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Identification of cost-optimal and NZEB refurbishment levels for representative climates and building typologies across Europe

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The energy consumptions of the building stock are playing a central role in the energy policy of the European Union. While the Member States are applying the Directives in force, the European Commission is working to update the regulatory framework. Specifically, it is necessary to achieve the great unrealized potential for energy savings in existing buildings. With this aim, the nearly zero-energy building (NZEB) target was introduced, and a comparative methodology framework to calculate cost-optimal levels of minimum energy performance requirements was proposed. This study focuses on the issue of building renovation, and it presents the results obtained with the application of a cost-optimal calculation method for identifying proper retrofit measures to reach cost-optimal levels and NZEB levels. The assessment takes into account an exhaustive set of passive and active renovation options and it was extended to various building types of 60s–70s (residential and non-residential) in a wide range of representative European climatic conditions. A very relevant energy-saving potential was found for all cost-optimal benchmarks, and in many cases, the obtained NZEB refurbishments have resulted interesting also from an economic point of view.
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ORIGINAL ARTICLE
Identification of cost-optimal and NZEB refurbishment levels
for representative climates and building typologies
across Europe
Paolo Zangheri &Roberto Armani &Marco Pietrobon &
Lorenzo Pagliano
Received: 30 November 2016 /Accepted: 4 September 2017 /Published online: 19 September 2017
#The Author(s) 2017. This article is an open access publication
Abstract The energy consumptions of the building
stock are playing a central role in the energy policy of
the European Union. While the Member States are
applying the Directives in force, the European
Commission is working to update the regulatory frame-
work. Specifically, it is necessary to achieve the great
unrealized potential for energy savings in existing build-
ings. With this aim, the nearly zero-energy building
(NZEB) target was introduced, and a comparative meth-
odology framework to calculate cost-optimal levels of
minimum energy performance requirements was pro-
posed. This study focuses on the issue of building
renovation, and it presents the results obtained with the
application of a cost-optimal calculation method for
identifying proper retrofit measures to reach cost-
optimal levels and NZEB levels. The assessment takes
into account an exhaustive set of passive and active
renovation options and it was extended to various build-
ing types of 60s70s (residential and non-residential) in
a wide range of representative European climatic con-
ditions. A very relevant energy-saving potential was
found for all cost-optimal benchmarks, and in many
cases, the obtained NZEB refurbishments have resulted
interesting also from an economic point of view.
Keywords EPBD recast .NZEB .Cost-optimal
calculation .Retrofit measures
Introduction
Motivation
The European building stock consumes approximately
40% of primary energy, and it is responsible for 36% of
the EU greenhouse gas emissions. A significant reduc-
tion of this energy demand is a requisite to meet Europes
GHG emission reduction targets, and buildings are a
strategic sector for the European energy policy. In fact,
it is a pillar of the Energy Union as set by the 2015
Communication
1
of the European Commission (EC).
The Energy Performance of Buildings Directive
(EPBD)together with the Energy Efficiency
Directive (EED) and the Renewable Energy Directive
(RED)defined a framework that creates the conditions
for long-term improvements in the energy performance
of Europes building stock. Without it, the indicative
target at the EU level of at least 27% for improving
energy efficiency in 2030
2
cannot be obtained.
In the frame of the implementation of the European
Directive 2010/31/EU (EPBD recast by the European
Energy Efficiency (2018) 11:337369
DOI 10.1007/s12053-017-9566-8
1
COM/2015/080 final.
2
This will be reviewed by 2020, having in mind an EU level of 30%.
P. Zangheri (*)
Directorate C - Energy, Transport and Climate, Joint Research
Centre (JRC), Ispra, VA, Italy
e-mail: paolo.zangheri@ec.europa.eu
P. Zangheri
DTE-SEN, ENEA, Ispra, VA, Italy
R. Armani :M. Pietrobon :L. Pagliano
end-use Efficiency Research Group, Dipartimento di Energia
(eERG), Politecnico di Milano, Milan, Italy
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Parliament 2010), the EU Member States were asked to
develop policies appropriate to their national situations
and provide the necessary financing to foster the transi-
tion to nearly zero-energy building (NZEB). The EPBD
recast requires that from 2019 onwards, all new build-
ings occupied and owned by public authorities are
NZEBs and all new buildings by the end of 2020.
However, acknowledging the variety in building culture
and climate throughout Europe, the EPBD does not
prescribe a uniform approach for implementing NZEB.
Member States were required to draw up National Plans
for increasing the number of NZEBs, with targets that
may be differentiated for different building categories.
According to paragraph 3 of Article 9, these plans shall
include NZEB definitions reflecting national, regional,
or local conditions, and a numerical indicator of primary
energy use.
Moreover, the EPBD recast asked Member States to
calculate cost-optimal levels of minimum energy perfor-
mance requirements for new and existing buildings by
using the comparative methodology framework
established by the Commission with the Delegated Act
No. 244/2012 (European Parliament 2012a,b)of16
January 2012 (including explanatory guidelines).
This cost-optimal calculation framework involves the
following steps: (i) definition of national reference
buildings representing national building stock, (ii) iden-
tification of energy efficiency measures and packages to
be evaluated, (iii) calculation of primary energy demand
of the reference buildings with the identified energy
efficiency measures, (iv) calculation of global costs
related to each the energy efficiency measure and pack-
age considering long-term expenditures and savings
during the calculations period, (v) sensitivity analysis
for input data, and (vi) derivation of cost-optimal levels
of energy performance requirements.
While the MemberStates are updating their plans, the
cost-optimal approach may be very effective both to
upgrade the energy performance requirements in force
at the national level
3
and to assess the effects of policy
measures implemented or proposed by the Member
States to achieve the NZEB target, particularly in the
case of policy measures based on financial incentives for
energy efficiency (EE) and renewable energy systems
(RES) technologies and the transformation of these
technologies national markets.
Literature review
In general application of optimization, methods for low-
energy and sustainable building design (including also
the cost-optimal objective) are well summarized in the
review analyses by Evins (2013), Nguyen et al. (2014)
and Machairas et al. (2014). Further review studies on
these subjects more specifically focusing on NZEB
developments are presented by Attia et al. (2013)and
Lu et al. (2015). Several examples of application of this
method also with the aim of determine the optimum in
terms of energy performances and costs (life cycle or
initial costs) are presented in numerous studies (Diakaki
et al. 2008; Brown et al. 2010; Morrissey and Horne
2011; Asadi et al. 2012; Fesanghary et al. 2012;
Kumbaroğlu and Madlener 2012; Rysanek and
Choudhary 2013; Nguyen and Reiter 2014;Penna
et al. 2015).
In literature, while it is available also, an extensive
literature on the cost optimization of specific building
element calculatione.g., the optimal insulation thick-
ness for the various building elements and in various
climatic conditions, as summarized by Fokaides and
Papadopoulos (2014)rarer is the published applications
of cost optimization procedures on the whole building-
plant system and only some of these refer explicitly to the
framework of EPBD Recast Directive. Because the meth-
od described in this paper is proposed as a direct appli-
cation of the European comparative approach, the follow-
ing previous experiences were considered particularly
relevant: Kurnitski et al. (2011), Hamdy et al. (2013,
Corrado et al. (2014), Ganic and Zerrin Yılmaz (2014),
Pikas et al. (2014), Ferrara et al. (2014), Brandão de
Vasconcelos et al. (2016), Becchio et al. (2016),
Ashrafiana et al. (2016), Ortiz et al. (2016a,b).
