کنفرانس بین المللی فناوری و مدیریت انرژی

صفحه اصلی / هشتمین کنفرانس بین المللی فناوری و مدیریت انرژی

A comprehensive study of optimal demand management for a distributed network with the EV charging stations

نویسندگان :

Mohammad Hossein Norouzi¹ Masoumeh Gholami² Reza Noroozian³

1- دانشگاه تبریز 2- دانشگاه زنجان 3- دانشگاه زنجان

کلمات کلیدی :

(EVs)Electric vehicles،Green energy،Genetic algorithm،Vehicle to grid،Distributed generations (DGs)

چکیده :

The most important activity to deal with the growing energy demand is the development of power systems through green technologies which will be one of the future requirements of the electrical industry. Since there are limited fossil fuels, the use of renewable energy sources (RESs) has become essential. The high participation of RESs needs frequency regulation because of their inverter-based low inertia generation. Also, the transportation industry is replacing conventional vehicles with electrical vehicles (EVs), which are environmentally friendly and it is estimated that the popularization of plug-in hybrid electric vehicles (PHEV) that can be charged at home will increase greatly in the near future. The effective way to develop distribution systems and overcome the inertia issue of RESs is to use the stored energy in the batteries of vehicles connected to the grid (V2G) in EV charging stations. Vehicles connected to the grid must be charged during off-peak load times, and inject energy into the grid at peak load times to provide inertia to the system and stabilize the frequency. Grid-connected vehicles also increase reliability and can take part in demand response. This paper investigates the effect of electric vehicle charging stations on power losses and voltage profiles in the IEEE standard 33-bus distribution network which is considered as the case study. The collaborative planning results using a genetic algorithm (GA) in MATLAB are compared in two modes with and without the presence of electric vehicles to emphasize the effective performance of optimal EV station integration on the voltage profile and power losses.