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Article
Techno-economic analysis of residential building
heating strategies for cost-effective upgrades in
European cities
Fei Yu, Wei Feng,
Maohui Luo, ..., Rui
Jiang, Jiawei Leng,
Liqun Sun
w.feng@siat.ac.cn
Highlights
A novel Monte Carlo
method for space heating
techno-economic analysis
Cost-benefit analysis
based on tariffs, building
envelope, and user
behaviors
Quantify incentives to
improve the cost benefit of
heat pump space heating
Policy recommendations
for European building
retrofit and heating
electrification
Yu et al., iScience 26, 107541
September 15, 2023 ª 2023
https://doi.org/10.1016/
j.isci.2023.107541
iScience
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Article
Techno-economic analysis of residential
building heating strategies for cost-effective
upgrades in European cities
Fei Yu,1,2,3,4,8 Wei Feng,1,2,5,8,9,* Maohui Luo,6,8 Kairui You,1 Minda Ma,2 Rui Jiang,1 Jiawei Leng,3,7 and Liqun Sun1
SUMMARY
The energy crisis in Europe requires cost-effective evaluations of residential heating strategies to reduce
costs and mitigate greenhouse gas emissions. This research studied different heating systems in China and
Europe. Based on heating energy surveys, simulation models were developed and further expanded for
European cities. Monte Carlo analyses were conducted to understand the heating demand and utility
costs in Rome, Madrid, and Athens. The sensitivity analysis found that electrifying heating systems with
heat pumps can reduce household heating costs and mitigate European cities’ dependence on natural
gas. However, the high upfront investment may hinder the cost-effective deployment of high-performance heat pump systems. Building envelope retrofits can also provide plausible energy savings despite
relatively long payback periods. Financial incentive analyses were conducted to quantify how fiscal measures can improve technologies’ techno-economic performance. Finally, the paper provided policy recommendations on future building cost-effective retrofits and heating electrification in Europe.
INTRODUCTION
Heating is an important energy use in buildings. According to International Energy Agency (IEA) data, almost half of the energy demand for
buildings was used for space and water heating globally in 2021, leading to 2450 million tons of direct carbon dioxide (CO2) emissions.1 Space
heating is the largest end-use energy consumption, accounting for 66%, 37%, and 54% of residential energy use in Europe, the US, and China,
respectively.2,3
Among all fuel types used for heating, natural gas is currently the most common, accounting for 42% of the global heating energy demand
in 2021.1 The share of natural gas in the heating mix varies among countries. In Europe, most space heating is provided by fossil-based systems.4 Boilers and furnaces burn natural gas and accounted for over 40% of the heating energy demand in 2021, while electrical heating systems accounted for 30%.5 Natural gas also plays a dominant role in the US and UK, accounting for more than 60% and 90% of the heating mix,
respectively.1,2 In China, while natural gas currently accounts for 20% of heating energy use, a growing trend toward increased natural gas use
is foreseen, considering China’s household coal-to-gas subsidies policy that has been in place since 2017.1,6 As coal still fuels 16% of the heating mix in China, any policy that aims to switch from coal-fueled boilers to gas-fueled boilers would massively promote natural gas consumption in China.1,6
The worldwide preference for natural gas in space heating systems has been due mainly to the low operational cost of natural gas. Electricity has become attractive in many countries,7 but often a more expensive method of heating compared to natural gas.8 In European countries, for example, electrical heating tariffs can be up to three times higher than natural gas tariffs.1 However, the energy crisis in Europe has
dramatically increased household energy costs.9 The hike in natural gas tariffs makes natural gas heating systems more expensive to operate.8
Given the possible shortage of natural gas supply and the continuous hike of natural gas tariffs in Europe, strategies for efficiently operating
and electrifying heating systems have attracted increased attention, although electric tariffs have also increased.10,11
Globally, building electrification is a key step to reducing CO2 emissions in the building sector.12,13 With the continuous decarbonization of
European power systems, electrifying building end-use demands has been discussed widely in energy policy development.14 Many countries
have planned to use electric heat pumps for space heating and replace existing natural gas heating systems.15,16 The IEA estimates that heat
1Institute of Technology for Carbon Neutrality, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
2Lawrence Berkeley National Laboratory, 1 Cyclotron Road, MS 90-2112, Berkeley, CA 94720, USA
3Southeast University, Architecture Department, Nanjing 210008, China
4Beijing University of Technology, Faculty of Architecture, Civil and Transportation Engineering, Beijing 100124, China
5Faculty of Materials Science and Energy Engineering, Shenzhen Institute of Advanced Technology, Shenzhen 518055, China
6Tongji University, School of Mechanical Engineering, Shanghai 201804, China
7Nanjing Urban Planning Design Institute of Southeast University, Nanjing 210096, China
8These authors contributed equally
9Lead contact
*Correspondence: w.feng@siat.ac.cn
https://doi.org/10.1016/j.isci.2023.107541
iScience 26, 107541, September 15, 2023 ª 2023
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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pumps have the global potential to reduce global CO2 emissions by at least 500 million tons by 2030.17 Research shows that heating electrification can achieve a 30%–40% reduction in greenhouse gas emissions in California.15 In China, switching from fossil fuels to decarbonized
ones could lead to 19% energy savings.18 In Europe, energy transition policies have been developed to reduce reliance on fossil fuels for
heating.19,20 Despite the potential benefits of heat pumps, the adoption rate remains limited in Europe. Policymakers are also worried
that large-scale heat pump adoption can result in a surge in grid peak power demand and possible power system congestion.
Apart from building electrification, building envelope retrofits on walls, roofs, and glazing systems can be cost-effective in energy efficiency retrofits.21,22 This includes applying insulation with good thermal resistance, implementing heat recovery from naturally ventilated
air, plugging leaks in the walls to keep air infiltration at low levels, and adopting window systems with insulating glazing and framing with
low heat flow.18,23 More recently, innovations have been made by integrating renewable energy such as photovoltaic with building envelopes
to further reduce a building’s energy demand.24,25 With building envelope thermal performance improvement, the space heating demand
would be greatly reduced, even to near zero.26 In the US, a 62% reduction in residential building energy consumption is estimated due to
upgrading the thermal resistance of the envelope and other characteristics.27 In China, the combination of space conditioning and building
envelope measures is assumed to achieve 48% energy savings.18 In summary, upgrading the building envelope with heating equipment efficiency and operational control is beneficial to both energy savings and carbon reduction.
