2025/04/04 by Gabriela Hug, Herrera, Maria Parajeles, Hug, Gabriela · 2 citations
Engineering · #Electric Vehicles and Infrastructure #Electric and Hybrid Vehicle Technologies #FOS: Electrical engineering #Systems and Control (eess.SY) #Transportation and Mobility Innovations #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2504.03633
openalex publication_date 2025/04/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Data overview This dataset offers a detailed view of charging demand and flexibility bounds for a fully electrified passenger car fleet in Switzerland in the year 2050. The data is aggregated at the level of each Swiss municipality, based on the 2022 administrative divisions. It was produced using the methodology outlined in the article "Modeling Charging Demand and Quantifying Flexibility Bounds for Large-Scale BEV Fleets," which has been accepted for presentation at the 2025 IEEE Kiel PowerTech and is available as a preprint on arXiv. The study presents a bottom-up modeling approach that uses geographic and sociodemographic data to simulate vehicle mobility patterns and driving energy needs. Charging behavior is modeled using real-world data, taking into account drivers' energy requirements and their range comfort preferences. Flexibility is quantified by defining hourly upper and lower bounds on charging power, as well as daily limits on the amount of flexible charging energy. Data description The data is organized into four CSV files, each containing specific information: baseline charging demand, lower and upper power flexibility bounds—provided for every municipality in Switzerland and for each hour of the year 2050—and flexible energy bounds, detailed for each municipality and each day of that same year. All quantities are given in kW or kWh. Municipalityhourlychargingpower2050.csv. Municipalityhourlylowerchargingpowerbound2050.csv Municipalityhourlyupperchargingpowerbound2050.csv Municipalitydailyflexiblechargingenergy2050.csv Acknowledgments The research published in this repository was carried out with the support of the Swiss Federal Office of Energy (SFOE) as part of the SWEET EDGE project. The authors bear sole responsibility for the results presented.