u/clausy

Had been procrastinating about buying a sub because I wasn't totally happy with the bass. Decided instead to upgrade the power from an 'old' Quad 606 power amp which I thought was already pretty beefy to Quad Artera Monoblocks. Oh. My. God. Speakers are totally transformed - bass properly slaps now. They went from being 'mid' to a proper wall of sound. OK not cheaper than getting a sub, but I don't think I need one now. This is just for music so I don't need it to shake the sofa when something blows up on screen. That's a different use case.
Edit: just to add, now using XLR cables from the Naim to the monoblocks - much smoother 'balanced' volume curve.

1.8kW (4 panels), 3.8kWh battery plugin solar. I got an API key and built a script to collect data and a little dashboard.
Solar generation forecasts from https://open-meteo.com: cloud-adjusted irradiance values — global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI) — for my location in London. These are fed into a https://pvlib-python.readthedocs.io model which accounts for the sun's position and converts the irradiance to plane-of-array (POA) values for each of the four panel strings at their specific tilt and azimuth angles. Applying the total panel capacity and a ~4% system loss factor gives forecast_w — expected generation in watts. Forecasts are collected four times daily (05:00, 10:00, 14:00, 20:00 UTC) and each run is stored separately, so forecast evolution through the day can be visualised. Actual generation is read from the EcoFlow MQTT API, which streams live telemetry; the collector averages these into 15-second windows and writes them to Parquet. This is then resampled to hourly averages so shows a daily actual vs forecast diff.

Spent a couple of hours with Gemini to set up a collector and a (simple) web UI. Still waiting for the Smart Gateway so baseload is locked to 300W for now.

I'll be adding more to it soon, but for anyone else wanting to try it, it's pretty simple to subscribe to your device's datastream. This is not supposed to be perfect - just a basic test app to visualise the data. Think I might chuck data into elasticsearch at some point. Anyway...

Description (from Gemini) of how the app works:

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A two-stage process: real-time ingestion followed by asynchronous visualization. The collector script acts as a background bridge; it authenticates with the EcoFlow API to obtain secure MQTT credentials, then establishes a persistent TLS-encrypted connection to a remote broker. It listens for specific telemetry "quotas" from your EcoFlow Ultra, strictly filtering the noisy raw JSON against a whitelist of 28 critical keys (like cell temperatures and PV string power). To optimize disk I/O, it buffers these snapshots in memory and periodically flushes them into Parquet files, organized in a hierarchical directory structure by date and hour.
The Dashboard App (FastAPI) then serves as the frontend layer. Rather than talking directly to the hardware, it reads from the Parquet "database" generated by the collector. When you access the dashboard, the backend uses Pandas to aggregate the various hour-based files for the current day, performs data normalization—such as converting millivolts to volts or stripping "sunset noise" from solar readings—and serves this as a JSON payload to Chart.js. This architecture ensures the UI remains snappy and responsive, as it is decoupled from the actual frequency of the MQTT messages.

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Here's full list of all the useful keys I'm collecting and writing to disc every 15 seconds and Gemini's interpretation of what they mean:
Power Flow & Consumption

• powGetPvSum: Total combined solar generation across all four strings (Watts).
• pinPv1 – pinPv4: Individual power input for each specific solar string (Watts).
• powGetSysLoad: Total AC power currently being consumed by the house (Watts).
• powGetBpCms: Net battery power; positive values indicate discharging, negative values indicate charging (Watts).
• powGetSysGrid: Net grid power; positive values indicate importing from the grid, negative values indicate exporting (Watts).
• powGetSysLoadFromBp: The portion of the house load being met specifically by the battery (Watts).
• powGetSysLoadFromPv: The portion of the house load being met directly by solar production (Watts).
• powGetSysLoadFromGrid: The portion of the house load being supplied by the utility grid (Watts).

Battery Health & Capacity

• cmsBattSoc: The State of Charge percentage, representing the remaining fuel in the battery.
• vBat: Raw battery bus voltage (usually recorded in millivolts).
• ioutBat: Raw battery output current; used to calculate precise charge/discharge rates.
• remainCap: Total remaining capacity available in the battery pack (mAh).
• cmsDsgRemTime: Estimated minutes remaining until the battery is fully depleted at current load.
• cmsChgRemTime: Estimated minutes remaining until the battery is 100% charged.

Solar Electrical Specs

• vinPv1 – vinPv4: Input voltage for each PV string; useful for checking if panels are within MPPT range (Volts).
• iinPv1 – iinPv4: Input current for each PV string; helps identify shading or panel degradation (Amps).

Thermals & Environment

• maxCellTemp: The temperature of the hottest individual battery cell (°C).
• minCellTemp: The temperature of the coldest individual battery cell (°C).
• maxMosTemp: The temperature of the hottest MOSFET (power transistor) in the inverter/BMS (°C).

Grid Health

• gridConnectionVol: The current voltage of the utility grid, used to monitor for brownouts or surges (Volts).
• gridConnectionFreq: The utility grid frequency; used to monitor stability (e.g., 60Hz or 50Hz).

Sorry about the reflections. It says ‘Created by Robert Smith’ bottom right. It was for sale a few weeks back I think on the WarChild website.