Abstract
Transportation vehicles are a large contributor of the carbon dioxide emissions to the atmosphere. Electric Vehicles (EVs) are a promising solution to reduce the CO2 emissions which, however, requires the right electric power production mix for the largest impact. The increase in the electric power consumption caused by the EV charging demand could be matched by the growing share of Renewable Energy Sources (RES) in the power production. EVs are becoming a popular sustainable mean of transportation and the expansion of EV units due to the stochastic nature of charging behavior and increasing share of RES creates additional challenges to the stability in the power systems. Modeling of EV charging fleets allows understanding EV charging capacity and demand response (DR) potential of EV in the power systems. This article focuses on modeling of daily EV charging profiles for buildings with various number of chargers and daily events. The article presents a modeling approach based on the charger occupancy data from the local charging sites. The approach allows one to simulate load profiles and to find how many chargers are necessary to suffice the approximate demand of EV charging from the traffic characteristics, such as arrival time, duration of charging, and maximum charging power. Additionally, to better understand the potential impact of demand response, the modeling approach allows one to compare charging profiles, while adjusting the maximum power consumption of chargers.
Highlights
The transport sector is responsible for almost a quarter of worldwide total CO2 emissions, while about three quarters of these emissions are attributable to cars and trucks
The main focus is on modeling the aggregated daily charger load profiles and comparing them with the load profiles during a demand response event when the maximum available charging power is reduced
Another large obstacle is unavailability of Electric Vehicles (EVs) vehicle labeling in the dataset, which constitutes the inability to model spatial coefficients, so that it is possible to take into consideration the geographical location of the charging infrastructure
Summary
The transport sector is responsible for almost a quarter of worldwide total CO2 emissions, while about three quarters of these emissions are attributable to cars and trucks. According to the IEA report, car ownership, trucking activity, and air travel would increase substantially by 2050 [1]. Besides promoting the climate change, the increasing number of combustion engine vehicles adds to the problem of airborne particle pollution. One of the challenges is to enable mobility without accelerating the climate change and prevent adding up to the already existing pollution problem [4]. Due to absence of emission during operation, Electric Vehicles (EVs) have become a promising technology that offers practical reduction of the CO2 emissions and air pollution if the increased power demand necessary to charge EVs is sustainable
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