Understanding the cost benefit of building retrofits is vital to promoting building electrification and building envelope efficiency improvement. There are still economic, regulatory, standards, and financing barriers in the existing building retrofit market, and the high upfront cost
has become one of the major barriers.28,29 In addition to the high capital costs, aspects including climate conditions, operational behaviors,
and technology efficiency all have an impact on the techno-economic performance of technologies, as well as their market potential.29–31 To
deploy cost-effective solutions, an in-depth investigation between the upfront cost and operational savings is needed to understand the economic viability of each strategy.32 There are studies utilizing the lifetime levelized cost to comparatively evaluate technologies with different
heat sources.33,34 While existing research included certain cost data such as technology investment costs, maintenance costs, and fuel costs,
the analysis of space heating retrofit was not conducted in a systematic way to combine all the cost factors together with building technology
performance data and policy factors. In addition, other retrofit benefits such as property value enhancement, occupants’ comfort improvement, and environmental benefits such as CO2 emission reduction all add to the benefits side of strategy promotions.35,36
Although building retrofitting is widely studied, there is very little understanding of the cost benefit of residential heating systems in
response to the energy crisis, the possible shortage of natural gas supply, and the hike of energy prices in Europe. To mitigate European
cities’ dependence on using natural gas for winter space heating, this study conducted a techno-economic analysis of residential building
space heating focusing on heating system electrification and building envelope performance retrofitting. The goals of this research are as
follows.
Develop a novel space heating techno-economic analysis method using Monte Carlo coupling with energy simulation tools;
Provide the techno-economic potential of electrifying residential heating considering the energy tariffs, building envelope thermal
integrity, and residents’ space heating operational behaviors;
Quantify the impact of financial incentives on improving the cost benefit of heat pump space heating based on appliance efficiency and
market prices; and
Provide result-based policy recommendations for existing building retrofitting and heating system electrification in European cities.
To answer these questions, the research was conducted in several steps (Figure 1). It started with collecting household heating energy
data, using Shanghai as an example. Based on the survey data and heating energy and utility bill data collection, simulation models were
developed to calculate the energy cost with various heating systems. With the successful validation of the simulation model in Shanghai,
we then applied the methodology to three European cities, namely Rome, Madrid, and Athens, which have winter heating degree days similar
to Shanghai. The study considered single-family and multi-family building types with three different heating systems: heat pump heater,
radiant floor, and room radiator. Data from the existing literature were obtained on European buildings’ envelope properties, heating operational conditions and user behaviors, and heating energy demand. Simulation models of European buildings were calibrated using collected
literature data, and a series of Monte Carlo sensitivity analyses were conducted to understand different heating systems and envelope impacts on heating energy demand. Given the hikes in energy prices in Europe, techno-economic analyses were conducted to evaluate the
heating energy and cost-saving opportunities of heating electrification using electric heat pumps, as well as of retrofitting existing buildings.
This study’s goal was to provide a novel techno-economic analysis method for residential building space heating and provide quantitative
cost-effective policy recommendations during the energy crisis.
RESULTS
Heating energy survey and data collection in Shanghai
To understand the heating systems, operation behaviors, and energy demand in residential buildings, the research started with a heating data
survey and collection (see STAR Methods). The two major heating systems we studied in Shanghai were air-source heat pumps and radiant
floor heating systems. By analyzing the heating energy data, we found that occupants have different operational behaviors when using the two
heating systems. From the ‘‘partial time and partial space’’ pattern to the ‘‘full-time and full-space’’ fashion, the differences in heating system
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Figure 1. Research methodologies
operational behaviors result in distinct heating energy demands (Figure 2). The annual heating energy use intensity (EUI) for heat pump systems varied from nearly 0 kWh/m2 to over 30 kWh/m2, while the cases using radiant floor systems could reach over 50 kWh/m2. The range of
distribution indicates that user behavior could largely affect the heating energy demand. Energy-efficient behavior such as the ‘‘partial time
and partial space’’ pattern should be recommended in the sense of energy savings.
On the other hand, user behavior tends to be combined with heating system types. In general, when using air-source heat pump systems,
the occupants tend to only turn on the heat pumps when heating is needed in the occupied spaces, thereby using the ‘‘partial time and partial
space’’ pattern. In contrast, due to the large thermal inertia of the radiant floor heating system, occupants tend to turn on the system continuously for a couple of hours in the whole household, applying the ‘‘full-time and full-space’’ pattern. As a result, the annual EUI for radiant floor
heating was relatively larger than that for heat pump systems: 17.4 kWh/m2 compared with 4.7 kWh/m2 on average. Thus, the operational
behavior tendency hindered behind the heating systems would affect the cost-benefit comparison of retrofitting among heating systems.
Heating energy use intensity in European cities
Based on the Shanghai data survey and collections, energy simulation models were developed, calibrated, and further expanded to European
circumstances (see STAR Methods, and Tables 1 and 2).37–40 Both multi-family and single-family residential buildings were involved (Figure 3).
In addition to the air-source heat pump and radiant floor heating systems, the simulation modeling work also considered the hot water
Figure 2. Surveyed heating energy consumption with air-source heat pump and radiant floor heating systems
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Table 1. The weather characteristics of the four cities studied37
HDDs (18 C)
City
99% Heating dry-bulb temperature
Yearly average relative humidity
Shanghai, China
1711
1.8 C
73%
Rome, Italy
1558
0.1 C
77%
Madrid, Span
1880
2.9 C
69%
Athens, Greece
1112
3.5 C
69%
radiator system commonly seen in Europe. Based on the experience learned from the Shanghai buildings, the simulation analysis adopted
two building operational patterns: (1) a normal pattern that operates buildings with a ‘‘full-time and full-space’’ mode, and (2) an energy-efficient pattern that operates buildings with ‘‘partial time and partial space’’ control. Building envelope thermal properties were normalized
based on common values found in the literature (Table 3).38–57 The normalized envelope system has a value of 0, which indicates that the
envelope has the best performance found in literature, with the best thermal insulation for walls, roofs, and fenestrations,42 while a value
of 1 indicates that the building envelope is not well insulated.43
To evaluate the impact of building envelope thermal performance on building energy use for each residential building type and heating
system, this study generated 800 Monte Carlo sensitivity analysis models based on different building envelope performances (Figure 4). The
modeling results (Figure 5) show the multi-family heating energy consumption in Rome. The sensitivity analysis indicated that the heating
system types, user behaviors, and envelope properties together could greatly affect the heating energy demand. Among all studied heating
systems, the heat pump heating system has the lowest EUI, while radiant floor heating has the largest EUI. The boiler and radiator system
consume more heating energy than the heat pump system in general despite the user pattern. Moreover, the level of average heating
EUI in Rome when using the heat pump space heating system is similar to that in Shanghai.