From a methodological point of view, the majority of
previous studies have focused on a limited number of
building variants, selected through a combination of
technical measures/packages or applying (more or less
sophisticated) multi-stage search-optimization tech-
niques (Table 1). Often to quantify the energy needs
for heating, cooling, and lighting, the calculations were
made by dynamic simulations, while the computation of
final energy uses could be obtained by more simplified
calculations (e.g., semi-stationary methods). For
3
It is provided that if the result of the comparative analysis carried out
shows that the minimum requirements in force are considerably less
efficient than those arising from the analysis of the cost-optimal levels
(deviation greater than 15%), the MS must give justification for this
difference or develop a plan outlining the appropriate measures to be
introduced in order to reduce significantly the energy gap.
338 Energy Efficiency (2018) 11:337369
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example, this is the case of Hamdys(2013)analysis,
which developed a multi-stage methodology based on a
multi-objective genetic algorithm able to reduce the
number of the building envelope simulations and, in a
second time, applying appropriate efficiency factors to
optimize the plant systems. In this way, he has increased
the number of considered building variants compared to
other studies. With this aim also, Ferrara et al. (2014)
applied a simulation-based optimization process, com-
bining the use of TRNSYS (Solar Energy Laboratory
2012) with GenOpt (Wetter 2008). Brandão de
Vas c onc e l os e t a l. ( 2016), who considers only the enve-
lope technologies, adopted a two-step approach which
consists in (i) preliminarily discarding of measures with
the same or worse thermal transmission coefficient and
higher global costs comparatively with other measures
and (ii) combination of all resulting measures with each
other, creating 35,000 packages of measures. A good
number of building variants (i.e., 2000) was considered
also by Ortiz (Ortiz et al. 2016a,b), who conversely
applied a Bbrute-force^approach to obtain a complete
characterization of the problem.
As shown in Table 2, the most considered energy
end-uses are space heating, cooling, and lighting. In line
with the EPBD, the appliances (e.g., domestic equip-
ment) are rarely taken into account. The energy calcu-
lations were made referring to similar indoor comfort
conditions by the authors.
About the cost calculation (Table 3), all authors re-
ferred to a financial perspective (including taxes and not
monetizing the environmental damage of emissions)
andexcept Kurnitski et al. (2011), who did not taken
into account maintenance, replacement, and disposal
coststhey considered all cost items indicated by the
Commission Delegated Act No. 244/2012 (European
Parliament 2012a,b). A real interest rate between 2
and 4% and a yearly increase of energy prices around
2% were used.
On the application side (Table 4), the majority of
previous studies have focused on residential building
Tabl e 1 Literature review: general methodology
Reference Calculation of
energy needs
Calculation of final
energy demand
Solving
method
Number
of building
variants
Kurnitski et al. 2011 Dynamic simulation
with IDA-ICE
Dynamic simulation
with IDA-ICE
Combination of the considered
measures/packages
<50
Hamdy et al. 2013 Dynamic simulation
with IDA-ICE
Simplified methods
and auxiliary
design calculations
Automatic multi-stage
optimization
method based on multi-
objective
genetic algorithm
3400
Corrado et al. 2014 Semi-stationary
method
(EN 13790)
Semi-stationary
method
(EN 13790)
Sequential search-optimization
technique
<50
Ganic and Zerrin Yılmaz 2014 Dynamic simulation
with EnergyPlus
Dynamic simulation
with EnergyPlus
Combination of the considered
measures/packages
<50
Pikas et al. 2014 Dynamic simulation
with IDA-ICE
(1 floor)
Dynamic simulation
with IDA-ICE
(fixed HVAC)
Iterative three-step wise
optimization
<50
Ferrara et al. 2014 Dynamic simulation
with TRNSYS
Dynamic simulation
with TRNSYS
Simulation-based optimization
process (GenOpt)
6000
Brandão de Vasconcelos et al.
2016
Dynamic simulation
with EnergyPlus
Dynamic simulation
with EnergyPlus
(fixed HVAC)
Combination of the considered
measures (for envelope only)
35,000
Becchio et al. 2016 Dynamic simulation
with EnergyPlus
Dynamic simulation
with EnergyPlus
Combination of the considered
measures
<50
Ashrafiana et al. 2016 Dynamic simulation
with EnergyPlus
Dynamic simulation
with EnergyPlus
Combination of the considered
measures (for envelope only)
55
Ortiz et al. 2016a,bDynamic simulation
with TRNSYS
Simplified methods
and auxiliary design
calculations
Combination of the considered
measures
2000
Energy Efficiency (2018) 11:337369 339
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types, covering both the ambit of new design and
building retrofit. Analyses on cost-optimal levels
are mainly based on identification of energy efficien-
cy measures/packages affecting energy performance
of buildings, but, in general, the most investigated
systems were the envelope solutions and the heating
generators. In any study, the same calculation meth-
odology was applied to more than two building types
and more than three weather conditions.
Even though it is not trivial to compare the
results obtained under different simplified assump-
tions and calculation methods, these previous
experiences found cost-optimal primary energy
levels in the range 90150 kWh/m
2
/year. The au-
thors, who did this type of comparison, found that
the primary energy targets related to the cost-
optimal levels are significant lower (2050%) than
those related to the standard requirements, in force
at national level.
This same conclusion was derived from the anal-
ysis of the first cost-optimal calculations done by the
Member States. Boermans et al. (2015) observes that
about half of the EU countries reveal a significant
gap (i.e., larger than 15%) between the cost-optimal
levels and the energy requirements in force. The
picture is very similar for the different building
types and for both new and renovated buildings.
From the methodological point of view, it is inter-
esting to observe that about half of the national
methodologies are in line with the CEN standards
and refer to them (at least partly) for the calculation
of primary energy and global cost. However, in most
cases, the primary energy calculation is considered
non fully reliable because the primary energy is not
always used as energy performance indicator, the
value of primary energy factors is low, and not all
technical systems are addressed (Zirngibl and
Bendzalova 2015).
Tabl e 2 Literature review: energy calculation
Reference Energy uses considered Electric primary
energy factor
PV energy taken
into account
Temperature set-points
in winter and summer
Kurnitski et al. 2011 Heating, cooling, ventilation,
pumps and fans, other
technical service systems,
DHW, lighting
1.5 n.a n.an.a
Hamdy et al. 2013 Heating, cooling, ventilation,
pumps and fans, other t
echnical service systems,
DHW, lighting, appliances
1.7 (for Finland) Self-consumed
(by hourly load
matching operation)
n.a25 °C
Corrado et al. 2014 Heating, cooling and DHW 2.17 (for Italy) Self-consumed
(by monthly load
matching operation)
20 °C26 °C
Ganic and Zerrin Yılmaz 2014 Heating, cooling and lighting 2.35 (for Turkey) Not considered 21 °C26 °C
Pikas et al. 2014 Heating, cooling and lighting n.a Self-consumed
(by hourly load
matching operation)
and exported
to the grid
n.an.a
Ferrara et al. 2014 Heating, cooling 2.58 n.a n.an.a
Brandão de Vasconcelos et al. 2016 Heating, cooling, ventilation,
pumps and fans, other
technical service systems,
DHW
n.a Not considered n.an.a
Becchio et al. 2016 Heating, cooling, DHW,
lighting and appliances
2.18 (for Italy) n.a 21 °C26 °C
Ashrafiana et al. 2016 Heating, cooling, DHW,
lighting
2.36 (for Turkey) Not considered 20 °C26 °C
Ortiz et al. 2016a,bHeating, cooling, DHW,
lighting and appliances
2.464 (for Spain) n.a 20 °C24.5 °C
n.a not available
340 Energy Efficiency (2018) 11:337369
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Generalizing the issue, it is interesting to remember
that some critical points on the cost-optimal method itself
were discussed. For instance, Tadeu et al. (2016) consider
that the global cost indicator is not enough for describing
the point of view of an investor and it must be
complemented with additional information. Becchio
et al. (2015) stressed the need to include in the global cost
formula other benefits related to energy-design of build-
ings (as indoor comfort conditions, reduction of CO
2
emissions, embodied energy, real estate market value).
