Multi-Period Optimization of Energy Demand Control for Electric Vehicles in Unbalanced Electrical Power Systems Considering the Center Load Distance of Charging Station Areas

The rise of plug-in electric vehicles (EVs) impacts the energy demand of power systems. This study employed a multi-period power flow analysis on the IEEE 123 node test system, which was optimized for the installation of 6-position EV charging stations. Temporal load shifting was utilized to control the charging intervals of electric vehicles. Non-dominated Sorting Genetic Algorithm (NSGA-II) was applied to determine the optimal locations for installing EV charging stations, considering target functions, such as total energy loss, voltage unbalance factor (VUF), and center load distance. The results showed that the center load distance resulted in the optimal charging station location in the central area of the system, different from conventional considerations. The results showed that installing the charging station in the center of the load group (case 4) increased the total energy loss and VUF compared to installing it at the root of the load group (case 3) by about 2.1134 and 1.2287%, respectively. However, EVs reduced impacts during periods of system weakness. By controlling charging intervals during off-peak times (case 6), total energy loss and VUF were decreased by 4.7070 and 5.6896%, respectively, which effectively reduced energy demand during peak periods

Impact of fast charging on lithium-ion battery in electric vehicle application

This paper presents the impact of fast charging on Lithium-ion batteries in electric vehicles (EVs) application. This impact occurred the charging accident based on chemical gas components of the Lithium-ion battery. According to the lithium-ion battery is popular used to be the primary energy for electric driving destination target and defined in high volume per energy density. The scheme of the charging station is used to find the gas volume of the lithium-ion battery component from the EVs. ALOHA software was applied to analyze the charging accident. The gas releases from the lithium-ion battery were selected to analyze the impact on the surrounding area and the environment of the fast charging station. The fast charging units are divided into 3 scenarios with 1, 5 or 10 EVs for the charging process. The simulation results for the Carbon monoxide (CO) showed the most impact to the thermal radiation treat zone, the flammable treat zone of 10 m and 54 m. Meanwhile, the toxic treat zone from the smoke generation showed the large scale of the free space area and concerned the wind flow direction. Therefore, the impact from the EVs during charging accidents needs to be studied to provide vital information for emergency situations and to advise on the preparation of optimal conditions for EV users and participants