Efficient energy use behaviors, such as shorter hours of operation and lower indoor air temperature setpoints, can significantly reduce
heating energy demand. However, the amount of energy saved by changing energy use behavior is largely affected by the building envelope’s thermal properties. According to Figure 5, as the envelope normalized value decreases, the range of heating EUI decreases. This indicated that with a better-performed envelope, the energy-saving potential caused by user behaviors tends to be smaller.
Heating energy cost is tightly connected with heating energy consumption. Annual heating utility bills were calculated for single-family and
multi-family building types in the three European cities (Figure 6). Electricity and natural gas tariffs dated August 2022 were used to understand the space heating bill per building floor space (Table 4). Similar to the energy intensity analysis, the heat pump heating system demonstrated the lowest heating cost in three cities. Having good energy usage behaviors by operating heating with fewer hours and lowering indoor air temperature setpoints can reduce approximately 50% of heating energy bills compared with operating a building in a full-time and
full-space fashion. Additionally, despite the heating systems, multi-family buildings have smaller heating costs than single-family buildings on
average. One of the reasons is that the multi-family building model has a more compact layout and surface-to-volume ratio. The energy cost
intensity difference between multi-family and single-family buildings becomes larger when using radiant floor systems, and smaller when using radiator or heat pump systems with partial time and partial space control.
Techno-economic analysis of electrifying residential space heating
As electric heat pump heating is favored in this energy crisis,10 it is important to understand the cost benefit of heat pump heating systems by
retrofitting a building and replacing the existing natural gas boiler with room radiators or radiant floor heating systems. We investigated the
Table 2. Reference cases for the Europe model calibration and the calibration results
Case A38
Case B39
Case C40
Location
Italy
Italy
Spain
Building type
Multi-family
Single-family
Single-family
U-wall [W/m2K]
0.60
0.30
1.00
0.23
U-roof [W/m2K]
0.60
0.25
0.65
0.19
U-window [W/m2K]
3.28
3.40
3.44
Infiltration [h1]
1.0
1.0
0.6
Heating system
gas boiler radiator
gas boiler radiator
gas boiler radiant floor
Heating setpoint [ C]
23
20
20
Operation hours [h]
9
10
6
7
EUI reported [kWh/m2]
31.78
37.85
21.10
35.20
10.56
EUI calibrated [kWh/m2]
31.87
37.08
21.00
34.70
10.30
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B
Figure 3. Base model geometry and floor plan of (A) multi-family and (B) single-family building
major heat pump air conditioners sold in the European market by selecting products with the energy efficiency of labels A, A+, A++, and
A+++.58 Heat pump air conditioners’ per-kW cost and coefficient of performance (COP) in the heating mode were sampled in this study
in the European market, as shown in Figures 7A and 7B.59 Heat pump system life cycle costs were also calculated by considering both equipment investment costs and installation and maintenance costs.60
In general, high-performance heat pump air conditioners tend to be more expensive and have relatively high upfront investment costs. The
heating energy bill would reduce when applying the heat pump system to replace the radiator heating or radiant floor heating system. Figure 5C shows the techno-economic analysis of a heat pump air-conditioner heating system replacing a traditional radiator and radiant floor
system in Athens. The techno-economic analysis was conducted by comparing the efficiency and cost data of heat pumps labeled in A, A+,
A++, and A+++ categories with their life cycle energy cost savings. In this analysis, we also considered the building’s operational and energy
use behaviors, as well as the building envelope thermal properties.
The techno-economic analysis indicated that heat pump air conditioners enjoy a good cost benefit when replacing radiant floor heating
systems. However, when replacing the natural gas boiler and radiator system, the overall payback periods are much longer. Considering that
most heat pumps’ average lifetime is approximately 10 years, using heat pumps to retrofit a building and replace the traditional radiator systems may not be a cost-effective solution from a cost-benefit heating system life cycle assessment point of view. The analysis also found that
heat pumps with the ‘‘A’’ label tend to have better payback periods compared with high-performance heat pumps. The main reason is that the
high upfront investment cost of high-performance heat pumps overwhelms the energy savings throughout the equipment’s lifetime. However, the high-performance heat pump does reduce a building’s CO2 emissions; Figure 7D demonstrates the CO2 emission reduction per
building floor space. Changing from no matter radiator or radiant floor systems, the heat pumps with the ‘‘A+++’’ label always perform better
in regards to CO2 emissions reduction than those with the ‘‘A,’’ ‘‘A+,’’ or ‘‘A++’’ label when under the same circumstance of other variables like
envelope properties and operation behaviors.
The cost benefit of heat pump retrofitting an existing building also varies based on the actual number of heating operational hours and
envelope properties in a building. Figure 8 indicates that buildings that use heating for 12 h a day tend to have a good payback period
compared with buildings that operate fewer hours per day. When the heating operation is less than 8 h per day, it is unlikely to pay back within
10 years by replacing the heating system from radiator to heat pump (Figure 8A). Moreover, for buildings with high-performance envelope
properties, a long payback period may occur. In contrast, as the envelope property performance gets worse, the payback period would
decrease dramatically. For buildings originally using radiant floor heating systems, heating system electrification is always worth consideration
unless the existing building already has a very high-insulated envelope (Figure 8B).
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Table 3. Sensitivity analysis parameter settings
Parameter
Envelope
U-wall [W/m2K]
Reference
Range
Mean
Std.
