Transport-Energy Integration Driven Pathways for Electromobility: A Swedish Case Study

The integration of transportation and energy is essential for sustainability, yet large-scale EV adoption faces challenges such as inaccurate energy demand forecasting, in-efficient charging deployment, and increased grid stress. This study proposes the Electrified Optimization for Infrastructure and Energy Transmission (EOIET) framework, integrating en-ergy demand estimation, charging infrastructure optimization, and grid impact assessment. Urban demand is estimated from historical data, while highway consumption is predicted via an LSTM-GRU model with Rayleigh distribution. Charging stations are optimized using a discrete urban distribution model for cities and simulated annealing for highways. Grid stability under large- scale EV adoption is evaluated through Monte Carlo simulations. Validated with Swedish data, this framework offers a scalable and resilient approach to transportation-energy integration.