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• W3038827787 abstract "The penetration of electric vehicles (EVs) and photovoltaic (PV) systems has increased globally in the last decade. For planning purposes, the spatiotemporal variability of distributed PV power generation and EV charging needs to be quantified for urban and rural areas. This study introduces a state-of-the-art, open, and generally applicable model framework for assessing the spatiotemporal mismatch between EV load and PV generation for urban and rural areas. The model is applied to a rural and an urban area, both 16 km × 16 km and located in Sweden, and is evaluated for the extreme months of January and July. The results show that an energy deficit of, at most, 86% and an up to ten times surplus took place in January and July, respectively. A high self-consumption (SC) of 77% was observed for January and a high self-sufficiency (SS) of 69% for July. This is to say that during July, PV can fulfill 69% of the EV charging load. Moreover, there were no observed correlations between the PV-EV temporal matching scores (the SS and the SC) and the dominant type of charging, e.g., workplace charging in each grid cell (1 km × 1 km) of the areas. This can be partially attributed to the wide distribution of the rooftop orientations in both areas. This challenges the assumption of low PV-EV temporal matching in residential parts of the city. Applying the proposed methodology to other regions is incentivized." @default.
• W3038827787 created "2020-07-10" @default.
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• W3038827787 date "2020-07-01" @default.
• W3038827787 modified "2023-09-26" @default.
• W3038827787 title "Estimating the spatiotemporal potential of self-consuming photovoltaic energy to charge electric vehicles in rural and urban Nordic areas" @default.
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• W3038827787 doi "https://doi.org/10.1063/5.0006893" @default.
• W3038827787 hasPublicationYear "2020" @default.
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