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Edge Device Energy & Environment

RevPi Controls Intelligent Load Management for EV Charging Parks

How can efficient load management be implemented for large EV charging parks? An innovative Python-based solution using Revolution Pi demonstrates how to intelligently manage more than 100 charging points.

Challenge

ChargeHere needed a flexible and scalable solution capable of reliably managing charging points in various environments. The system had to efficiently control load management and prevent overloads. Ensuring stable and secure operation, even during potential internet outages, was particularly crucial.

ChargeHere, a subsidiary of EnBW (one of Germany's largest energy companies), develops innovative charging infrastructure for electric vehicles. The company focuses on commercial applications for medium to large enterprises. Their solutions range from company parking lots for employees and fleets to commercial properties and public parking garages, including residential real estate projects. The solutions are particularly suitable for locations with extended vehicle parking times, such as hotels, sports facilities, and apartment buildings.

Solution

The solution uses the Revolution Pi with a customized image based on the pre-installed RevPi OS. The software was developed in Python, enabling particularly flexible and powerful development with easy integration. Communication with charging points occurs via WebSockets in a local subnet, ensuring fast and reliable data transmission. A separate industrial router with SIM card provides secure internet connectivity. During internet outages, an offline mode maintains load management while adhering to local load limits.

Implementation

A single Revolution Pi can control more than 100 charging points and is installed in one of the control cabinets at each location. Available power is distributed from the grid connection to various control cabinets, with each cabinet supplying up to 20 charging points. Depending on the project, control cabinets are located in technical rooms of parking garages and underground car parks, or near charging points in outdoor parking areas.

The software comprises three main modules:

  • Monitoring: Real-time supervision of charging points to control status and performance
  • Configuration: Management and adjustment of settings for operational optimization
  • Load Management: Intelligent control and distribution of loads to ensure efficient use of available power

Technologies Used:

  • RevPi Connect with custom image
  • RevPi DIO extension module for additional digital inputs and outputs
  • Modbus TCP for communication with charging points
  • WebSocket communication in local network
  • Industrial router with SIM card for secure internet connectivity
  • Python-based software solution for load management

Results & Outlook

The system enables efficient management and monitoring of charging infrastructure in real-time. The Python-based implementation allows flexible expansion of functionalities and ensures future viability. The solution has been successfully implemented in numerous projects, from company parking lots to hotels and sustainable quarter projects.

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