Number
of cases
Mora et al.21; Mora et al.38; de Rubeis et al.39;
0.2–1.7
0.95
0.25
800
0.2–2.5
1.35
0.38
0.9–5.9
3.4
0.83
0.3–1.3
0.8
0.18
Pérez-Andreu et al.40; Suárez et al.41; Escandón
et al.42; Escandón et al.43; Escandón et al.44;
Mastellone et al.45; Echarri-Iribarren et al.46;
Grygierek et al.47; López-Ochoa et al.48; Ounis
et al.49; Pohoryles et al.50; Haneef et al.51;
Canale et al.52; Barbosa et al.53
2
Mora et al.21; Mora et al.38; de Rubeis et al.39;
U-roof [W/m K]
Pérez-Andreu et al.40; Suárez et al.41; Escandón
et al.42; Escandón et al.43; Escandón et al.44;
Mastellone et al.45; Echarri-Iribarren et al.46;
Grygierek et al.47; López-Ochoa et al.48;
Pohoryles et al.50; Haneef et al.51; Canale
et al.52
2
U-window [W/m K]
Mora et al.21; Mora et al.38; Pérez-Andreu
et al.40; Suárez et al.41; Escandón et al.43;
Escandón et al.44; Mastellone et al.45; EcharriIribarren et al.46; Grygierek et al.47; Pohoryles
et al.50; Haneef et al.51; Canale et al.52; Barbosa
et al.53; Lizana et al.54
1
Infiltration [h ]
de Rubeis et al.39; Pérez-Andreu et al.40; Suárez
et al.41; Escandón et al.42; Escandón et al.43;
Escandón et al.44
Setpoint [ C]
Mora et al.38; de Rubeis et al.39; Pérez-Andreu
16–20
et al.40; Suárez et al.41; Mastellone et al.45;
Echarri-Iribarren et al.46; Grygierek et al.47;
Laskari et al.55; Laskari et al.56; Madonna and
Bazzocchi57
Operation hours [h]
Mora et al.38; de Rubeis et al.39; Pérez-Andreu
6–10
et al.40; Suárez et al.41; Escandón et al.42;
Escandón et al.43; Escandón et al.44;
Mastellone et al.45; Barbosa et al.53; Laskari
et al.55; Laskari et al.56; Madonna and
Bazzocchi57
City
Athens, Rome, Madrid
3
Building type
Multi-family, single-family
2
Heating system
Radiant floor, radiator, air-source heat pump
3
Techno-economic analysis of building envelope retrofitting for space heating
Retrofitting existing buildings’ envelope systems can also produce good energy savings. The techno-economic performance of building envelope retrofitting is influenced by the before-or-after retrofit envelope thermal performance. Here, we investigated two retrofit pathways. In
the first case, we retrofitted buildings from the worst envelope conditions (a normalized value of 1) to different post-retrofit conditions
(Figures 9A, 9C, and 9E); in the second case, we assumed buildings were retrofitted to the best conditions we can see in the market (a normalized value of 0) from different prior-retrofit conditions (Figures 9B, 9D, and 9F). We used buildings with radiant floor heating systems in Rome
as an example to demonstrate the cost benefit of envelope retrofitting.
The results show that when the difference between before- and after-retrofit conditions is big (meaning a building is retrofitted from poor
thermal insulated conditions to very good thermal insulated conditions), the retrofit tends to have a shorter payback period. Longer heating
operation hours also generate a potentially good cost-benefit ratio through envelope retrofitting, as energy cost savings are significant. Since
building envelope materials tend to have a 30-year or longer lifetime compared with heat pump air conditioners,61 the retrofit activity can be
prioritized to candidate buildings with poor insulation, longer hours of operation, or poor heating usage behaviors. Small incremental retrofits
of buildings are not recommended, as the payback period tends to be long.
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Figure 4. Monte Carlo method-based building energy performance analysis
Incentive policies and impact analysis
To facilitate heat pump electrification and building envelope retrofitting, policies have been developed in European countries.62 During the
energy crisis in Europe, the European Commission proposed the REPowerEU Plan in May 2022 to reduce the dependency on fossil heating.63
The plan targets to install 20 million heat pumps in the European Union (EU) by 2026 and nearly 60 million by 2030.64 Because of the plan, sales
of heat pumps in EU nations have increased by 40% year-on-year in 2022 than 2021 (49% more air-to-water heat pumps and 19% more air-toair heat pumps).65 Countries like Norway, Denmark, Netherlands, Germany, Belgium, Austria, and France have set policies to ban fossil fuel
boilers in buildings.66 Spanish building regulations have also set requirements for building owners to install renewable hot-water heating,
including heat pumps, for new construction and existing building retrofitting.67
In addition to target development, financial incentive policies have also been proposed to reduce the upfront installation costs through
government grants or tax incentives. In the Netherlands, the Investment Subsidy for Sustainable Energy and Energy Saving allows homeowners to apply for a minimum of 500 V subsidy per heat pump, with a minimum capacity of 400 kW.68 Italy has taken tax incentives such as the
‘‘Superbonus’’ and ‘‘Ecobonus’’ to accelerate energy efficiency measures including heating system replacement with heat pumps. The Superbonus tax rebates offer tax credits covering a maximum of 110%, 70%, and 65% of installation costs by 2023, 2024, and 2025, respectively, for
centralized heat pump systems.69,70
Subsidizing heat pump operation costs with lower utility tariffs has also been adopted by several European countries. In the Netherlands,
subsidies are given to household consumers, resulting in electricity costs 76.4% lower than the EU average in 2022.71 In 2022, Greece also
offers electricity tariff subsidies for residential users 0.221 V/kWh per household for monthly consumption up to 500 kWh.72,73
As for existing building retrofit projects, the EU countries have made great efforts with the inauguration of the European Green Deal package. Targeting 55% greenhouse gas (GHG) reductions by 2030 and net zero by 2050, the EU has developed the Renovation Wave strategy and
introduced a deep retrofit standard through the Energy Performance of Buildings Directive.74 These long-term energy efficiency renovation
Figure 5. Heating energy use intensity for multi-family residential buildings in Rome
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Figure 6. Heating energy cost intensity for multi-family and single-family buildings in Rome, Madrid, and Athens
strategies, including the building thermal insulation improvement, are enhanced by the 2022 REPowerEU Plan.75 Many EU countries have
developed codes, standards, and certifications to promote energy-efficient building retrofits. For example, Spain has developed Royal Decrees, with requirements on building codes, energy certification, and existing building retrofitting.76 Italy has set out Energy Efficiency Action
Plan and revised the standard UNI/TS 11300 Energy Performance of Buildings to offer minimum requirements for building energy efficiency.77
EU member states are encouraged to use fiscal measures to promote energy savings and overcome financial barriers through government
funding, low-interest loans, and tax incentives. The German Development Bank (KfW) provides preferential loans and grants, in collaboration
with private banks, to support building envelope thermal retrofits.78 Spain has several financial aid programs, such as the PAREER-CRECE
Program, the MITMA State Housing Plan, and the Multiregional OP for Spain, which aim to accelerate energy efficiency retrofits.76 Tax incentives are also widely adopted for building envelope thermal performance improvement. In Germany, 20% of up to 6000 V in labor costs can be
deducted from personal tax liability.79 The Netherlands provides tax deductions covering 45.5% of the investment cost of qualified energyefficient technologies through Energy Investment Allowance.80,81 To qualify for the Italy Superbonus tax deductions, a building’s thermal insulation improvement should cover at least 25% of the gross surfaces, and the envelope U values should reach the requirement of Italy’s building code requirements.70,82
To understand how financial incentives promote the cost-effectiveness of space heating electrification and building envelope retrofitting,
this study conducted an incentive sensitivity analysis. We investigated the different cost-share of financial incentives to cover heat pumps or
building envelope retrofitting and recalculated the techno-economic performance of heat pumps and building envelope retrofitting. The results showed that the incentives are effective in cutting heat pumps’ initial investment cost and effectively reducing the payback period (Figure 10A). A relatively high incentive rate is needed to make high-efficient heat pump air conditioners cost-effective, such as those with an
A+++ label. Similarly, the techno-economic performance of building envelope retrofitting is also improved with incentives to reduce initial
costs (Figure 10B). With a high incentive rate, buildings with original poor thermal performance can pay back within an acceptable period of
less than 30 years. Small incremental retrofits require higher incentives to achieve cost-effectiveness. Therefore, the financial incentives need
to be developed in conjunction with high-performance energy standards to guide cost-effective envelope retrofitting.