Objectives and overview
Against the regulatory background, the main objec-
tive of this study is to identify primary energy
levels and benchmarks for building renovation
which may represent the cost-optimal and NZEB
4
targets across Europe.
The paper covers the main aspects discussed above
and it proposes an additional calculation method con-
sistent with the European framework (European
Parliament 2012a,b). Compared to previous methods
and applications, (i) it is single stage rather than multi-
4
Referring to the analysis of Marszal et al. 2011, this study is based on
the BZEB limited^definition: a low-energy building, fulfilling any
national/local energy efficiency requirements, which offsets the yearly
balance between its weighted energy demand for heating, DHW,
cooling, ventilation, auxiliaries and built-in lighting, and the weighted
energy supplied by on-site generation systems driven by on- or off-site
sources and connected to the energy infrastructure. Static (or quasi-
static) and symmetric primary energy factors are used as weights in the
balance.
Tabl e 3 Literature review: global cost calculation
Reference Considered costs Economic
perspective
Buildings
lifetime (year)
Real interest
rate (%)
Annual increase
of energy prices
Kurnitski et al. 2011 Energy, labor, materials,
overheads and taxes
Financial 30 3 2%
Hamdy et al. 2013 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 3 2%
Corrado et al. 2014 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 4 Electric 2%
Gas 2.8%
Ganic and Zerrin Yılmaz 2014 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 20 4.12 n.a
Pikas et al. 2014 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 20 4 n.a
Ferrara et al. 2014 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 4 2%
Brandão de Vasconcelos et al. 2016 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 3 n.a
a
Becchio et al. 2016 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 2.3 n.a
Ashrafiana et al. 2016 Energy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 2.4
b
n.a
Ortiz et al. 2016a,bEnergy, labor, materials,
maintenance, replacement,
disposal and taxes
Financial 30 2.5
c
Electric 2.5%
Gas 2%
n.a not available
a
The authors refer to the EUs forecasts for energy costs trends (European Commission 2014)
b
Calculated as difference between the market interest rate (11.25%) and the inflation rate (8.85%)
c
Calculated as difference between the market interest rate (4.5%) and the inflation rate (2%)
Energy Efficiency (2018) 11:337369 341
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Tab l e 4 Literature review: application
Reference Application area
(reference period)
Measures/packages considered (number of variation steps
in addition to the base case)
Building types (area) Climatic conditions
Kurnitskietal.2011 New building design Insulation levels of building envelope (4), air leakages rate (4),
windows (4), heating systems (7), solar systems (thermal (2),
PV (2))
Single house
(171 m
2
)
Cold Estonian climate
Hamdy et al. 2013 New building design Insulation levels of building envelope (816), air tightness levels (3),
window types (3), shading systems (4), efficiency of heat
recovery (3), cooling (2) and heating (4) plants, solar systems (2)
Two-storey house
(143 m
2
)
Vantaa (Finland)
Corrado et al. 2014 Refurbishment
(19461960)
Insulation levels of building envelope (57); window type (5);
solar shading devices (2); solar systems (thermal (3), PV: 4);
generators for heating, cooling and DHW (11)
Apartment block
(1550 m
2
)
Milan (Italy)
Ganic and Zerrin
Yılmaz 2014
Refurbishment
(before regulation standards)
Insulation levels of building envelope (2), window systems (2),
lighting system (2), and chiller EER (2)
Office (4500 m
2
) Anjara, Antalya
(Turkey)
Pikas et al. 2014 New building design Insulation of external walls (5), window area and glazing type (6),
external shading, PV panel size
Office (n.a.) Cold Estonian climate
Ferrara et al. 2014 New building design Envelope systems (3), insulation levels of building envelope (20),
windows type (4), windows width (38), heating and cooling
systems (4), ventilation strategy (2)
Single house
(155 m
2
)
Rhone-Alpes region
(France)
Brandão de Vasconcelos
et al. 2016
Refurbishment (19601990) Insulation levels of building envelope (49), window types (9) Apartment block
(1500 m
2
)
Lisbon (Portugal)
Becchio et al. 2016 Refurbishment (1900) Insulation levels of building envelope (3), window types (3),
heating and cooling systems (2), ventilation (2),
solar systems (thermal (1), PV (8)).
Ex-industrial
(3600 m
2
)
Turin (Italy)
Ashrafiana et al. 2016 Refurbishment (19851999) Insulation levels of building envelope (9), window types (6) Apartment block
(2729 m
2
)
Turkey (Istanbul, Antalya,
and Erzurum)
Ortiz et al. 2016a,bRefurbishment (19912007) Insulation levels of building envelope (32), windows type (2),
solar protection (1), heating and cooling systems (2),
ventilation strategy (2), user behavior (1), solar systems (2)
Apartment block
(400 m
2
)
Barcelona (Spain)
n.a. not available
342 Energy Efficiency (2018) 11:337369
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stage (it considers in one single step all the technologies
and their combinations, rather than optimizing step by
step); (ii) itdescribes the entire Energy-Cost plane rather
than being limited to the Pareto frontier; (iii) it computes
a large number of variants, thus avoiding to rely on a
pre-judgment from the analyst of the suitable combina-
tions which might miss some relevant variant; and iv) it
includes a base refurbishment level as a useful reference
for the entire energy and cost calculation.
To populate a large database of comparable results
across Europe, the calculation is applied to four building
types (two residential and two non-residential), repre-
sentative of the EU stock built in years 60–‘70, in ten
European climatic contexts.
The rest of this paper is structured as follows:
BMethodology^section describes the calculation meth-
odology and the main input data used. BResults and
discussion^section presents and discusses the main
results obtained. Finally, the most relevant conclusions
are outlined in BConclusions^section.
Methodology
To identify cost-optimal benchmarks for building reno-
vations across Europe, a comprehensive methodology
was developed. It consists of seven steps, starting from
the selection of reference climates in EU28 and ending
Tabl e 5 Summary of the applied methodology
Applied methodology Calculation of energy needs Dynamic simulation with EnergyPlus
Calculation of final Energy uses Applying simplified and auxiliary design
calculations
Solving method Combination of the considered measures/
packages
Number of building variants > 25,000
Energy calculation Energy uses considered Heating, cooling, ventilation, pumps and fans,
other technical service systems, DHW, lighting
Electric primary energy factor Between 1.50 and 3.14, depending on the national
mix of sources and generation technologies.
