Abstract
With the increasing number of electric vehicles and the emergence of vehicle-to-grid technology, electric vehicles have become distributed loads and power sources with random movement characteristics in the distribution network. In order to evaluate the reliability of the distribution network incorporating electric vehicles, firstly, this paper uses the trip chain theory to describe the travel of electric vehicles. Based on the static traffic flow distribution, a high efficiency quasi-dynamic travel simulation method is proposed to consider the influence of traffic congestion on the path selection. Then, the simulation time advancement of the Monte Carlo method is improved, which makes the reliability assessment of the distribution network containing a large amount of electric vehicles' charging and discharging behaviors realizable. Finally, the practicality of the method is verified by the modified IEEE-RBTS Bus-6 test system. The effects of electric vehicles penetration, discharging threshold, and battery capacity on reliability of both distribution networks and electric vehicles are studied.
Highlights
In recent years, environmental and energy problems have become increasingly severe
THE TRIP CHAIN OF EVS This paper focuses on the modeling and analysis of private electric vehicles for the reason they are principle members in V2G [13]
· 100% = Si where Si is the charging threshold of vehicle i, SOCi is the state of charge; Eiall is the battery capacity; Eimax represents the maximum of daily power consumption
Summary
Environmental and energy problems have become increasingly severe. Electric vehicles (EVs) with environmental protection and energy-saving advantages have been proved effective to alleviate energy shortage, environmental pollution and global warming [1]. This paper aims to solve the contradiction between path simulation accuracy and calculation speed and proposes a quasi-dynamic traffic distribution method. We establish an assessment method for the reliability of distribution network and electric vehicles, in which traffic simulation and Monte Carlo simulation are improved. On the basis of static traffic flow distribution, the temporal and spatial distribution and real-time state of charge (SOC) of EVs are obtained by efficient quasi-dynamic simulation method. Based on the former, the influence of electric vehicles penetration, discharge threshold and battery capacity on distribution network and electric vehicles’ reliability is studied. For (1) and (3), the type of trip chain and departure time can be extracted by Monte Carlo simulation
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