Table 4. Electricity and natural gas tariffs in Italy, Greece, and Spain7
Electricity [V/kWh]
Natural gas [V/kWh]
Normal
high
Aug 2022
normal
high
Aug 2022
Italy
0.19
0.5
0.47
0.075
0.185
0.18
Spain
0.195
0.4
0.35
0.072
0.165
0.165
Greece
0.18
0.3
0.24
0.05
0.165
0.165
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A
C
B
D
Figure 7. Techno-economic analysis of applying heat pumps to retrofit building heating systems
DISCUSSION
This study developed a novel techno-economic analysis method to quantifying the cost benefit of residential space heating system retrofitting
in European cities. The results showed that electrifying space heating and building envelope retrofitting still have significant cost barriers.
To overcome these cost barriers, comprehensive supporting policies are needed to scale-up air-source heat pump deployment in residential
buildings in Europe. Building codes and standards need to be updated, and space heating electrification needs to be encouraged. Financial
incentives and support need to be set up to help residents mitigate the high upfront investment cost of purchasing and installing high-performance heat pump systems. Incentives can also be set up to encourage building envelope retrofits and shorten the retrofit payback period.
Apart from policies, technology improvements are also needed in the long run. The maturity of high-performance heat pump space heating systems may help to reduce the upfront cost. The continuous heating electrification and wide adoption of heat pumps in China could also
reduce heat pump costs sold in the European Union. Expanding the service life of heat pump air-conditioning systems would benefit longterm usage. Smart heating operational control based on monitoring indoor thermal comfort would stimulate behavioral changes.
Electrifying space heating systems can also bring challenges to European power systems, such as increasing the peak power demand and
causing power transmission and distribution system congestion. Such challenges must be solved before large-scale electrification can be carried out. The issue could be solved by upgrading power transmission and distribution systems, installing distributed energy resources, and/or
implementing heat pump demand response programs. Techno-economic analyses are needed to understand which solution or combination
of different solutions can offer the optimal cost benefit.
A
B
Figure 8. Techno-economic analysis of applying a heat pump to retrofit buildings with different hours of heating operation
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C
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Figure 9. Techno-economic analysis of building envelope systems retrofitting for single-family buildings in Rome
On the other hand, even though heat pump air conditioners offer good techno-economic performance and avoid using natural gas, the
radiator and radiant floor space heating systems could offer better thermal comfort. More studies are needed to understand the thermal comfort and indoor environment when using heat pump systems for space heating in Europe. The improvement of indoor thermal comfort remains a future challenge for heating system electrification.
Conclusion
In response to the European energy crisis, this paper conducted an in-depth analysis to evaluate the cost benefit of residential heating under the
hike of energy prices. A techno-economic analysis was performed with dynamic couplings of building envelope and user behavior factors. The
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B
Figure 10. Impact of financial incentives to cover heat pumps and building envelope retrofits initial investment cost and shorten payback periods
study compared the performance of heat pump systems across different energy labels and conducted techno-economic analysis on the costeffective solutions for residential building space heating. Based on the quantitative research results, recommendations were provided for scaleup heating system electrification and building envelope performance retrofitting to reduce the reliance on natural gas for winter space heating.
Techno-economic analysis of different heating systems in European cities shows that heat pump air-conditioner heating systems offer low
energy intensity compared with radiator and radiant floor systems. Adopting better building operational behaviors such as ‘‘partial time and
partial space’’ can also greatly reduce heating energy demand. Because of the hike in natural gas costs in the European Union, switching from
natural gas heating systems to electric heat pump air conditioners can greatly reduce heating utility bills. Depending on the heat pump air
conditioners’ efficiency and cost, the payback period from investing in heat pump systems also varies. A high-efficient heat pump system with,
for example, an A+++ label may not demonstrate the best techno-economic performance due to its high upfront cost, even though it produces good energy savings and GHG emissions reduction. Retrofitting a building from poor envelope conditions to good thermal integrity
often demonstrates a good payback period. In addition, heat pumps and envelope retrofitting are recommended for buildings that operate
heating systems for long periods.
Furthermore, the paper investigated the financial incentive policies implemented in Europe and analyzed their impact on enhancing the
techno-economic performance of heat pumps and building envelope retrofits. This study found that providing financial incentives to highefficient heat pumps and building envelope thermal integrity improvement can effectively shorten the technologies’ payback period. A
high incentive rate is needed to make high-efficient heat pumps cost-effective. Therefore, financial incentive policies need to be developed
in conjunction with building energy standards to guide cost-effective building heating system retrofits. The quantitative techno-economic
analysis can serve as a data source for decision-makers to develop new policies.
Overall, besides the technical findings, the model and framework developed in this study can be widely used for the techno-economic
analysis of other technologies. It also can be used as a framework to assess building codes and appliance standards. The tool can also
help policymakers to evaluate the effectiveness of incentive policies based on technology and human behaviors.
Limitations of the study
In this research, the August 2022 energy prices were applied for techno-economic analysis. The prices include both natural gas and electricity
tariffs, indicating how both prices changed during the energy crisis. However, large-scale electrification can also lead to an increase in electricity demand and a hike in electricity prices. This, in turn, will impact the cost-effectiveness of heat pump electric heating. The social-economic connection between heat pump adoption and consequent electricity price change needs further investigation.
It is noticed that the techno-economic analysis is only conducted for existing building retrofit. In regard to new construction, as the
upfront investment cost of heat pumps would be lower than that of existing building retrofits, it is expected that electrifying space heating
in new construction would have better techno-economic performance. For existing buildings, possible costs associated with the dismantling and disposing of the existing heating system components such as gas boilers, pipes, and heating radiators can also increase the cost
of upgrading a heating system. The aforementioned costs would make the heat pump’s payback periods longer. It is necessary to note
that air-source heat pumps can be operated in heating mode during the winter and cooling mode during the summer. Should existing airconditioners be inefficient, upgrading high-performance heat pump systems can also lead to cooling energy savings and potentially
shorten the payback period of heat pump systems. However, as some European buildings are not equipped with mechanical cooling
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systems, and tend to operate with natural ventilation or fans, installing heat pumps for cooling can lead to changes in occupants’ cooling
behaviors and increase cooling energy use. Further techno-economic studies are needed to fully consider cooling energy consumption
under different scenarios.