Evaluated for two scenarios (reference and
ambitious) in each considered national context
PV energy taken into account Self-consumed (by simplified assumptions) and
exported to the grid
T set-points in winter and summer 20 °C26 °C
Global cost calculation Considered costs Energy, labor, materials, maintenance, replacement,
disposal and taxes
Economic perspective Financial and macroeconomic
Buildings lifetime 30 years
Real interest rate Between 0.86 and 2.36%, depending on the
national context (from EUROSTAT 20082011)
Annual increase of energy prices Patterns simulated over the period 20112050 for
two energy scenarios (BReference^and BAmbitious^)
Application Application area Refurbishment (of buildings built in 60s70s)
Measures/packages considered
(variants in addition to the base
refurbishment case)
Insulation levels of building envelope (3), tightness
levels (2), window types (2), shading systems
(12), night natural ventilation strategies (12),
lighting load/control (12), efficiency of heat recovery
(1), heating (5) and cooling (4) generators, heating
(1) and cooling (1) distribution, heating (4) and
cooling (4) emission systems, heating (1) and cooling
(2) control, solar systems (3)
Building types (area) Single house (140 m
2
), apartment block (1000 m
2
), office
(2400 m
2
), school (3500 m
2
)
Climatic conditions Seville (ES), Madrid (ES), Rome (IT), Milan (IT),
Bucharest (RO), Vienna (AT), Paris (FR), Prague (CZ),
Berlin (DE), Helsinki (FI)
Energy Efficiency (2018) 11:337369 343
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with the development of a sensitivity analysis. In gen-
eral, the methodology of the study is as follows:
Step 1: selection of representative climate condi-
tions within the European Union.
Step 2: definition of reference building types
(including its thermos-physical, passive and active
components) and determination of base levels of
retrofit measures.
Step 3: selection of renovation measures and pack-
ages applicable to the building types.
Step 4: execution of energy calculations for each
combination of retrofit measures, with the determi-
nation of the (net) primary energy demand.
Step 5: execution of economic calculations for each
combination of retrofit measures, determining the
investments costs and the global costs over the
calculation period.
Fig. 1 Summer Severity Index versus Winter Severity Index (on the left) and Climatic Cooling Potential in July (on the right) for 24
European cities (values normalized on those of Milan) with indication (red circles) of the ones selected for this analysis
Office School
South façade
South/North façade
North façade
East façade
East façade
West façade
Fig. 2 Schedules used to
simulate the internal gains in the
building types
344 Energy Efficiency (2018) 11:337369
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Step 6: identification of energy levels representing
the cost-optimal and the NZEB targets and opti-
mumpackagesofretrofitmeasures(i.e.,technolog-
ical benchmarks).
Step 7: development of a sensitivity analysis fo-
cused on some key calculation parameters.
To provide a comparison with the bibliography
discussed in the introduction, a summary of the meth-
odology applied in this study is shown in Table 5.The
following subchapters provide more details about the
main steps of the calculation approach.
Selecting the EU reference climates
The climate of Europe is temperate-continental, with the
influence of the ocean on the western coasts and a
Mediterranean climate in the South. The climate is
strongly influenced by the Gulf Stream, which keeps
mild air over the high-latitude north-western region over
the winter months. While Western Europe has an oce-
anic climate, Eastern Europe has a drier, continental
climate. Parts of the Central European plains have a
hybrid oceanic/continental climate. Four seasons occur
in Eastern Europe, while Southern Europe experiences
distinct wet season and dry seasons, with prevailing hot
and dry conditions during the summer months.
To assess the energy and comfort performances of
buildings, climatic conditions are usually represented as
sets of data that describe the climate at a certain location at
different degrees of detail. Since several weather variables
affect the building behavior, it is not straightforward to
establish a definition of typical weather. Different defini-
tions and hence different types of data sets are available
based on different weighting of the parameters and other
choices. In this case, the analysis was based on the datasets
developed by the International Weather for Energy
Calculations (IWEC),
5
which consist in hourly data of
the main climatic variables arranged in typical weather
years. This same data was subsequently used to carry out
the energy simulations.
To take into account the climatic variety of the EU28
area, nine target European countries were chosen. Within
them, the climatic conditions of 24 cities were chosen for
their representativeness. To further filter the selection, three
indicators were used as reference: the Winter Severity
Index and the Summer Severity Index proposed by F.
SanchezdelaFlorthe(2006) and the Climatic Cooling
Potential developed by Artmann et al. (2007). These in-
dexes were calculated for all cities (Fig. 1), and ten of them
were finally chosen also depending on their relevance in
terms of urban population. Finally, the following climate
conditions were selected: Seville (ES), Madrid (ES), Rome
(IT), Milan (IT), Bucharest (RO), Vienna (AT), Paris (FR),
Prague (CZ), Berlin (DE), and Helsinki (FI).
Defining the reference building types
According to the Building Stock Observatory of the
European Commission,
6
in 2013, the EU residential
stock (which accounts for about 65% of consumption)
is composed by almost 250 million of dwellings (single-
family houses represent 65% of residential floor space,
against 35% for apartments), of which almost 43% built
in the period 19451979. Out of the total floor area of
the service sector, 29% is used for offices (public and
private), 27.5% for wholesale and trade, 16% for edu-
cational activities, 14.5% for hotels and restaurants and
6.5% for health and medical activities, and the remain-
ing 6.5% for other activities.
In this context and in line with the principles of the
EPBD Directive, four typologies of buildings (two res-
idential and two examples of the non-residential sector)
were selected. The attention was focused on the relevant
and strategic subcategory of buildings built in the 60s
70s, before the appearance of significant energy perfor-
mance requirements in the European and national regu-
lations. To establish models representative of the nation-
al building stocks and, at the same time, to allow a direct
cross comparison between countries, it was decided to
fix the envelope geometries and the internal gains.
Taking into account the data collected by previous stud-
ies (Tabula: Ballarini et al. 2014; Corgnati et al. 2013;
Odyssee-Mure: Lapillonne et al. 2012) and asking the
advice of national experts participating to the research
project ENTRANZE, these reference cases were
obtained:
a single (detached) house, composed by two floors
over the ground level and an underground level,
with a net conditioned area of about 140 m
2
and a
5
The IWEC weather files are the result of the ASHRAE Research
Project 1015 by Numerical Logics and Bodycote Materials Testing
Canada for ASHRAE Technical Committee 4.2 Weather Information.
They were derived from up to 18 years of DATSAV3 hourly weather
data.
6
http://ec.europa.eu/energy/en/eu-buildings-database
Energy Efficiency (2018) 11:337369 345
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
ratio of envelope area and conditioned net volume
(S/Vratio) of 0.7,
a four-floor block of 12 apartments with a condi-
tioned area of 1000 m
2
and a S/Vratio of 0.33,
a medium-size and highly glazed office building,
with five floors (of 3-m height each), S/Vratio of
0.33 and a net heated area of 2400 m
2
(prospects
shown in Fig. 2), and
a two-floor school of medium size with S/Vratio of
0.46 and a net heated area of 3500 m
2
(Fig. 2).
Additional details about these types are provided in
Table 6. Under the ground floors of all the reference
buildings, there is an unconditioned basement. The res-
idential models, as well as the school, have an uncondi-
tioned space between the last slab and the slope roof.
Only for the apartment block, different window areas
were selected in different climates: 15% of the total
façade surface for the Spanish, Italian, and French cases;
and 30% in the other countries.
