BEV Fast Charging Strategy Optimization

Wei Ji

doi:10.1016/j.ifacol.2020.12.152

2020-01-01

冀伟 (Wei Ji) *

DOI：10.1016/j.ifacol.2020.12.152

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摘要

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This paper presents different approaches to optimize battery electric vehicles (BEVs) fast charging strategy. A rule based model was built to simulate BEV charging behavior. Monte Carlo analysis was performed to explore the potential variance of congestion at fast charging stations, which could cause longer than four-hour waiting at the most congested station. Genetic algorithm was performed to explore the potential minimum waiting time at fast charging stations, and it can decrease the waiting time at the most congested station to be shorter than one hour. A deterministic approach results in feasible suggestions that people could consider to take fast charging as soon as the state of charge is approaching 40-miles range while remaining relative short waiting time at charging stations. Copyright (C) 2020 The Authors.

Keyword:

Optimal operation and control of power systems

Modeling and simulation of power systems

Control of renewable energy resources