Abstract
The rapid response characteristics and high-speed growth of electric vehicles (EVs) demonstrate its potential to provide auxiliary frequency regulation services for independent system operators through vehicle-to-grid (V2G). However, due to the spatiotemporal random dynamics of travel behavior, it is challenging to evaluate the ability of EV cluster to provide ancillary services under the premise of reaching the expected state of charge (SOC) level. To address this issue, a novel calculation model of charge and discharge capacity of EV cluster based on trip chain with excellent parallel computing performance is presented in this work. Following the introduction of the characteristic variables of the proposed trip chain model, the user’s continuous travel behavior in a time scale of several weeks is simulated. In particular, a bidirectional V2G scheduling strategy based on the five-zone map is designed to guide the charging and discharging behavior of EVs, where the expected SOC levels are guaranteed. The results of a 3-week travel simulation verify the effectiveness of the presented model in coordinating the V2G scheme and calculating the charge and discharge capacity of the EV cluster.
Highlights
In recent years, the development of renewable energy sources, such as wind and solar power, has made great progresses
In order to intuitively reflect the ability of electric vehicles (EVs) responding to Automatic Generation Control (AGC) signals and participating in V2G under the premise of meeting the owner’s travel needs, an EV scheduling strategy based on the five-zone map is proposed as a new solution
This article proposes a novel calculation model of charge and discharge capacity of EV clusters based on the trip chain
Summary
The development of renewable energy sources, such as wind and solar power, has made great progresses. The queuing models for calculating the load of the charging station are proposed in [10] and [11] based on the assumption that the arrival time of EVs at the charging station follows the Poisson Distribution. Based on practical data, analyzing the user’s travel pattern through the trip chain model with time-space variation probability is the fundamental work to study the impact of integrating large-scale EVs on power grids. 4) The charge and discharge capacities of the EV cluster are calculated based on the trip chains and the five-zone map. In order to intuitively reflect the ability of EVs responding to AGC signals and participating in V2G under the premise of meeting the owner’s travel needs, an EV scheduling strategy based on the five-zone map is proposed as a new solution.
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