Finally, this research mainly focused on heating electrification in southern European cities, as heat pump systems have certain limitations
when applied in low-temperature outdoor environments. The heating capacity and efficiency of conventional air-source heat pumps decrease
significantly as the outdoor temperature decreases.83 Although achievements have been made in the heat pump to minimize heat leakage,
develop defrost technology, prevent condensation, and withstand extremely cold temperatures, the relatively high upfront cost is still the
main barrier for market-scale applications.84 Advanced heat pump technologies have been developed to achieve 100% of the rated heating
capacity (COP = 3.52) at 15 C and 75% of the heating capacity at 25 C, with a cost of 310.83 V/kW.85 More studies are needed to understand the cost-effectiveness of heating electrification in northern and central Europe with the maturity and wide adoption of heat pump technology for space heating.
STAR+METHODS
Detailed methods are provided in the online version of this paper and include the following:
d KEY RESOURCES TABLE
d RESOURCE AVAILABILITY
B Lead contact
B Materials availability
B Data and code availability
d METHOD DETAILS
B Literature review
B Energy survey and simulation model calibration
d QUANTIFICATION AND STATISTICAL ANALYSIS
B Monte-Carlo sensitivity analysis
B Techno-economic analysis
SUPPLEMENTAL INFORMATION
Supplemental information can be found online at https://doi.org/10.1016/j.isci.2023.107541.
ACKNOWLEDGMENTS
This manuscript has been authored by an author at Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231 with the
U.S. Department of Energy. The U.S. Government retains, and the publisher, by accepting the article for publication, acknowledges, that the
U.S. Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes.
AUTHOR CONTRIBUTIONS
Conceptualization, F.Y., W.F.., and M.L.; literature analysis, F.Y., W.F., and M.L.; writing—original draft preparation, F.Y., W.F., and M.L.;
writing—review and editing, F.Y., W.F., M.L., K.Y., M.M., R.J., J.L., and L.S.; supervision, W.F.; project administration, W.F.; funding acquisition,
W.F. All authors have read and agreed to the published version of the manuscript.
DECLARATION OF INTERESTS
The authors declare no competing interests.
Received: January 20, 2023
Revised: May 8, 2023
Accepted: July 27, 2023
Published: August 3, 2023
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STAR+METHODS
KEY RESOURCES TABLE
REAGENT or RESOURCE
SOURCE
IDENTIFIER
Software and algorithms
jEplus
https://www.jeplus.org/
Energyplus
https://energyplus.net/
Other
Energy price data
IEA8
Weather data of studied cities
World Meteorological Organization WMO37
Discount rate
Exchangerate101
Split heat pump air conditioning data
ClimaMarket59
installation cost for one mini-split heat pump air conditioner
Right Casa60
GHG emission factor
Eleonora et al.102
building envelope retrofit installation costs
Mora et al.21
RESOURCE AVAILABILITY
Lead contact
Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Wei Feng (w.feng@
siat.ac.cn).
Materials availability
This study did not generate new unique reagents.
Data and code availability
d All data reported in this paper will be shared by the lead contact upon request.
d This paper does not report the original code.
d Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.
METHOD DETAILS
Literature review
Techno-economic analysis (TEA) is widely used to evaluate the technical and economic potentials when adopting certain technologies.86 Previous research has used TEA to evaluate the potential of technology investment decisions, and to guide technical solutions toward improving
the overall system value proposition.87 TEA also involves sensitivity analysis identifying parameters that have the dominant influence on system performance.88
To analyze economic performance, cost estimation models have been developed in the following formats: per-unit model, segmenting
model, cost-index model, power-sizing model, and learning curve.89 These models can be combined to attain comprehensive solutions for
intricate problems. The per-unit model is commonly applied when the unit cost remains relatively constant, such as in estimating labor and
utility consumption costs.90 The segmenting model partitions the total cost of a complex system into individual processes or components.91
The cost index model utilizes published data, such as the Consumer Price Index (CPI), to account for historical cost variations.92 Meanwhile,
the power-sizing model operates on the premise that equipment costs per unit of capacity decrease as the size of the equipment increases.93
Thus, it has wide applications in estimating the cost of equipment or a complete processing facility. The learning curve model, also referred to
as the experience curve, demonstrates that a product’s cost decreases in proportion to its cumulative output.94 Therefore, the model can be
leveraged to forecast future trends. In addition, several indicators, indices, and analytical techniques can be employed to evaluate overall
economic performance, such as the return-on-investment (ROI) metric, payback period (PBP), gross profit (GP), and net present value (NPV).88
On the other hand, TEA frequently experiences physical modeling variability and integrated data uncertainties.95 Consequently, decisionmakers with risk preferences require crucial information from uncertainty and sensitivity analyses. Typically, uncertainty analyses utilize the
distribution-function-based analytic method, graphical illustration, and simulation.89 The former quantifies the uncertainty in a probability distribution, while the graphical illustration is based on the economic decision tree.96 A common approach used to derive the uncertainty distribution is Monte Carlo simulation.95,97,98 This method involves sampling a probability distribution randomly to solve intractable integration
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problems. By employing the Monte Carlo method, the feasibility of technologies’ techno-economic performance can be assessed, taking into
account the risks and integrated uncertainties from input variables.98
However, the literature includes few studies that use Monte Carlo simulation for building system techno-economic analysis; nor has the
literature developed techno-economic methods for space heating technologies during the European energy crisis. Therefore, this research
developed a novel Monte Carlo method coupled with the building energy simulation method to analyze the techno-economic solutions of
residential building space heating in Europe.
Energy survey and simulation model calibration
In this research, four cities in China and Southern Europe were studied: Shanghai, Rome, Athens, and Madrid. All have close latitudes and
similar heating degree days (HDDs, Table 1) and weather conditions.
To understand heating energy demand in residential buildings, the research began with a heating use survey and energy data collection.
Climatic weather conditions have a strong impact on heating energy demand; thus, we selected buildings in Shanghai for residential household heating energy data collection. Shanghai has HDDs that are similar to those in Southern European cities. Representative heating energy
data in Shanghai can help us further develop simulation models and conduct techno-economic analyses for cities in Southern Europe.