To simulate the internal gains, typical design levels
and schedules were applied (Fig. 3). They were defined
mediating the slightly different indications provided by
the national experts, who referred to national standards
or previous studies. A more precise method was used for
the lightingloads in the non-residential buildings, where
the switching on the lights was simulated dynamically to
Tabl e 6 Fixed building characteristics of the selected reference buildings
Building characteristic Single-family
house (SFH)
Apartment block (AB) Office School
Building
geometry
No. of heated floor 2 4 5 2
S/Vratio (m
2/
m
3
) 0.7 0.33 0.33 0.46
Main orientation S/N S/N S/N S/N
Net dimensions of heated volume 8.5 × 8.5 × 6 m 24.6 × 11.2 × 12.8 m 30 × 16 × 15 m 45 × 60 × 7 m
(U shape)
Net floor area of heated zones (m
2
) 140 990 2400 3500
Area of S and N façade (m
2
) 51 315 450 752.5
Area of E and W façade (m
2
) 51 143 240 315
Area of the roof/basement (m
2
) 72.25 54 480 1750
Window area on S façade (%) 25 1530 56 32
Window area on E façade (%) 7 0 32 22
Window area on N façade (%) 25 1530 50 29
Window area on W façade (%) 7 0 35 40
Internal gains
(main rooms)
Occupancy design level (m
2
/person) 50 25 18 5.6
Lighting design level (W/m
2
) 3.5 3.5 18 18
Appliances design level (W/m
2
) 4 4 9 1.75
Fig. 3 Prospects of the non-residential building models
346 Energy Efficiency (2018) 11:337369
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Tab l e 7 Variable characteristics of selected base refurbishment levels. The Uvalues were calculated applying the standard ISO 6946 (ISO 2007) for the building components selected as
typical by the national experts
Country Type of building Wall Roof Basement Window Heating generator system
(emission system)
Cooling generator system
(emission system)Uvalue [W/m
2
°K] Uvalue [W/m
2
°K] Uvalue [W/m
2
°K] Uvalue [W/m
2
°K]
Seville Residential 1.43 1.90 1.32 5.84 Gas boiler Chiller
Non-residential 1.37 1.292.19 1.542.57 5.86 (radiator) (fancoil/split)
Madrid Residential 1.43 1.901.325.84Gasboiler Chiller
Non-residential 1.37 1.292.19 1.542.57 5.86 (radiator) (fancoil/split)
Rome Residential 1.22 1.67 1.69 3.01 Gas boiler Chiller
Non-residential 1.17 1.281.57 1.74 5.78 (radiator) (fancoil/split)
Milan Residential 1.22 1.67 1.69 3.01 Gas boiler Chiller
Non-residential 1.17 1.281.57 1.74 3.47 (radiator) (fancoil/split)
Bucharest Residential 1.46 1.61.25 1.28 2.67 District heating or gas
boiler(radiator)
Chiller
Non-residential 1.34 1.014.14 1.10 2.72 (air diffuser/fancoil)
Vienna Residential 1.25 1.38 1.80 2.62 Gas boiler Chiller
Non-residential 1.192.59 1.111.50 1.24 2.72 (radiator) (fancoil/split)
Paris Residential 1.542.87 1.212.56 1.98 3.47 Gas boiler Absent or chiller
Non-residential 1.061.17 1.652.83 3.47 5.78 (radiator) (fancoil/split)
Prague Residential 1.340.63 1.330.65 1.24 2.66 District heating
or biomass boiler(radiator)
Absent or chiller
Non-residential 1.071.41 0.500.63 3.97 3.50 (fancoil/split)
Berlin Residential 0.931.43 1.111.18 1.021.65 2.67 Gas boiler Absent or chiller
Non-residential 1.42 0.68 1.15 2.72 (radiator) (fancoil/split)
Helsinki Residential 0.480.60 0.300.39 0.48 2.50 District heating Absent
Non-residential 0.460.62 0.390.84 0.530.7 2.95 (radiator)
Energy Efficiency (2018) 11:337369 347
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achieve a specified illuminance set-point on the visual
task (i.e., 750 lx).
In order to obtain homogeneous building variants in
terms of functionality, esthetic aspect, and liveability
(conditions normally not evaluated by a cost-optimal
analysis), the concept of Bbase refurbishment level^
(BRL) was introduced. It represents the lower level of
renovation to which compare the more efficient ones. In
other words, it is not contemplated the possibility of not
interveninginanywayonabuilding older than 40 years.
Avoiding to consider the renovation of building elements
without an influence on the thermal energy needs, the
BRL includes the rehabilitation of the building façade
and roof (finishing material), the substitution of the old
window systems and of the old heating/cooling systems
with similar (in terms of technology) components, and
the installation of an active cooling system (to guarantee
similar thermal comfort conditions, if necessary
7
). This
methodological refinement (the Commissions
Guidelines do not require explicitly to define this refur-
bishment level) allows to clearly recognize also which
costs could be omitted
8
and to fix the end-life of the
original building components (older than 40 years).
Unlike geometries and thermal gains, the physical prop-
erty of the envelope components (wall, roof, basement,
windows) and the configurations of the thermal systems of
the base cases (i.e., the base refurbishment levels) were
diversified by country. They are shown in Table 7.
Selecting the retrofit measures and calculating
the associated energy levels
In order to define packages of measures able to increase
the energy performances of the reference cases, technol-
ogies and techniques from the following groups were
taken into account:
Building envelope: measures that deal primarily
with the reduction of heat transmission and im-
proved air tightness of the building envelope with
the objective of reducing transmission losses and
losses from (uncontrolled) air-exchange.
Space heating: an active system is usually necessary
to meet the demand for heating. This demand can be
met by efficient and/or renewable energy systems
(e.g., condensing boilers, heat pumps, and thermal
solar panels) in conjunction with suitable storage,
distribution, and emission systems.
Domestic hot water: DHW is often produced
with the same system used for space heating,
but it can also be supplied by combined systems
(e.g., when integrating solar energy systems
with a generator using fuel or electricity) or
7
The installation of an active cooling system was avoided only where
the cooling power was lower than 5 W/m
2
or the cooling operation time
was lower than 100 h.
8
Under the full cost approach disciplined by the reference guidelines,
it results possible to omit the costs related to building elements which
do not have an influence on the energy performance of the building and
costs that are the same for all building variants.
Tabl e 8 Ranges of envelope variants selected for the residential type in the considered contexts
Packages Building parameter Base renovation
level
Vari at i o n
step 1
Vari at i o n
step 2
Variation
step 3
Value range Value range Value range Value range
Opaque envelope
elements
Uvalue of external walls [W/m
2
°K] 0.482.87 0.220.52 0.170.31 0.150.23
U-value of Roof [W/m
2
°K] 0.32.56 0.140.56 0.120.33 0.090.23
Uvalue of basement [W/m
2
°K] 0.481.98 0.450.57 0.290.48 0.210.48
Window systems Uvalue of windows [W/m
2
°K] 2.55.84 1.032.6 0.71.71
Infiltration air change rate per hour
a
[1/h]
0.270.77 0.110.61 0.080.58
Passive cooling
strategies
Solar shading device and control External blinds
manual
External blinds
automated
––
Night ach ventilation rate [1/h] 0 4 ––
Lighting load [W/m
2
] and control 3.5 manual 3.5 manual ––
Heat recovery Efficiency [%] 0 (absent) 80 ––
a
Here, the actual average air changes per hour due to infiltrations are provided. They refer to three different permeability classes of windows
(i.e., 2, 3, and 4), as defined by the European standard EN 12207 (CEN 2000)
348 Energy Efficiency (2018) 11:337369
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separate systems. High-efficient storage and dis-
tribution systems are crucial for reducing heat
losses along all the chain.
