Abstract
As an important part of the smart grid, Electric Vehicles (EVs) could be a good measure against energy shortages and environmental pollutions. In this paper, based on the relevant EVs development policy, the private EVs charging load is investigated. Based on statistical data, the Monte Carlo method is applied to determine the one-trip driven distance for the private EV. And by analyzing the EVs driving habit and the charging characteristics of EVs battery, we derive the initial state-of-charge (SOC) of charging, charging power and initial charging time. As a result, a more accurate mathematical model of computing the charging load used by private EVs is proposed. Furthermore, the EVs charging loads in 2015 and 2020 are computed and compared in plug-in charging and wireless charging mode. The results of simulation show that the daily load peak of private EVs charging caused by wireless charging mode is significantly lower than that of plug-in charging mode. And the charging load of large-scale EVs would have significant impacts on the planning and operation of power grid. It is very important to predict and analyze the EVs charging load for the construction and scheduling of the smart grid in the future.
Highlights
The preceding scarcity of crude oil, serious environmental pollutions, growing carbon dioxide emissions and other factors initiated a "green" economy, resulting partly in the strive for more efficient individual transportation
This paper aims at predicting the private Electric Vehicles (EVs) charging load profile
Due to many uncertain factors, it is difficult to set up a precise mathematical model of calculating the EVs charging load
Summary
The preceding scarcity of crude oil, serious environmental pollutions, growing carbon dioxide emissions and other factors initiated a "green" economy, resulting partly in the strive for more efficient individual transportation. Compared with Internal Combustion Engine Vehicles (ICEVs) which burn fossil fuels, Electric Vehicles (EVs) show the potential for solving the energy crisis and reducing the emissions of carbon dioxide. The wireless charging mode would become the development tendency of EVs charging [10,11,12] This charging model could disperse continuous charging time and reduce charging aggregation, so that there is difference in the charging load profiles. This paper aims at predicting the private EVs charging load profile. 232 The Open Electrical & Electronic Engineering Journal, 2015, Volume 9 mathematical model is proposed to compute the private EVs charging load by applying Monte Carlo method to obtain the single trip mileage, initial SOC, initial charging time and charging power according to the characteristics of battery and the driving habits. Based on the relevant EVs development policy of China, the private EVs scales until 2015 and 2020 have been predicted and the load profiles are simulated respectively
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