A Calculation Model of Charge and Discharge Capacity of Electric Vehicle Cluster Based on Trip Chain

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.

Impact of Large-Scale Mobile Electric Vehicle Charging in Smart Grids: A Reliability Perspective

“…The mobile behavior of EV users can be understood as a spatial and temporal interacting process, normally starting from one certain point and finally arriving at the destination, which can be simply categorized into three basic aspects: work, entertainment, and residence. A trip chain is usually utilized to reflect EV dynamic travel characteristics (Liang et al, 2020) and is therefore employed in this paper to provide a better description of user's travel patterns.…”

Research on Charging-Discharging Operation Strategy for Electric Vehicles Based on Different Trip Patterns for Various City Types in China

“…Here, we focus on private cars used for work or entertainment and fully consider people's life habits when simulating user trip patterns. We also adopt a "travel chain" structure to represent the travel time, travel destination, and trip itinerary of EV users and the sequence of each trip [13]. Overall, the travel of an EV used for work and entertainment can be roughly divided into trips to/from home, work, and entertainment, which we represent using the English letters H, W, and E, respectively.…”

Heavy-duty electric vehicle charging profile generation method for grid impact analysis

“…When the HDEV is generated, it is given the initial SOC level when it arrives the HPCS, as SOC arrival . The SOC value is drawn from a normal distribution with a standard deviation [15] equal to 0.1. The expected SOC value µ arrival is decided by the battery size of the HDEV and the average energy used to travel to the HPCS, (4).…”