NOTE: Updated October 2024 with improved charts.
I had a 10 kW Vaillant Arotherm heat pump installed in July 2022, and a year later a Vaillant Sensonet gateway, which provides monitoring and logging services via the ‘myVaillant’ smartphone app. Since I now have a year’s worth of data, this note reviews what has been logged to see how the system is performing.
The heat pump serves my house of approximately 90 square meters internal area. I have previously posted about the building’s energy efficiency and additional first floor insulation added. This pump’s capacity exceeds the current requirements of the house, but we are planning an extension in the near future.
System operation
The way I run the system is for space heating to run continuously with a fixed temperature of 19 degrees C is set in the downstairs hallway (a central point in the house), and hot water to run continuously at 50 degrees C. In the first year of running the system, I experimented with running heating and hot water for set periods during each day of the week, but I found that the heat pump had to work hard to bring the system and the fabric of the house back up to temperature.
I was advised that continuous operation was more efficient and since the house is almost always occupied, this matched our use. At that point I hadn’t taken a close look at the measured performance and was just monitoring the electricity demand ad hoc. It is not to say that running the system with setback temperatures would not be effective and may better match occupancy: see analysis from Heatgeek or Protons for Breakfast on this subject, But for me, having a continuous temperature is the most comfortable and seems to work well.
The myViallant app
The myVaillant app usefully provides a button to download all logged data per year in a set of CSV files and this code is available on Github. I have summarised the year period from July 2023 to July 2024 in the following charts. Having read this PFB review, I am aware that there are issues with the quality of the logged data. The review measured a ~8% error in electricity consumed and a ~20% error in the heat energy produced, as well as pointing out many logged values are quantised to kWh units, which I also observe in my data. Significantly, this means that the raw Vaillant data under reports COP. I don’t have a point of comparison with with an alternative measurement of the consumed and generated energy (although I would like to install an OpenEnergyMonitor to do this). Despite the potential inaccuracies of the Vaillant data, it remains useful for a high-level review of the system.
Analysis
The overall performance of the system for the year from July 2023 to July 2024 is summarised in the following table.
Metric | Value |
---|---|
Consumed electricity heating | 1.34 MWh |
Consumed electricity hot water | 1.01 MWh |
Total consumed electricity | 2.36 MWh |
Average daily electricity consumption | 6.65 kWh |
Heat generated heating | 4.91 MWh |
Heat generated hot water | 3.13 MWh |
Total heat generated | 8.04 MWh |
Heating SCOP | 3.65 |
Hot water SCOP | 3.09 |
Total SCOP | 3.41 |
Note that when scaling consumed electricity by 8% and generated electricity by 20% to adjust for possible inaccuracy, heating SCOP is 4.06, hot water SCOP is 3.43 and they are combined at 3.79. Note also, that these figures do not include the electricity used for the weekly Legionella purge performed by an immersion heater I have installed in my system.
Looking more closely at consumption, the chart below shows all measurements over this period for heating, hot water and their combination.
Most obviously, electricity consumption during the winter months increases significantly when the heat pump is using approximately 10 kWh per day. There are two spikes in November and January where temperatures went below zero, and at these times consumption went up close to 30 kWh per day. As expected, electricity consumption for hot water is more consistent throughout the year with a lesser increase through the winter months. The short periods where both drop to zero are due either to a holiday and the system being in ‘absence’ mode or a technical issue. The technical issue has been due to a loss of pressure in the system, requiring a manual top up from the mains water supply.
The next chart is the heat energy generated, which is tightly correlated with the consumption graph.
Combining the previous two charts by calculating the ratio between generated and consumed, gives the coefficient of performance (COP). A handful of measurements produced very large COP values, that are unrealistic, so I have clipped these with a maximum COP of 6.
This is the same COP data averaged over weekly intervals.
The next chart is a different presentation of the COP data, with COP plotted as a function of heat output. It’s clear that peak COP is at ~10 kW heat output, but there is little penalty in efficiency between that and the highest recorded output.
Looking at the temperature of the hot water tank, this stays constant as expected but with a few exceptions: when I changed the temperature from 45 to 50 degrees C in October 2023; when the system has been off or out of order; and when every week on a Monday the immersion heater kicks in to perform a Legionella purge (which curiously it has stopped since March 2024. After later investigation this appears to be a faulty timer or immersion heater, so I switched to performing the purge using the heat pump itself).
Finally, we have a plot of internal (red) vs external (blue) temperature in degrees C. This clearly shows that the 19 degrees C target was maintained throughout the year, notwithstanding the periods of absence/downtime and on particular hot days when the temperature rose above the target. Given how quickly our summers are changing with more intense heat, having a system that can also perform cooling would be a big benefit. But overall, I think this chart well represents the benefit of having a heat pump, providing a home environment with a continuous temperature throughout the year.
For the same period I obtained the electricity use and cost data from Octopus using their excellent API via the Octograph tool, visualised below on a Grafana dashboard. According to the Vaillant data, the heat pump used 2.39 MWh of energy, which is only 32% of the total electricity use. I am suspicious that this is inaccurate, even factoring in an 8% underestimate from the Vaillant measurements. I would expect the heat pump to be using more like half of total electricity on average, given that other electricity use is cooking and appliances etc, but perhaps I am wrong. Otherwise the usage profile matches between the two data sets.
Summary
The data collected by the Vaillant heat pump control system appears to be somewhat inaccurate but nevertheless provides a high-level overview of the performance of the system. I’ve been very pleased with how it has performed over the last year, and this is backed up by the statistics I have collated. With work planned on the house, there are more thermal-efficiency gains to be made, so hopefully I can further improve it’s running efficiency.
References and further reading
- Protons for Breakfast, articles about heat pumps is a fantastic set of articles by physicist Michael de Podesta.
- Energy Stats provides pricing data for various Octopus Energy tariffs.
- Guy Lipman’s Octopus Energy resources is a collection of notes focusing on using the Octopus API to access energy data.
- Octopus Energy API is the landing page for using their API.
- Octograph (Github) A Python tool for extracting Octopus Energy meter readings to InfluxDB and Grafana.