Electric vehicle charging station placement framework: scenario generation, impact assessment, and placement

Electric vehicles (EVs) are promising solutions for reducing carbon emissions and fossil fuels. However, the EV charging stations (EVCSs) may cause power system issues in the distribution system. Unlike the conventional load fixed to the power system, an EV charging load is a load that moves according to the driver's behavioral characteristics, location, or time. Therefore, charging loads are challenging to control, necessitating a pre-emptive analysis in power system planning and operation. Furthermore, the scenario generation of charging load based on real data is also crucial for accurate analysis. This paper presents the framework for optimal EVCS placement based on charging demand scenario generation and impact assessment analysis on the distribution system. The proposed framework consists of two main steps. First, the charging load scenario is generated according to the residential, commercial, and industrial areas and the time when the charging station is located. The charging demand is modeled via real data, and the kernel distribution estimation is applied to scenario generation to reflect the real characteristics of the charging demand, which is advantageous for modeling charging loads that do not follow parametric distribution (e.g., Gaussian and Weibull distribution). In this Step, the time-series scenario, depending on the location of EVCS, is generated. Second, the optimal location of EVCS for each area type (i.e., residential, commercial, industrial area) is determined based on impact assessment analysis on the distribution system. The charging demand impact assessment regarding voltage and overload is conducted based on the scenario set generated in the first Step. Finally, the bus that minimizes syst em impact while satisfying system operational constraints is determined as the optimal connection point for EVCS. The proposed framework is tested on the modified IEEE 33 bus system to validate its effectiveness.