Application of AOA algorithm for optimal placement of electric vehicle charging station to minimize line losses

The conventional transportation system uses fossil fuels and it emits greenhouse gases which affect the envi-ronment. A new kind of transportation must be created immediately because of the growing population. Electric Vehicles (EVs) have less impact on environmental pollution and they will become the base for future transport systems. The battery's specific energy is very low and it needs frequent charging. The long-distance trans-portation using EVs needs charging stations and it leads to placing Electric Vehicle Charging Station (EVCS) in the power grid. The placement of EVCS in the grid increases network losses which have an adverse impact on the grid. In this research work, network loss minimization by the optimum placement of EVCS along with Distributed Generation (DG) is considered. The proposed approach has been validated on the IEEE 33 bus system. The analysis was carried out using the Loss Sensitivity Factor (LSF) approach considering the variable network pa-rameters in the Radial Distribution Network (RDN). The EVCS optimal placement was resolved by Arithmetic Optimization Algorithm (AOA). The results are compared with Particle Swarm Optimization (PSO) and Harris Hawks Optimization (HHO) approaches. The findings show that the optimal placement of EVCS along with DGs reduces network losses considerably.

Automated summary

The conventional transportation system using fossil fuels emits greenhouse gases, causing environmental pollution. To meet the needs of the growing population, a new transportation system must be established. Electric Vehicles (EVs) have less environmental impact and will be the foundation of future transportation systems. However, the low specific energy of batteries requires frequent charging. Additionally, the placement of Electric Vehicle Charging Stations (EVCS) in the power grid for long-distance transportation leads to increased network losses, negatively impacting the grid. This research focuses on minimizing network losses by optimizing the placement of EVCS with Distributed Generation (DG).