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Python, Photons, and Predictions.

Wallbox

We currently use three electric vehicles in our household and daily life: a Renault Zoe R135, which has been with us since 2019, a Tesla Model Y Long Range, which joined us in 2023, and my company car, a Skoda Elroq 85, which arrived in 2025.

All three vehicles are charged at home using a wallbox. Initially, we had a Wallbox Pulsar Plus installed in 2020, which served us well for several years. However, after the warranty period ended, it started to fail more frequently, leading to multiple replacements and repairs. Eventually, I decided to replace it with a Tesla Wall Connector, which has been more reliable and better suited to our needs.

Both wallboxes are integrated into my self-written Python software stack, which forms part of my self-developed Home Energy Management System. This system connects charging, solar production, consumption data, weather forecasts, and local dashboards into one coherent environment.

The backend periodically polls the Tesla Wall Connector, stores the retrieved data in structured JSON format, and prepares it for visualization on a local dashboard. The frontend reads this JSON file and presents the most relevant operating values directly in the browser, including connection status, charging status, voltage, frequency, current values, temperatures, session data, uptime, and energy statistics.

The system is designed to run autonomously on a Raspberry Pi. It is lightweight, energy efficient, and independent of cloud services. All raw data remains inside my local network, behind a hardened firewall. When external publication is needed, only sanitized and structured JSON data is sent outward to a public web server. Internal systems cannot be queried from outside.

Click here to view the live dashboard for my Tesla Wall Connector.

Historical data from my former Wallbox Pulsar Plus charger is still available. A dedicated dashboard with detailed real-time and historical statistics from the previous setup can be found here. Our full charging history is available here.

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