In the survey, the residential heating energy consumption, usage behaviors of heating systems, and indoor thermal environment conditions were all involved. Heat pump heating systems were often operated in ‘‘partial time and partial space’’ usage patterns. The heating system was operated in occupied rooms or spaces when needed, and occupants often turned the heating off when their thermal comforts were
met. In contrast, for the natural gas boiler radiant floor heating system, ‘‘full time and full space’’ usage patterns were often observed. This
means that the heating was operated continuously for a couple of hours and was designed to supply the entire household instead of roombased control. The survey collected data from 890 households with heat pumps and 995 households with natural gas-fired radiant floor heating. According to our survey, most residents turned on their heating system from November to February. The study collected household heating energy data from electricity and/or natural gas utility bills.
Given different heating operational behaviors from Shanghai’s residential buildings, we developed energy simulation models to capture
the different ways to operate heating systems, based on surveyed building envelope thermal performance. The models in this study involved
two typical residential building types: multi-family and single-family. The model for multi-family buildings was a six-floor building based on a
real residential building in Shanghai, China (Figure 3A). The multi-family residential building had six floors. Each floor was 501.85 m2 and consisted of four households. Each household unit included one living room, one kitchen, three bedrooms, two bathrooms, and three balconies.
It served as a home for a family with usually two to six people. The floor height was 3 m and the window-to-wall ratio (WWR) was 18.18% in
general (26.90%, 4.35%, 24.66%, and 4.90% for north, east, south, and west respectively).
The single-family building type is not very common in the urban area of Shanghai but is very common in European cities. Even though we
don’t have the surveyed data for the single-family building, some of the energy use patterns as well as space heating techno-economic analysis carried out later in this study can still be applied to the single-family building. Therefore, we developed a single-family residential building
model (Figure 9B) based on existing literature, suitable for Southern Europe cities.41 The model was a two-floor flat house, with 119.51 m2 floor
space per floor. On the first floor, there were two bedrooms, one restroom, one living room, one kitchen, and a corridor. The second floor was
not specified by the reference and was roughly considered to be the bedroom space. The WWR of the single-family model was 15.38%
(16.55%, 9.49%, 18.95%, and 14.24% for north, east, south, and west respectively).
All the building models faced north-south. The geometry and building floor plan can be found in Figure 9. Three types of heating systems
were modeled in this study: the natural gas boiler and radiant floor, the natural gas boiler and radiator, and the electric heat pump. Based on
the Shanghai survey data, the models were designed with heating systems in the living rooms and bedrooms. Thus, the net conditioned heating areas for multi-family and single-family residences in total were 1847.32 m2 and 182.81 m2 respectively, accounting for 61.35% and 76.49%
of the respective total construction floor space.
The simulation models were calibrated with actual heating energy data collection to ensure that the simulation models can represent the
actual case studies. We calibrated the multi-family building using the collected heating demand data in Shanghai. The building envelope
material properties were compared and adjusted based on relative standards and case investigations. For cases whose building envelope
thermal properties were difficult to obtain through onsite investigation, we tracked the local residential building energy standard based
on the building construction year. For most case buildings built between 2001 and 2010, the energy standard JGJ 134-2001 was applied
in the simulation analysis.99,100 Based on the onsite investigation and existing literature, most of the cases were built with external walls of
concrete cellular blocks with a layer of cement mortar covering the structure internally and externally, while a thermal insulation panel was
placed on the outward face of the walls.100 Roofs were made up of reinforced concrete covered by a cement mortar layer on the inner faces,
while the outer face also presented a cement layer covered by tiles and by a thermal insulation panel.100 The simulation model adopted double-glazed windows with a clear inner pane and a reflective outer pane. The heating setpoint for the radiant floor was 18 C, while the one for
the heat pump was 20 C. Most occupants reported turning on the radiant floor system from 21:00 to 23:00 on weekdays, and from 19:00 to
23:00 on other days. The radiant floor system was often controlled at the whole apartment level by using the air temperature sensor in the
living room. For the heat pump system, the bedrooms and living room were controlled separately using split heat pump air conditioners.
Based on the survey data, the systems in bedrooms were on from 06:00 to 07:00 and from 23:00 to 24:00 on weekdays, while only on from
23:00 to 24:00 on the other days. The heating systems in the living rooms were on from 21:00 to 23:00 on weekdays and from 19:00 to
23:00 on other days.
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The study understands that even though the model was calibrated with Shanghai’s survey data, it cannot be applied directly to Europe given
the difference in the building envelope, equipment efficiency, and occupant behaviors. Therefore, this research further calibrated the multifamily and single-family residential building models for European conditions based on existing literature.38–40 Building envelope thermal properties, infiltration rate, heating system performance, and heating operation data were obtained for calibration with the simulation model (Table 2). The model was expanded from the Shanghai calibrated model with input settings adjusted according to the references. After tuning the
simulation with European case parameters, we simulated the model in EnergyPlus and compared the simulated annual heating energy use intensity (EUI) in kilowatt-hours per square meter (kWh/m2) with actual case heating energy demand. Both the simulated results and the recorded
data for each reference case are presented in Table 2. The similarities between the simulated output and referenced data prove that the models
are calibrated. Thus, after the calibration, the developed simulation model was applied in southern European cities for further analysis.
QUANTIFICATION AND STATISTICAL ANALYSIS
Monte-Carlo sensitivity analysis
Simulating the model with individual cases is not sufficient to understand the dynamics of heating energy demand influenced by various factors. Based on previous surveys and analysis, we observed two major factor groups that have strong impacts on heating energy demand: 1)
building envelope thermal properties; and 2) building operation conditions and occupant behaviors. To address the sensitivity caused by
these factors, a Monte Carlo method-based analysis was developed (Figure 4). We first constructed an input parameter domain by identifying
key factors and their distribution characteristics. Then, Monte Carlo samples were randomly drawn from the input domain based on each input
variable’s probability distribution function to generate multiple variable sample groups. Building energy performance simulations were conducted with sampled groups, and the building energy output distribution was calculated. Finally, sensitivity analysis was performed to
demonstrate the impact of key factors on the energy and cost results. Overall, the Monte Carlo method-based analysis of building performance can be described as follows:
8
< P ðAi Þ/ai
P ðBi Þ/bi
:
f ðai ; bi Þ/E
(Equation 1)
where A represents the building envelope thermal properties; B represents building operation conditions and occupant behaviors; f ðÞ represents the function of building energy performance simulation; PðÞ represents the distribution functions for variables A and B; Ai ; Bi represent
the sampled cases for A and B; ai ; bi represents the sampled random variables; E represents the simulated building energy performance.
After constructing an input variable domain with a large number of samples, the developed energy simulation model can build a corresponding energy output domain.