Ventilation systems: mechanical ventilation sys-
tems allow having control on the air change
rates necessary for IAQ and can also limit losses
from air-exchange if heat recovery systems are
installed. Ventilation and heat recovery can have
both a centralized or decentralized layout, with
the latter sometimes easier to implement in ret-
rofit work.
Cooling: heat protection and passive cooling
systems such as shading devices, night ventila-
tion coupled with exposed mass, can help to
reduce or avoid cooling needs to be met by
active systems. Normally, these techniques are
not considered in previous cost-optimal analy-
sis, but their potential is relevant in many
climates.
Solar systems: photovoltaic and solar thermal sys-
tems are the most common technologies used to
generate on-site renewable energy. Their contribu-
tion (also that exported to the grid) reduces the total
primary energy demand.
Lighting: for office and school buildings, in combi-
nation with adopted passive cooling strategies, energy
efficiency actions were also adopted on lighting sys-
tems, particularly, high-efficiency lighting installa-
tions and automatic control as function of the day-
lighting illuminance levels and with objectives of
glare reduction.
A relevant aspect of any cost-optimal calculation
is the number of building variants that it can eval-
uate: on one hand, a low number allows very de-
tailed calculations of the energy performances; on
the other, a high one improves the characterization
of the problem. In this case, to increase the number
of variants evaluated with a reasonable level of
detail, a three-step procedure was adopted for the
primary energy demand calculations. In particular:
firstly, the energy needs for heating and cooling,
as well as the energy use for lighting (that also
depends on the glazing typologies and solar
shading solutions), were obtained by dynamic
simulation of building models, suitably defined
in EnergyPlus environment (United States
Department of Energy 2013).
Tab l e 9 Ranges of envelope variants selected for the non-residential type in the considered contexts
Packages Building parameter Base renovation level Variation step 1 Variation step 2 Variation step 3
Value range Value range Value range Value range
Opaque envelope elements Uvalue of external walls [W/m
2
°K] 0.462.59 0.20.46 0.130.28 0.090.16
UvalueofRoof[W/m
2
°K] 0.394.14 0.160.53 0.120.21 0.090.13
Uvalue of Basement [W/m
2
°K] 0.533.97 0.30.58 0.210.32 0.160.22
Window systems Uvalue of Windows [W/m
2
°K] 2.715.86 1.532.718 0.7742.108
Infiltration air change rate per hour [1/h] 0.491.3 0.150.61 0.050.23
Passive cooling
strategies
Solar shading device Ext./internal blindsfixed slat angle Ext./internal blindsfixed slat angle External blindsslat angle
varies to block beam solar
Control Manual Automated Automated
Night ach ventilation rate [1/h] 0 2.5 5
Lighting load [W/m
2
]
and control
18 (15
a
)
manual
12 (5
a
)
manual
6(2
a
)
automated
Heat recovery Efficiency [%] 0 (absent) 80 ––
a
Lightingload[W/m
2
] in service rooms
Energy Efficiency (2018) 11:337369 349
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Secondly, the related final energy demands were cal-
culated applying simplified dynamic calculations and/
or efficiency factors to each variant of the thermal sub-
systems and with further calculations for RES sys-
tems, pumps, fans, and other auxiliary systems.
Finally, the net primary energy demand values were
obtained applying appropriate primary energy con-
version factors (PEFs), for which a dedicated study
was developed, and (if applicable) subtracting the
weighted contribution from solar renewable energy
exported to the grid.
Combining the detailed dynamic simulations to ob-
tain energy needs with the simplified design of thermal
plants, more than 25 thousand building variants were
defined, for each building type and each weather condi-
tion. In principle, this amount of data ensures the possi-
bility of clearly recognizing the cost-optimal levels
(minimum global cost for each value of net primary
energy demand), as the lower profile of the Bcloud^of
points in the domain Energy-Cost. Multi-stage optimi-
zation approaches were not adopted to avoid limiting the
economic competition between refurbishment measures
related to different sub-systems of the building (e.g.,
between thermal insulation and RES systems).
Energy performance of building envelope
The selection of the energy efficiency measures is a
critical choice since a very high number of packages
can be established aggregating them. For this study,
which provides a very wide application, the most
typical and applicable renovation measures were
selected and especially, those on the envelope (eval-
uated by dynamic simulation) were aggregated in
several packages. Specifically, four packages of en-
velope measures were composed, combining the
insulation of all the opaque envelope elements; the
substitution of window systems (including glasses
and frames); the heat protection and passive cooling
strategies (including solar protections, night natural
ventilation, and lighting); and the heat recovery
strategy. As shown in Tables 8and 9, in addition
Tabl e 1 0 Summary of the boundary conditions of the simulations
carried out
EnergyPlus version 7.2
Surface convection
algorithm
Adaptive convection algorithm
Heat balance
algorithm
Conduction transfer function
Solar Distribution Full interior and exterior with reflections
Ter rai n Cit y
Zone thermal system Zone HVAC: ideal loads air system +
design specification: outdoor air
Zone control Humidistat and thermostat
Daylighting object Daylighting: controls
Infiltration and
ventilation objects
Zone infiltration/ventilation: design flow
rate + zone refrigeration door mixing
Thermal bridge
adjustment
Narrow sub-surfaces (as small part of the
external walls) were added for model-
ing lintels, columns and other main
thermal bridges. A no mass material
was associated to these geometric areas
and its fictitious U-value was calculated
on the basis of available thermal bridge
repertoires (Pascual Buisán et al. 2012).
Tabl e 11 Ranges of efficiency coefficient considered for the sub-
systems alternatives
Sub-system Seasonal efficiency factor
In heating
mode
In cooling
mode
Generation systems
Gas boiler (%) 80
Condensing gas boiler (%) 95104
a
Air to water reversible heat pump
(with high SCOP/SEER)
1.442.91
b
0.63.20
b
Ground source reversible heat
pump (with high SCOP/SEER)
1.553.89
b
0.634.45
b
District heating connection (%) 100
Biomass boiler (%) 90
Emission systems
Insulated radiant floor (%) 9799
c
97
Radiator (%) 9295
c
Fancoil/split (%) 9496
c
98
Air diffuser (%) 9094
c
97
Distribution systems
Not insulated pipes (%) 9295
a
9295
Insulated pipes (%) 99 99
Control systems
Climatic control system (%) 8680
a
90
Climatic + room indoor control
system (%)
9895
a
98
a
Depending on the emission system
b
Calculated for each building variant and climate according to
standard EN 14825 (2012)
c
Depending on the emission power system
350 Energy Efficiency (2018) 11:337369
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to the levels of the base cases, three levels of insu-
lation, two types of windows, two passive cooling
combinations, and one heat recovery strategy were
identified for each building type and in each climate
in accordance with the national expertsindications.
Because these variants were defined as real retrofit
measures (i.e., addition of an insulation layer of a
certain commercial thickness and substitution of the
window), the values of parameters depend on the
starting characteristics of the reference models,
which are different for every climatic context (as
shown in Table 7).
