Projekt

Spatiotemporal Analysis of Electric Truck Charging in Europe (VESUVIO)

The European Union’s climate targets – cutting greenhouse gas emissions by 55% by 2030 and reaching net zero by 2050 – require a rapid transformation of the freight transport sector. Electrifying heavy-duty vehicles (HDVs) is a key part of this effort. However, the deployment of public charging infrastructure and integration into existing electricity grids remain significant challenges.

This research project aims to close these knowledge gaps by providing detailed insights into the spatial and temporal charging demand for battery-electric trucks (BETs) across Europe and evaluating the readiness of regional electricity grids.

Electric truck adoption is accelerating, but infrastructure development must keep pace. This project provides actionable insights for policymakers, energy providers, and infrastructure operators by combining transport demand forecasting with electricity grid analysis. It supports implementation of the AFIR regulation and helps ensure that the electrification of freight transport proceeds efficiently and reliably.

Objectives and Outputs of the two project phases

  • In the first phase (June – December 2025), the project develops a high-resolution model to estimate electric truck charging demand across the EU27 and neighboring countries. The model accounts for market uptake scenarios, truck fleet compositions, trip patterns, and charging behaviour for different operational types (urban, regional, and long-haul).

    The model produces hourly load profiles on a regional scale (e.g. NUTS-3 or 16×16 km grid cells), helping to identify high-demand locations such as major corridors and logistics hubs. It integrates data from freight transport models, national statistics, and infrastructure plans such as the Alternative Fuels Infrastructure Regulation (AFIR).

    Expected outputs include:

    • A scenario-based simulation tool (developed in Python) to estimate charging demand over time and space
    • Open data sets and key assumptions for BET deployment and charging behaviour
    • Regional energy demand maps and hourly load curves
    • A validated, modular demand model that can be updated as new data becomes available
    • Interactive maps and data visualizations (optional)
  • In the second phase (January – June 2026), the project assesses whether regional electricity grids can meet future charging needs in selected European regions. Areas with high demand and publicly available grid data will be prioritized – such as parts of Ireland, the UK, France, Sweden, and Germany.

    This analysis compares projected charging loads with medium-voltage grid capacity on a substation level. The study also explores alternative solutions like demand-side management, smart charging, and local storage to alleviate potential bottlenecks.

    Expected outputs include:

    • Substation-level assessments of grid capacity and constraints
    • Identification of reinforcement needs in grid-critical regions
    • Regional and cross-country recommendations for infrastructure planning
    • A final report on grid readiness and planning strategies