An Improved Dynamic User Equilibrium Model-Based Planning Strategy of Fast-Charging Stations for Electric Vehicles

Due to the climate change and energy crisis, electric vehicles (EVs) have proliferated significantly in many countries with the aim of mitigating carbon emissions and addressing energy-related challenges. The construction of fast charging stations (FCSs) is considered as an indispensable part in facilitating the wider adoption of EVs. In this context, this article, for the first time, proposes a planning strategy for FCSs based on an improved dynamic user equilibrium (IDUE) model, with the objective of minimizing the travel cost of the traffic network (TN), operation cost of the electricity network (EN), construction cost of newly built FCSs, and travel failure cost. In contrast to the conventional DUE model, the proposed IDUE model not only considers drivers' travel cost but also incorporates the carbon emission flow (CEF) model to account for the carbon emission cost of EVs, thereby achieving the environmental benefits of EVs. Additionally, a novel feasible path screening method for EVs is developed in this work to search the feasible path and identify the practical charging behavior of EVs drivers. To handle the various uncertainties involved in the planning strategy, a data-driven approach based on an improved density-based spatial clustering of applications with noise algorithm is innovatively introduced to generate a set of representative scenarios. Finally, numerical experiments are conducted to validate the superiority and effectiveness of our proposed method.