Wishing to reduce the number of simulations, 36
of the possible 72 combinations of packages were
selected renouncing to study seldom found renova-
tion variants, such as those that provide a high-
performance improvement of certain elements with-
out a simultaneous action on the others (e.g., the
installation of an insulating layer of 2025 cm, at
same time maintaining the original single-panes
glazing). In this way, a total of 1440 models (36
variants per 4 building types per 10 climates) were
defined and their energy needs for heating/cooling
and energy use for lighting were calculated by the
EnergyPlus simulations.
For obtaining building envelope configurations
fully comparable in terms of indoor comfort perfor-
mances, the energy needs for all the building
Tabl e 1 2 Primary energy factor (PEF) considered for the present study
Carrier ES IT RO AT FR CZ DE FI
Electricity 1.89 2.05 2.53 1.65 2.72 3.14 2.45 2.69
Gas 1.00 1.00 1.00 1.17 1.00 1.00 1.00 1.00
Biomass (total PEF: renewable + non-renewable part) 1.25 1.50 1.50 1.08 1.50 1.20 1.50 1.50
District heating 1.20 1.20 1.20 1.00 1.20 1.40 1.20 0.70
Tabl e 1 3 Average and standard deviation (on all target countries) of cost of technologies (material, labor, general expenditure, and business
profit) for the different variation steps
Packages Building parameter Type of
building
Base renovation
level
average ± st. dev.
Variation step
1
average ± st.
dev.
Vari at i o n s t e p
2
average ± st.
dev.
Variation step
3
average ± st.
dev.
Opaque envelope
elements
Wal l s [/m
2
] Res. 32 ± 23 64 ± 20 72 ± 22 80 ± 23
Non-res. 31 ± 22 59 ± 19 70 ± 24 86 ± 26
Roof
b
[/m
2
] Res. No renovation
a
27 ± 12 32 ± 11 42 ± 12
Non-res. 51 ± 20 54 ± 48 67 ± 50 80 ± 52
Basement [/m
2
] Res. No renovation 37 ± 24 43 ± 24 52 ± 25
Non-res. No renovation 52 ± 27 60 ± 29 69 ± 30
Window systems Window
c
[/m
2
] Res. 64 ± 29 277 ± 74 332 ± 96
Non-res. 64 ± 26 276 ± 69 329 ± 84
Passive cooling
strategies
Solar shading device and
control
[/m
2
of windows]
Res. 201 ± 119 325 ± 130 ––
Non-res. 199 ± 113 319 ± 124 335 ± 126
Night ventilation system
[/m
2
of windows]
Res. Absent 228 ± 58 ––
Non-res. Absent 119 ± 114 222 ± 56
Lighting and control
[/m
2
of floor]
Res. – –––
Non-res. 33 ± 12 39 ± 15 69 ± 18
a
The rehabilitation of the finishing material of the roof do not have an influence on the thermal energy needs, because there is a
unconditioned zone between the roof and the heated spaces
b
In school building, last slab in contact with unconditioned space; in office, roof in contact with conditioned space
c
Variant 1: repair and restoration existing windows
Energy Efficiency (2018) 11:337369 351
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variants were calculated assuming the same indoor
conditions for each typology, specifically, the same
operative temperature and relative humidity set-
points, 20 °C in winter and 26 °C in summer (latent
control not applied) for the residential types and
20 °C and 25% in winter and 26 °C and 60% in
summer for the non-residential buildings
9
.Thesame
was done for the values of minimum air change (at
maximum occupation rate), coherently with the oc-
cupation levels and the ventilation design rates pro-
posed by EN 15251 (CEN 2007b) for very low-
polluted buildings, 0.5 h
1
in the residential build-
ings, 0.8 h
1
in the office, and 1.6 h
1
in the school.
About the tool employed for this first step of calcu-
lation, it is useful to specify the algorithms used, the
boundary condition selected, and the choices made to
overcome some limitations of the software (as the eval-
uation of the thermal bridges). An overview of these
aspects is shown in Table 10.
Energy performance of thermal systems
The thermal systems (including all the main sub-
components) were evaluated by simplified calculation
methods derived from the Italian EPB standard UNI TS
11300-2 (UNI 2008) and several European reference
standards: EN 15243 (CEN 2007a), EN 15316 (CEN
2007c), and EN 14825 (CEN 2012). In this way, it was
possible to associate to each envelope variant a large
number of alternative (and feasible) thermal plants.
They were designed combining five heating and cooling
generator types, two distribution variants, four heating
and cooling emission systems, and two heating/cooling
control options. These alternatives were considered in all
9
As discussed in several previous studies (Nicol and Humphreys
2010; Deuble and de Dear 2012; Pagliano and Zangheri 2010;
Carlucci 2013), other choices (e.g., the adaptive comfort target for
naturally ventilated buildings) are also possible and it may be one of
the ways to reduce the energy needs for cooling with respect to those
estimated in this study, while offering comfortable living and working
conditions to occupants.
Tabl e 1 4 Average and standard
deviation (on all target countries)
of cost of sub-systems alternatives
(material, labor, general expendi-
ture, and business profit)
Sub-system Unit Average ± st. dev.
Generation systems
Gas boiler /kW 151 ± 72
Condensing gas boiler /kW 194 ± 90
Air to water reversible heat pump
(with high SCOP/SEER)
/kW 524 ± 209
Ground source reversible heat pump
(with high SCOP/SEER)
/kW 1009 ± 325
District heating connection /dwelling 642 ± 240
Biomass boiler /kW 541 ± 108
Emission systems
Insulated radiant floor /m
2
of floor 92 ± 68
Insulated radiant floor + local dehumidifier /m
2
of floor 141 ± 68
Radiator /m
2
space conditioned 45 ± 31
Fancoil/split /m
2
space conditioned 54 ± 27
Air diffuser /m
2
space conditioned 73 ± 30
Distribution systems
Insulated pipes (low) /m of pipe 8 ± 4
Insulated pipes (medium) /m of pipe 12 ± 6
Control systems
Climatic control system /unit 996 ± 456
Climatic + room indoor control system /number of rooms 311 ± 168
Solar systems
Photovoltaic panels /m
2
of solar panel 2782 ± 386
Solar thermal system /m
2
of solar panel 812 ± 378
352 Energy Efficiency (2018) 11:337369
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selected contexts with some exceptions: the gas genera-
tion and the radiant floor systems were not applied in
Finland, and the district heating option was not consid-
ered in Spain, due to their very low diffusion (also in the
main urban areas).
In the assessment of the final energy demands, sev-
eral auxiliary design calculations were also needed.
Specifically, the seasonal efficiency factor of heat
pumps was calculated applying the hourly method de-
scribed in the standard EN 14825 (CEN 2012). The
energy demand for DHW was estimated with the meth-
od EN 15316-3-1 (CEN 2005) and considering the
number of occupants already used (as thermal gains)
in the dynamic simulations.
Where applicable, the energy consumption of cir-
culating pumps (ST included) was calculated assum-
ing their efficiency equal to 80%, estimating the
pressure losses in function of the size and
complexity of the different buildings and deducing
the operation times from the simulation results
(hourly energy needs). For the building variants in
which a mechanical ventilation system was imple-
mented, a simplified dimensioning of fan consump-
tionswasbasedonanefficiencyvalueof60%and,
in the presence of a heat exchanger, the pressure
losses were increased of 300 Pa. For fancoils and
splits, a specific fan power of 0.7 kW/m
3
/s was
used. In designing the power of the auxiliary sys-
tems, a safety factor of 1.2 was used.
