The Evaluation Method of Tunable Potential of Electric Vehicle Considering Multi-Time-Step Coupling

The charging behavior of electric vehicles (EVs) is random. Its adjustable ability is uncertain. EV's tunable potential needs to be evaluated before using the adjustability of EVs. However, the existing research fails to fully consider the coupling relationship between the adjustable ability of each time step of EVs. The results evaluated individually for each time step are too optimistic. Therefore, a tunable potential evaluation method for EVs considering multi-time-step coupling is proposed in this research. An evaluation model of the tunable potential of EVs considering multi-time-step coupling is established by analyzing the influence of the coupling relationship between different time steps on the regulation ability of EVs. Particle swarm optimization (PSO) is applied to verify the validity of the method.

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Published
2024-10-25
DOI
https://doi.org/10.1109/appeec61255.2024.10922374
Primary Topic
Engineering Applied Research
Type
article
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The Evaluation Method of Tunable Potential of Electric Vehicle Considering Multi-Time-Step Coupling

Sijie Cai, Yingjin Ye, Zhiming Chen, Nan Ye et al.
Engineering Applied Research
article

The Evaluation Method of Tunable Potential of Electric Vehicle Considering Multi-Time-Step Coupling

Sijie Cai, Yingjin Ye, Zhiming Chen, Nan Ye, Qifan Wu
article en

Abstract

The charging behavior of electric vehicles (EVs) is random. Its adjustable ability is uncertain. EV's tunable potential needs to be evaluated before using the adjustability of EVs. However, the existing research fails to fully consider the coupling relationship between the adjustable ability of each time step of EVs. The results evaluated individually for each time step are too optimistic. Therefore, a tunable potential evaluation method for EVs considering multi-time-step coupling is proposed in this research. An evaluation model of the tunable potential of EVs considering multi-time-step coupling is established by analyzing the influence of the coupling relationship between different time steps on the regulation ability of EVs. Particle swarm optimization (PSO) is applied to verify the validity of the method.

Fujian Electric Power Survey & Design Institute (CN)
Affordable and clean energy
Openalex Percentile: Top 68%
Engineering Applied Research
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