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  4. Grid and user-optimized planning of charging processes of an electric vehicle fleet using a quantitative optimization model
 
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Grid and user-optimized planning of charging processes of an electric vehicle fleet using a quantitative optimization model

Publikationstyp
Journal Article
Date Issued
2021-05-15
Sprache
English
Author(s)
Welzel, Fynn  
Klinck, Carl Friedrich  
Pohlmann, Yannick  
Bednarczyk, Mats  
Institut
Quantitative Unternehmensforschung und Wirtschaftsinformatik W-4  
TORE-URI
http://hdl.handle.net/11420/9125
Journal
Applied energy  
Volume
290
Article Number
116717
Citation
Applied Energy 290: 116717 (2021-05-15)
Publisher DOI
10.1016/j.apenergy.2021.116717
Scopus ID
2-s2.0-85102021974
The promotion of electric mobility is considered a counterreaction to climate change and is therefore subsidized by various countries. The possibility of charging individual electric vehicles at employer's premises enables the use of an electric vehicle for a large part of the population. In addition, solar radiation peaks during common working hours, resulting in economic and ecological advantages of locally installed photovoltaic systems at the workplace. As business-as-usual charging management is based on rudimentary rules, this power is not optimally used. Furthermore, high charging utilization may lead to high loads and thereby exceed the limitations of the respective building's grid connection capacity. Hence, an optimization approach for improved charging management is required. A non-linear optimization model for coordinated charging of electric vehicles within a local energy system, which consists of a building, a photovoltaic system and a variety of different electric vehicles, is developed in this work. Respective charging profiles take the maximum charging power as a function of the state of charge into account. The objective is to minimize the costs of the charging station operator, incorporating customer satisfaction via penalty costs. The optimization model results in increased consumption of locally provided photovoltaic power and lower electricity costs in most cases. For companies with limited grid connection, the implementation also allows for more vehicles to be charged simultaneously without extending the grid connection capacity. The developed charging management is therefore suitable for real-time charging scheduling.
Subjects
Dynamic charging management
Electric vehicle
Non-linear optimization
Photovoltaic
Real-time charging scheduling
Workplace charging
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