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EnergyLab TimeSeries

EnergyLab TimeSeries

Real-Time Data, Sensor Dashboards, and AI-Built Monitoring Systems

  • Welcome to EnergyLab-TimeSeries.com
  • Sandbox 3
  • Sandbox 5
  • Sandbox 6
  • Sandbox 8
  • Sandbox 9
  • Sandbox 10
  • Sandbox 11
  • Sandbox 12
  • Sandbox 13
  • Sandbox 14
  • Sandbox 15
  • EnergyLab Projects
    • EnergyLAB Journal
    • EnergyLab Data and Archives
    • EnergyLab Data Points – LAN
    • EcoFlow Power Station with Solar PV
    • Gas Boiler Efficiency Monitoring
    • Tracking Infrared Stack Temperature for Energy Use
    • IR Temperature Sensing Thermal Pane Window
    • Sandbox 1
      • Sandbox 1: Programming with Jarvis – NANO to Googlesheet in WordPress
    • Sandbox 2
      • From Sensor to Sandbox: Inside EnergyLab’s Real-Time Data Flow
  • EnergyLab Programming
    • From Keyboard to Control Center: Building a New Kind of Lab with ChatGPT
    • Engineering with ChatGPT
    • Programming with ChatGPT – Lessons Learned and Best Practices
    • Team EnergyLab: How I’m Building the Future with ChatGPT
    • EnergyLab Archives
  • About Us
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Sandbox 5

Real-time InfluxDB LAN ➝ EnergyLAB Hub LAN ➝ WordPress Cloud Sync (Post-Secured)

Overlay Map Live Trends System Stats

🧾 Sandbox 5: System Description

Live graphic (auto-updated every 60 seconds) illustrating power flow from a utility grid power plant to a desktop receptacle.

This system was originally developed out of personal interest and curiosity to understand — via the EnergyLAB LAN — the interaction of electrical loads with battery storage and solar power. See also [EcoFlow Power Station with Solar PV LINK]

An EcoFlow Delta 2 Max Power Station (2,400W, 2,048Wh, LiFePO₄) is plugged into the receptacle. A desktop workstation with three large monitors is powered by the station, along with select EnergyLab monitoring equipment. The total electrical load varies between 60 and 700 watts, depending on activity. This data is published every 5 seconds.

A Renogy 400W portable/foldable solar suitcase is mounted on a 4′×8′ rack at a 20° tilt and connected to the EcoFlow unit via XT60 solar cable. The panel offers 22.7% cell efficiency under ideal conditions, with output ranging from 0W to nearly 400W, depending on time of year, sun angle, and cloud cover.

Weather data is provided by an on-site Ecowitt HP2564 and WS-90 weather station. This data is published via MQTT once per minute from an Intel NUC 240 Docker container (ecowitt2mqtt) to the MQTT Broker hosted on RPi 241. The solar radiation can range from 0 to around 1,000 W/m2.

Power station telemetry is processed by Node-RED on Intel NUC 240, and is published both to the MQTT Broker (RPi 241) and an InfluxDB database on RPi 253. EcoFlow data points are updated every 5 seconds.

Data is also visualized locally in Grafana (Dell Edge 254).

This system came online in October 2024, and has since grown into a living, evolving project — most recently expanded through ChatGPT-assisted development of the EnergyLAB Hub, enabling data from this private lab network to be shared live via a WordPress site hosted on WP Engine.

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