Evaluation of the Usage of Edge Computing and LoRa for the Control of Electric Vehicle Charging in the Low Voltage Grid

Abstract

The electrification of the mobility sector poses new challenges for grid operators. The simultaneous charging of a large number of electric vehicles could overload the grid. To solve this problem, sensors must be used to create observability of the low-voltage grid and to introduce control of the charging processes. The new sensors will generate large amounts of data containing personal information. For better and local handling of these data streams, edge computing approaches have been discussed. In this work, an edge computing system for the problem is presented. The structure of the software and the LoRa-based communication system is discussed in particular. Different sub-tasks are packaged in docker containers to get flexible and reusable software, that can be used for multiple use cases and hardware systems. The LoRa communication should lead to higher data security with it being decentralized and independent of the internet. With the system presented here, it is possible to determine the grid state using the sensors installed in the grid and to use this information to control the charging process of electric vehicles. The system was tested in a field test. The results show the general applicability of the approach and needed improvements for LoRa communication.