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

Fynn Welzel, Carl-Friedrich Klinck, Yannick Pohlmann and Mats Bednarczyk

Applied Energy, 2021, vol. 290, issue C, No S030626192100235X

Abstract: 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.

Keywords: Non-linear optimization; Dynamic charging management; Electric vehicle; Photovoltaic; Workplace charging; Real-time charging scheduling (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (15)

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DOI: 10.1016/j.apenergy.2021.116717

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