Analyzing electric vehicle, load and photovoltaic generation uncertainty using publicly available datasets
This paper aims to analyze three publicly available datasets for quantifying seasonal and annual uncertainty for efficient scenario creation. The datasets from Elaad, Elia and Fluvius are utilized to statistically analyze electric vehicle charging, normalized solar generation and low-voltage consume...
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Main Authors | , , , |
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Format | Journal Article |
Language | English |
Published |
02.09.2024
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Subjects | |
Online Access | Get full text |
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Summary: | This paper aims to analyze three publicly available datasets for quantifying
seasonal and annual uncertainty for efficient scenario creation. The datasets
from Elaad, Elia and Fluvius are utilized to statistically analyze electric
vehicle charging, normalized solar generation and low-voltage consumer load
profiles, respectively. Frameworks for scenario generation are also provided
for these datasets. The datasets for load profiles and solar generation
analyzed are for the year 2022, thus embedding seasonal information. An online
repository is created for the wider applicability of this work. Finally, the
extreme load week(s) are identified and linked to the weather data measured at
EnergyVille in Belgium. |
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DOI: | 10.48550/arxiv.2409.01284 |