For input parameter selection and distribution assumptions, a thorough literature review was first conducted to understand how building
envelope thermal conditions and heating operation and occupant behaviors vary from case to case. The study particularly extracted from
existing European studies on building envelope U values (including walls, roofs, and windows), infiltrated rate, space heating setpoint,
and operation schedule.21,37–43,87,89–100 From the literature, we also obtained the lower bounds and upper bounds for building envelope
U values which correspond to respective good and poor thermal performance for walls, roofs, and windows. The same approach was
used to identify the range of building infiltration rates, space heating setpoints, and operation schedules. Detailed parameter ranges and
statistical values collected from existing literature can be found in Table 3.
To represent the building envelope’s thermal properties in the real world, a normal distribution was assumed to make input parameters
cover all reference cases. Thus, the mean value and standard deviation for each metric were calculated to form the normal distribution function (Table 3). On the other hand, the heating setpoint and the operation hours of heating systems in this research were considered to be
evenly distributed. Based on the distribution curves, 800 samples were generated in each variation domain. The distribution of these samples
is presented in the Appendix.
Building envelope measures tend to have a strong correlation with their thermal performance. The literature review found that high-performance buildings have low U values as well as low infiltration rates, while inefficient buildings tend to be leaky and not well insulated in regard to walls, roofs, and windows. It is rare to find a case that has very good thermal properties on one measure but very poor on other measures. Based on the characteristics above, we grouped the generated building envelope variable to create 800 building envelope cases. The
grouping method can significantly reduce the number of simulation runs compared with randomly matrixing one variable with another. Then
the building envelope parameter group was coupled with the heating setpoint and heating operation schedule groups. Thus, the building
thermal properties were studied under different levels of thermal comfort including cases with a lower perceived thermal comfort and poor
thermal properties. A boiler efficiency of 0.85 or air-sourced heat pump heating coefficient of performance (COP) of 3 was used at this stage,
as later analysis will conduct detailed heating equipment efficiency analysis. With all the parameters, Monte Carlo sensitivity analysis was carried out by simulating building energy use for each building type in each city.
Techno-economic analysis
To conduct a techno-economic analysis, the calculated heating energy use intensity (EUI, unit kWh/m2) was used as a key heat energy performance indicator. Then, the energy cost intensity was calculated by using EUI multiplied by the average household energy price. Table 4 shows
the electricity and natural gas tariffs in Italy, Greece, and Spain.7 Each includes the lowest price in normal conditions before the European
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energy crisis, the highest value during the price fluctuation, and a more recent price obtained in August 2022. In this study, we mainly use the
August 2022 energy price, admittedly because energy price fluctuation does pose a strong impact on household heating cost-benefit analysis.
The goal of the techno-economic analysis is to find the most economically viable way to retrofit residential heating systems in Southern
Europe. There are a couple of ways to reduce heating energy demand and cut heating utility bills: 1) electrifying space heating by replacing
natural gas heating systems with electric heat pumps; and 2) retrofitting the building envelope by improving its thermal integrity. To illustrate
the cost-benefit retrofit, a techno-economic analysis was conducted by considering the life cycle and energy savings. We used dynamic
payback periods as the main metric by comparing the capital expenditure (CAPEX) and net present value (NPV) methods:
NPV =
X CFn
n initial investment
(Equation 2)
ð1+iÞ
where n is the period that takes values from 0 to the year n until the cash flows ending period payback period [year]; CFn is the cash flow from
heating energy savings capital gain in year n [V]; and i is the discount rate. In this research, a discount rate of 5% was considered.101 The
payback period is calculated when NPV is equal to 0.
Electrify space heating with a heat pump system
To electrify space heating with heat pumps, the initial capital investment includes the purchase cost of heat pump systems and the installation
labor cost:
Chp = Chp equip + Chp install
(Equation 3)
where Chp is the initial investment for replacing natural gas heating systems with heat pump systems [V]; Chp equip is the total equipment cost
to buy heat pump systems [V]; and Chp install is the heat pump system installation cost [V]. In this study, the costs associated with the dismantling and disposal of the existing system, including the gas boiler, pipes with fittings, and floor heating or radiators, are not considered. The
existing equipment can remain in buildings and will not affect the installation and operation of a heat pump system.
To better compare the technology cost with heating energy saving capital gains, the heat pump investment cost was divided by the building
floor space to obtain the per floor space investment cost. The heat pump investment cost was obtained from split heat pump air conditioning
data from European appliance retailers’ websites.59 Based on each case’s heating demand, the heat pump equipment investment cost for each
case was calculated accordingly. The labor installation cost was obtained from market survey data and existing literature. The installation cost
for one mini-split heat pump air conditioner was 375 V in Spain.60 We assumed that a similar cost scheme can be applied to Italy and Greece.
As heat pump systems often offer high efficiency, the saved energy can reduce CO2 emissions from space heating. In Europe, the emission
factor for natural gas was 0.226 tons of CO2 equivalent per megawatt-hour (tCO2 eq/MWh), while that for electricity was 0.426 tCO2 eq/MWh,
0.343 tCO2 eq/MWh, and 0.22 tCO2 eq/MWh in Greece, Italy, and Spain, respectively.102
Building envelope retrofit
Similar to heat pump electrification retrofit, the building envelope retrofit also requires the total investment in materials cost for walls, roofs,
and windows, as well as the labor cost:
Ctotal = Cwall + Croof + Cwindow + Clabor
(Equation 4)
where Ctotal is the total cost for the building envelope retrofit [V]; Cwall is the material cost of the insulation changes for walls [V]; Croof is the
material cost of the insulation changes for roofs [V]; Cwindow is the material cost of the insulation changes for windows [V]; and Clabor is the
labor cost [V].
Similar to the heat pump cost calculation, we also used the total building cost divided by the building floor space to obtain the per building
floor space envelope retrofit cost. The unit floor space retrofit cost was used to compare with unit floor space energy savings and obtain the
building retrofit payback period.
In this research, a single-family unit in Spain was used as the case for building envelope retrofit analysis. According to Mora et al. (2018), the
unitary cost of the EPS panels and the XPS panels in Spain is 263.78 V/m3 and 267 V/m3, respectively.21 For the windows, Mora et al. (2018)
reported the investment cost of four glazing systems with regard to windows’ U value and solar heat gain coefficient (SGHC) in Europe (see
table below).21 Based on the existing literature, we build a window cost function to calculate the window retrofit investment cost. The labor
cost for the envelope retrofit in Spain was found to be 55.6 V/m2.21
The unitary investment cost of four glazing systems in Europe21
System A
System B
System C
System D
U
1.14
1.10
0.61
0.60
SHGC
0.61
0.35
0.58
0.34
Price [V/m2]
404.33
439.06
477.65
454.49
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