Learning-based projection

The above-described developments in price are based on interviews and experience from the sector. To validate the size and speed of these price developments a learning-based projection is also considered. The following is not an in depth analysis of the heat pump market but should be seen as an indicative analysis of the theoretical price development under certain developments and assumptions as described below.

This is a theoretical method for estimating price developments based on a so-called learning rate. The learning rate describes the price reduction for every doubling of capacity installed or units sold for a given technology.

The Reflex project Technological Learning in Energy Modelling [15] has assessed learning curves for different energy technologies, including heat pumps. Here the heat pump technology is evaluated to have a learning rate of 10% but also concludes that this value is very uncertain and can vary from country to country. For comparison, the same study found the following learning rates for other technologies:

 Solar PV: 18.6-21.4% depending on type

 CCS: 2.1 – 2.2% depending on fuel, but 11-12% for industrial CCS.

 Li-ion battery storages: 12.5-15.2% depending on scale.

 Fuel cell stacks: 18%

 Wind systems: 5.9% for onshore systems and 10.3% for offshore systems

It is assumed that the investment price of heat pumps in Denmark will follow the developments in the EU and therefore, it is necessary to look at the expected number of heat pumps in Europe and not just Denmark.

Table 6 shows an estimate of the distribution of individual heating in Europe [16] [17]. Boilers are assumed to be mainly based on oil and gas. With current climate goals in the EU and individual countries, a shift from boilers to heat pumps and district heating is expected.

Number of heating units 2019

Table 6: Estimated distribution of individual heating installations in EU based on statistics from the European Heat Pump association. Note the statistics for heat pumps only cover EU21, but all large member states are represented.

To begin, it is assumed that boiler installations will be replaced (or supplemented) with another heat source with the following distribution of alternative sources. Exhaust and air-to-air heat pumps are generally supplementary heat sources.

 District heating: 25 %

207 Electric heat pumps, air-to-water, brine-to-water, air-to-air and ventilation

 Exhaust HP: 5 %

Overall, two scenarios are considered: 1) The number of boilers replaced/supplemented is 30% in 2030, 60%

in 2040 and 70% in 2050 and 2) The number of boilers replaced/supplemented is 10% in 2030, 30% in 2040 and 50% in 2050 compared to today. These two scenarios combined by the distribution of alternative heat sources, results in the development of the number of heat pumps described in Figure 43. Table 7 shows the relative number of heat pumps compared to 2019.

Figure 43: Number and type of heat pumps in the 2 scenarios Relative

development

2019 2030 2040 2050

Air-to-water 1 8 15 24

Ground-to-water 1 3 6 8

Exhaust-air 1 6 11 17

Air-to-air 1 2 4 5

Table 7: The relative development for the number of heat pumps compared to 2019.

Figure 44 shows the price developments for 4 different learning curved scenarios and the developments described in the datasheet:

1. 10%: Learning curve predictions based on unit increase described in Table 7 combined with a learning rate of 10%.

2. Same as 1) but with a more conservative learning rate of 5%.

3. The more conservative version of 1) where the boiler reduction instead is 10% in 2030, 30% in 2040 and 50% in 2050. The learning rate is 10%

4. Same as 3) with a more conservative learning rate of 5%.

The learning rate calculations indicates that the price developments presented in the datasheets are neither very optimistic nor conservative. The price reductions for air-to-water heat pumps and ground source heat pumps in the datasheets follow a development between the scenarios with learning rates of 10% and 5% for a more conservative development in Europe, but close to a learning rate of 5% for the more progressive

207 Electric heat pumps, air-to-water, brine-to-water, air-to-air and ventilation

scenario. In 2030 the investment costs in the datasheets are decreased by 14% and 10% for air-to-water and ground-sourced heat pumps respectively while the 4 learning-based scenarios show a range of 9-27% and 5-17% respectively for 2030 compared to 2019.

Figure 44: Expected investment price reduction compared to 2020 for each type of heat pump. See description of scenarios in text.

For air-to-air and exhaust heat pumps, the development described in the datasheet tend to follow the more conservative learning-based estimations towards 2030.

The learning curve estimates presented here are theoretical and based on some simple assumptions about the development of the market in Europe.

86%

207 Electric heat pumps, air-to-water, brine-to-water, air-to-air and ventilation

It is assumed that the learning-curve reductions affect the full investment, because learning is also expected regarding installation hereunder improved product design to simplify installation.

Quantitative description

[7] Energistyrelsen, ” Beregning af SCOP for varmepumper efter En14825”, 2011 [8] Interview med VS Automatic

[9] COWI, ”Evaluering af Abonnementsordningen for varmepumper til boligejere”, 2019 [10] Website investigation of various suppliers.

[11] Interviews with various installation companies.

[12] Interview with Bosch.

[13] The Danish Energy Agency, “Varmepumper installeret halvårligt fra 2009 til første halvår 2020”, 2020. https://ens.dk/sites/ens.dk/files/Statistik/udvikling_i_salg_af_varmepumper_fra_2009.pdf [14] Dansk Energi, ”Den lille blå bog om varmepumper”, 2019.

https://elforsk.dk/sites/elforsk.dk/files/media/dokumenter/2019-04/Den_Lille_Blaa_Om_Varmepumper.pdf

[15] A. Louwen, M. Junginger, A. Krishnan, ”Technological Learning in Energy Modelling: Experience Curves”, REFLEX project, 2018.

http://reflex-project.eu/wp-content/uploads/2018/12/REFLEX_policy_brief_Experience_curves_12_2018.pdf

[16] S. Pezzutto, S. Croce, S. Zambotti, L. Kranzl, A. Novelli, P. Zambelli. “Assessment of the Space Heating and Domestic Hot Water Market in Europe—Open Data and Results”. Energies, 2019.

[17] Statistics from the European Heat Pump association, http://www.stats.ehpa.org/hp_sales/story_sales/

[18] Ministry of Environment and Food of Denmark, ”Utilsigtet tab af Fgasser ved demontering af klimaanlæg og varmepumper Udredningsprojekt”, 2020.

https://www2.mst.dk/Udgiv/publikationer/2020/02/978-87-7038-159-8.pdf [19] SparEnergi.dk, ”Varmepumpe på abonnement”,

https://sparenergi.dk/forbruger/varme/varmepumper/varmepumper-paa-abonnement