazard, and is simultaneously exposed to multiple risks such as floods, wildfires and landslides. Official maps remain an essential reference, but they do not always provide the level of granularity needed for asset-level decisions. Detailed engineering assessments, on the other hand, are time-consuming and difficult to scale across an entire region.
A further dimension is now impossible to ignore: the future. It is no longer enough to understand today’s risk. It is also necessary to understand how that risk may evolve over the coming decades, in order to guide investments, adaptation strategies and operational priorities.
It is in this context that CVA started working with Eoliann, selecting as a first scope of analysis part of its electricity network and 20 substations in Aosta Valley, with the aim of moving towards a more advanced approach to climate risk assessment.
CVA and Eoliann jointly developed a project based on Airis technology. Rather than limiting the work to hazard assessment alone, the analysis covered the full risk chain: from the probability and intensity of events to asset vulnerability, all the way to the estimation of expected economic damage.
CVA provided the geospatial data of the network, guided the selection of the pilot assets, and contributed its knowledge of the territory to validate the results.
Power lines were divided into 30-metre segments, consistently with the resolution of the models. Each segment and each substation were then analysed through Eoliann’s proprietary models, trained on satellite data, climate variables and geomorphological features of the territory.
The analysis focused on two main hazards:
A first layer of landslide risk assessment was also included.
For each asset, Airis estimated not only hazard, but also its specific vulnerability depending on the infrastructure type, together with the Average Annual Loss (AAL), a metric that captures the average economic impact of risk over time.
Each asset was therefore assigned both a Hazard Index and a Risk Index on a 0–10 scale.
All analyses were carried out both for the current scenario and for future climate scenarios, with 2040 and 2050 horizons and RCP 4.5 and RCP 8.5 scenarios.
This allowed CVA to understand not only present-day risk, but also its possible evolution over time, in line with key European requirements on disclosure and adaptation.
Map of the flood risk index across the electricity network – Baseline 2025
The project delivered a complete risk profile for more than 3,600 network segments and 20 substations, with a reading that goes from hazard all the way to expected economic damage, also including projections for 2040 and 2050.
A complete reading of risk
CVA now has access not only to a measure of hazard, but also to an estimate of vulnerability and expected economic loss for each asset.
A view into the future
The 2040 and 2050 projections make it possible to plan adaptation investments based on how risk may evolve, not just on today’s snapshot.
Clearer priorities for intervention
The most exposed lines and substations were identified precisely, providing a quantitative basis for maintenance and resilience planning.
Multiple hazards, one single framework
Floods, wildfires and landslides were analysed through the same logic and on the same data foundation, resulting in a more integrated view of risk.
The project with CVA clearly shows what it means to move from a fragmented reading of risk to a more complete one, able to keep present and future together.
Because strengthening the resilience of a network does not only mean knowing where risk is concentrated today. It also means understanding how it may change over time, and starting to make decisions accordingly.
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