Decarbonization of heating in the buildings sector: efficiency first vs low-carbon heating dilemma 16–17th november 2023, Turin, Italy, etsap meeting, etsap winter workshop, semi-annual meeting, november 2023, Politecnico di Torino Lingotto, Torino Mr. Andrea Moglianesi, VITO, Belgium

2. • General context: buildings and space heating
• Modelling approach
• Data sources
• Modelling implementation
• Scenario setup
• Results and insights
• General – Residential sector
• Energy Efficiency and Low Carbon Heating
Overview

3. • Buildings still cover ~12.4% of
GHG emissions in Europe
• This despite a decarbonization
effort (-20% fossil fuels
consumption from 1990)
General context
Buildings sector
Distribution of greenhouse gas emissions in the European Union (EU-27) in 2021, by sector
Source: Statista

4. General context
The role of space heating
0
10
20
30
40
50
60
70
80
Cooking Space
cooling
Space
heating
Water
heating
Belgium
Consumption
[PJ]
Final Energy Consumption - Residential Buildings
Other
Fossil fuels
0
500
1000
1500
2000
2500
Cooking Space
cooling
Space
heating
Water
heating
EU27
Consumption
[PJ]
Final Energy Consumption - Residential Buildings
Other
Fossil fuels
• Space heating covers two thirds of the final demand and 77% of fossil
consumption in residential buildings in Europe
• In Belgium these figures are even more extreme (75 and 88%)

5. General context
The role of space heating
• Two key measures for the decarbonization of space heating
• Energy Efficiency increase through renovation and insulation
• Electrification of the demand (heat pumps)
• Very often, the economic viability of one measure depends on the level
of the other → Dilemma
price ratio elec/gas = 3.5 price ratio elec/gas = 2.5
insulation a b c d e f insulation a b c d e f
a 0.93 a 1.00
b 0.93 0.71 b 1.00 1.00
c 0.93 0.71 0.42 c 1.00 1.00 0.93
d 0.95 0.76 0.47 0.28 d 1.00 1.00 0.96 0.74
e 0.96 0.78 0.49 0.31 0.25 e 1.00 1.00 0.98 0.78 0.68
f 0.98 0.85 0.60 0.40 0.33 0.23 f 1.00 1.00 1.00 0.90 0.83 0.62
Decision matrix showing the proportion of heat supplied by the heat pump in a year for different insulation levels, per electricity/gas price ratio.
For medium-sized terraced buildings. Source: VITO/EnergyVille

6. Modelling approach
The model: TIMES-BE-3R
• First Belgian 3-regions model (VITO-ICEDD)
• Flanders, Wallonia, Brussels
• Developed in the framework of EPOC project (funded by Federal Government)
• Collaboration between several partners, who helped with sector-specific data
• Universiteit Gent for power import/export curves
• TML for transport
• VITO-SEB for buildings

7. Modelling approach
Data – Residential sector
Large availability of data on
buildings → Necessity to
find a compromise between
high resolution and
computational expense

8. Modelling approach
Residential buildings sector
• Buildings divided per category (2,3,4 Facades, Apartments)
• End demands are not building-specific, except for space heating and
water heating
• Demands can be satisfied using specific technologies (heat pumps,
etc.)
• For space heating, its demand can be also satisfied installing insulation
technologies, which directly provide end demand

9. Modelling approach
Residential buildings sector

10. Modelling approach
EPOC Central Scenario
General assumptions
• Net-zero 2050 Scenario
• CO2 price increasing from 50€/t (2020) to 350€/t (2050)
Residential sector
• Demand driven by population growth (from FPB estimates)
• Max 4% annual energy efficiency renovation (to potentially reach
100% in 2050)

11. Results
General residential sector results – Final Energy Consumption

12. Results
General residential sector results – Emissions by end demand

13. Results
Residential sector – Space heating demand by technology

14. Results
Residential sector – Energy Efficiency Strategy

15. Results
Residential sector

16. Results
Residential sector

17. Modelling approach
• In case of large availability of data for residential buildings, a balance
should be found between resolution of inputs, and the model size
• With appropriate strategies, it is still possible to obtain very detailed
results
Model results
• When there is a substantial uptake of heat pumps, investments in
energy efficiency measures are optimal (especially for older buildings)
• Still, the main driver for their uptake is ELC/GAS price ratio
Conclusions
Main takeaways

18. Thank you for the attention