Ich dachte, meine Wärmepumpe wäre SPARSAM – dann kam DAS 10€-Teil! MEGA!

Summary

Andreas Schmitz demonstrates how smarter control could substantially lower a heat pump’s electricity costs without replacing the heating system or adding insulation. His setup uses a roughly €10 infrared transmitter, temperature sensors, and a self-built machine-learning controller to operate an air-to-air heat pump. He says the ideas may also apply to air-to-water systems.

A central point is that maximizing the coefficient of performance (COP) does not necessarily minimize energy use or cost. In the tests, maximizing COP made the heat pump run steadily at low power and fan speed, raising COP from 4.9 to 5.3 compared with automatic mode. But it also produced more heat than needed, so total electricity use and cost were higher than with a strategy aimed directly at reducing consumption.

Four control strategies

1. Maximize COP: Run continuously and gently for high efficiency. This improved COP but could overheat the space and use more total energy.
2. Minimize energy use: Heat in short, high-power bursts, then let the room’s thermal mass store heat. The controller aims to provide only the heat needed, rather than maximize efficiency per unit of heat.
3. Use dynamic electricity prices: Shift heating to cheaper periods—such as overnight or when midday solar generation lowers prices—and coast through expensive periods using stored heat. COP falls further, but the electricity bill can fall.
4. Include occupancy predictions: Estimate when someone will be in the room, using patterns or sensors such as motion detectors. Preheat during cheap periods, then rely on stored heat while the room is occupied or unoccupied as appropriate. In the example, the controller sometimes lets the temperature dip below its target to avoid expensive heating.

For the selected example day, the video compares a €3.79 automatic-mode bill with €1.35 under the most advanced strategy—about one third as much. These comparisons use a simulation of the heat pump and room, built from weeks of measurements so the same modeled winter day can be tested under different control strategies. The one-third saving is therefore not yet presented as a verified real-world result.

Schmitz says the energy-minimizing strategy is already running in his home. Dynamic pricing and occupancy-aware control are planned for later real-world testing.

Guide and tutorial content

The video offers a step-by-step conceptual guide to the four control strategies and explains why heat-pump control should consider total energy, electricity prices, and when rooms are used, rather than focusing on COP alone. A separate video is promised to explain the simulation and control system in more detail.

Main speaker/source: Dr. Andreas Schmitz (Akkudoktor), presenting his own heat-pump tests and simulations.