LAPSE:2023.12159v1
Published Article
LAPSE:2023.12159v1
Probabilistic Load Profile Model for Public Charging Infrastructure to Evaluate the Grid Load
Andreas Weiß, Florian Biedenbach, Mathias Müller
February 28, 2023
Abstract
The shift toward electric mobility in Germany is a major component of the German climate protection program. In this context, public charging is growing in importance, especially in high-density urban areas, which causes an additional load on the distribution grid. In order to evaluate this impact and prevent possible overloads, realistic models are required. Methods for implementing such models and their application in the context of grid load are research topics that are only minorly addressed in the literature. This paper aims to demonstrate the entire process chain from the selection of a modelling method to the implementation and application of the model within a case study. Applying a stochastic approach, charging points are modelled via probabilities to determine the start of charging, plug-in duration, and charged energy. Subsequently, load profiles are calculated, integrated into an energy system model and applied in order to analyze the effects of a high density of public charging points on the urban distribution grid. The case study highlights a possible application of the implemented probabilistic load profile model, but also reveals its limitations. The primary results of this paper are the identification and evaluation of relevant criteria for modelling the load profiles of public charging points as well as the demonstration of the model and its comparison to real charging processes. By publishing the determined probabilities and the model for calculating the charging load profiles, a comprehensive tool is provided.
Keywords
charging point modeling, electric avenue, electric vehicle charging, energy system modeling, grid load, public charging, stochastic modeling
Suggested Citation
Weiß A, Biedenbach F, Müller M. Probabilistic Load Profile Model for Public Charging Infrastructure to Evaluate the Grid Load. (2023). LAPSE:2023.12159v1
Author Affiliations
Weiß A: Forschungsstelle für Energiewirtschaft (FfE) e.V., 80995 Munich, Germany; School of Engineering and Design, Technical University of Munich (TUM), 80333 Munich, Germany [ORCID]
Biedenbach F: Forschungsstelle für Energiewirtschaft (FfE) e.V., 80995 Munich, Germany
Müller M: Forschungsstelle für Energiewirtschaft (FfE) e.V., 80995 Munich, Germany; School of Engineering and Design, Technical University of Munich (TUM), 80333 Munich, Germany
Journal Name
Energies
Volume
15
Issue
13
First Page
4748
Year
2022
Publication Date
2022-06-28
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15134748, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.12159v1
This Record
External Link

https://doi.org/10.3390/en15134748
Publisher Version
Download
Files
Feb 28, 2023
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
186
Version History
[v1] (Original Submission)
Feb 28, 2023
 
Verified by curator on
Feb 28, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.12159v1
 
Record Owner
Auto Uploader for LAPSE
Links to Related Works
Directly Related to This Work
Publisher Version
(0.33 seconds) 0.02 + 0.03 + 0.15 + 0.06 + 0 + 0.03 + 0.01 + 0 + 0.01 + 0.02 + 0 + 0