The Orderly Charging Strategy of Electric Vehicles in V2G Mode by Considering user Responses

This paper primarily establishes a vehicle-to-grid (V2G) model for electric vehicle (EV) charging and discharging, employing a particle swarm optimization algorithm. Under the premise of ensuring the travel demands of EV users, the model aims to maximize the consumption of surplus photovoltaic power from the commercial building’s base load by work-area EVs. A dynamic time-of-use electricity pricing model is formulated based on the deviation between photovoltaic output and work-area load, thereby reducing peak-valley differences and ensuring grid stability, while also enhancing the satisfaction of EV users with charging and discharging, achieving a win-win outcome. The objective function for minimizing distribution grid load variance incorporates the conventional work-area load, photovoltaic output, and EV charging/discharging power, leveraging the dual source-load characteristics of EVs.

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Publication Details

Published
2025-07-25
DOI
https://doi.org/10.1109/aceee66257.2025.11148601
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
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article

The Orderly Charging Strategy of Electric Vehicles in V2G Mode by Considering user Responses

Aoyang Han, Ying Wu, Mingchen Wang, Yuanfu Li et al.
Electric Vehicles and Infrastructure
article

The Orderly Charging Strategy of Electric Vehicles in V2G Mode by Considering user Responses

Aoyang Han, Ying Wu, Mingchen Wang, Yuanfu Li, Zhen Wei, Feng Wang, Lisheng Li
article en

Abstract

This paper primarily establishes a vehicle-to-grid (V2G) model for electric vehicle (EV) charging and discharging, employing a particle swarm optimization algorithm. Under the premise of ensuring the travel demands of EV users, the model aims to maximize the consumption of surplus photovoltaic power from the commercial building’s base load by work-area EVs. A dynamic time-of-use electricity pricing model is formulated based on the deviation between photovoltaic output and work-area load, thereby reducing peak-valley differences and ensuring grid stability, while also enhancing the satisfaction of EV users with charging and discharging, achieving a win-win outcome. The objective function for minimizing distribution grid load variance incorporates the conventional work-area load, photovoltaic output, and EV charging/discharging power, leveraging the dual source-load characteristics of EVs.

Shandong University (CN), State Grid Corporation of China (China) (CN), Shanghai Electric (China) (CN), Economic Research Institute (BG)
Openalex Percentile: Top 76%
Electric Vehicles and Infrastructure
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