4.6 Article

Assessment of Distribution System Margins Considering Battery Swapping Stations

期刊

SUSTAINABILITY
卷 15, 期 8, 页码 -

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MDPI
DOI: 10.3390/su15086782

关键词

battery swapping; flexibility; loading margin; mathematical model

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The penetration of electric vehicles into the market is expected to significantly increase EV charging demand, leading to a surge in the demand for electrical energy. To address this, swapping EV batteries instead of traditional charging can provide capacity support for the power distribution grid during off-peak periods. This study presents a mathematical optimization model that assesses distribution system margins considering different EV charging infrastructures, maximizing system margins while considering battery swapping station loads and grid limitations.
Penetration of electric vehicles (EVs) into the market is expected to be significant in the near future, leading to an significant increase in EV charging demand, and that will create a surge in the demand for electrical energy. In this context, there is a need to find intelligent and cost effective means to make better use of electricity resources, improve the system flexibility, and slow the growth in demand. Therefore, swapping EV batteries rather than traditionally charging them can serve as flexible sources to provide capacity support for the power distribution grid when they are charged during off-peak periods prior to their swapping at the station. This paper presents a novel mathematical optimization model to assess distribution system margins considering different EV charging infrastructures. The proposed model maximizes the distribution system margins while considering the flexibility of battery swapping station loads and distribution grid limitations. To demonstrate the effectiveness of the proposed model, simulation results that consider the National Household Travel Survey data and a 32-bus distribution system are reported and discussed. Unlike charging EV batteries, swapping them would not affect system margins during the peak hours.

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