Use of probabilistic distribution functions for EV fast-charging infrastructure planning for highways
Year: 2024
Type: conference-paper
Abstract: The widespread adoption of electric vehicles (EVs) has brought about a change in transportation, requiring advanced planning and infrastructure development to meet the growing demand. This research presents an innovative approach to model EV charging demand on highways, which is critical for strategically deploying fast-charging infrastructure to support the increasing adoption of EVs. The aim is to develop the charging infrastructure in accordance with the variable demand for EV charging, thus reducing grid congestion and improving the quality of service for EV users. Through the use of probabilistic distribution functions (PDFs) based on traffic flow on different highway segments and EV characteristics, the study offers a dynamic and data-driven framework for accurate predictions of EV charging demand. The planning strategy is based on simulations utilizing real traffic data, thereby ensuring the reliability and applicability of the proposed solutions in actual scenarios.
Authors: Verónica Anadón Martínez, Andreas Sumper
Institution: Universitat Politècnica de Catalunya
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4407362149