Development and Optimal Design of Electric Vehicle Charging Station Digital Twin

Electric vehicles (EVs) have contributed to reducing carbon emissions, promoting the advancement of sustainable transportation. However, a widespread adoption of EV is significantly impeded by the lack of charging stations and inefficient charging systems. To address these issues, we introduce a new Charging Optimization Framework (COF) based on quantitative modeling implemented in Anylogic simulation software. The COF aims to reduce the EV charging time while meeting customers' demands. The methodology incorporates real-time stochastic simulation of EV arrival patterns using a non-homogeneous Poisson process. Computational results indicate a significant reduction (81.46%) in overall charging time over the baseline using the COF. Based on a new System Efficiency metric, the optimal number of charging stations and waiting stations were computed as 11 and 13, respectively, maximizing the average efficiency under the EV arrival and charging demand distribution considered. Simulation results highlight the optimal EV charging station design's potential in helping reduce resource misutilization while fulfilling customers' charging demans. These findings not only support the value of the simulation model for effective planning but also provides a forward-looking solution strategy for electric mobility.