References on the variants of thermal system are
provided in Table 11.
Energy from RES
In Europe, solar energy is one of the most favorable
RES (European Commission 2006)andthemost
Fig. 4 Main energy prices estimated over the period 20102050 by POLES model, for the different macro-scenarios
Energy Efficiency (2018) 11:337369 353
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applied one to the building sector. The sun source
was considered available on the roof of all building
types, and four alternatives of solar systems were
taken into account: (i) both solar thermal (ST) and
photovoltaic (PV) absent; (ii) only solar thermal,
designed to cover 50% of the energy need for hot
water; (iii) only PV panels, installed on the 50% of
the roof free surface (north exposition excluded) and
designed to cover not more than the yearly primary
energy demand of the building; and (iv) the combi-
nation of the two systems (with the previous sizing
rules). A flat plate solar thermal collector
10
and a
photovoltaic panel of monocrystalline silicon
11
were
selected as reference technologies and fixed for all
applications. A performance decay of 1% per year
was applied for both technologies.
In line with the EU Commission Decision 2013/
114/UE and the standard EN 15603 (CEN 2008), the
renewable contribution from heat pumps and bio-
mass generation systems was evaluated considering
the first as Bon-site generation from on-site
renewables^and the second as Bon-site generation
from off-site renewables^.
The electricity generated by photovoltaic systems
and exported to the grid was converted in primary
energy applying the same primary energy factors used
to convert the electric final demand (see below).
Primary energy of the building variant
To obtain the (net) primary energy demand from the
final levels, appropriate primary energy factors for each
considered carrier were used (Table 12). For the primary
energy factors of fossil sources, biomass, and district
heating, the reference values provided by the national
experts were applied. Otherwise, for electricity, a dedi-
cated analysis was developed by Enerdata using the
Prospective Outlook on Long-term Energy Systems
(POLES) model.
12
Price and power mix projections
were derived from two scenarios of the world energy
systems simulated with the POLES model, using histor-
ical data up to 2011: a BReference^scenario and an
BAmbitious^climate scenario, with the same macroeco-
nomic context and main differences on the carbon
policies.
The BReference^scenario assumes that, once the
global recession is over, business as usual behavior
is resumed rather quickly. Only on-going and al-
ready planned climate policies are taken into ac-
count, including the 20% emissions reduction in
the European Union by 2020. It is assumed that no
consensus is reached at international level and, after
2020, it is assumed that additional energy and cli-
mate policies are adopted (EU reduces its emissions
in 2050 by 50% compared to 1990 levels). Without
a global agreement, these low-intensity and non-
coordinated policies result in soaring CO
2
emissions
across the world and in emerging economies in
particular. The future fuel mix is dominated by fossil
fuels.
The BAmbitious^climate scenario shows a clear
transition towards a long-term decarbonisation, with
moreambitiouseffortsonenergyefficiencyanda
real emergence of renewable technologies.
Negotiations between advanced and emerging econ-
omies on climate change are eventually successful,
10
With: overall heat loss coefficient U
L
= 3.5 W/m
2
K; absorbance of
the receiver α= 0.95; transmittance of the cover systems τ=0.85.
11
With peak power factor of 0.15 kW/m
2
.
12
https://ec.europa.eu/jrc/en/poles
Tabl e 1 5 Main economic inputs used in the cost-optimal calculations
Economic parameters ES IT RO AT FR CZ DE FI
Financial real interest rate (%) 2.21 2.36 1.56 1.45 1.72 1.68 1.44 0.86
VAT refurbishment of residential (%) 10.0 10.0 24.0 20.0 19.6 21.0 19.0 24.0
VAT refurbishment of non-residential (%) 21.0 21.0 24.0 20.0 19.6 21.0 19.0 24.0
Taxes on electricity (%) 19.4 28.3 19.4 27.2 29.4 17.5 44.6 29.8
Taxes on gas (%) 15.3 36.4 47.6 25.6 16.6 16.7 24.2 36.9
Taxes on biomass (%) 21.0 21.0 24.0 20.0 19.6 21.0 19.0 24.0
Taxes on district heating (%) 21.0 21.0 24.0 20.0 19.6 21.0 19.0 29.0
Carbon price (20112050) /tCO
2
From 3 (in 2011) to 84493 (in 2050 for BReference^BAmbitious^scenarios)
354 Energy Efficiency (2018) 11:337369
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and an international consensus is progressively
reached. Europe goes beyond its 20% target by
2020, and the OECD and emerging countries meet
their Copenhagen objectives. A new international
agreement is adopted to reach the 2050 targets,
i.e., a trajectory limiting the global temperature in-
crease at around 2 to 3 °C by the end of the century
(IPCC 2007), which implies reducing world emis-
sions by a factor 2 by 2050 compared to 1990
levels, and by a factor of 4 for developed countries.
Under these assumptions, the residential domestic
prices of oil and gas are projected to increase by respec-
tively 5.9 and 5.2% per year in the ambitious scenario
over the period 20102030. In the reference scenario,
the progression will be lower because of lower carbon
tax. The average electricity price will increase by 2% per
year in the ambitious scenario and by 0.8% per year in
the reference one. The electricity price is expected to
peak in 2030 at around $3400/toe in the ambitious
scenario and at $2500/toe in the reference scenario.
Fig. 6 Example of Energy-Cost cloud, obtained for the apartment block located in Vienna (financial perspective 2011,
BReference^scenario)
Fig. 5 Scheme of the methodology used for identifying the primary energy targets (on the left) and technological benchmarks (on the right)
for a certain building type located in a certain climate
Energy Efficiency (2018) 11:337369 355
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Tabl e 1 6 Identification of the cost-optimal (BC-opt^) and NZEB targets, and selection of technological benchmarks (financial perspective
2011, BReference^scenario)
Climate and building
type
Targets Benchmarks
(Net) primary energy
[kWh/m
2
/year]
Global costs
difference with
respect to BRL
[%]
Energy need for
heating
a
[kWh/m
2
/year]
Energy need for
cooling
[kWh/m
2
/year]
RES
contribution
b
[kWh/m
2
/year]
Initial
Investment
difference with
respect to BRL
[%]
BRL C-opt NZEB C-opt NZEB C-opt NZEB C-opt NZEB C-opt NZEB C-opt NZEB
Seville (ES) SFH 156 25 < 10 14 1 6 3 48 24 83 57 36 64
AB 127 35 < 25 28 23 11 3 15 12 79 68 32 17
Office 225 145 < 10 5 16 18 4 88 37 74 58 51 110
School 189 83 < 10 *8 8 8 20 6 58 25 117 81 20 124
Madrid (ES) SFH 236 43 < 10 18 1 30 15 32 11 107 91 66 84
AB 182 49 < 30 28 24 23 15 6 5 37 86 50 24
Office 298 124 < 10 14 20 59 15 49 19 122 72 56 134
School 262 80 < 10 10 6 71 17 21 9 179 90 40 110
Rome (IT) SFH 193 41 < 10 11 4 19 11 39 12 98 89 30 62
AB 157 69 < 35 21 9 7 10 24 8 40 36 23 40
Office 296 72 < 20 8 13 12 11 37 37 3 70 27 103
School 357 101 < 10 4 9 13 9 28 29 0 95 42 102
Milan (IT) SFH 346 50 < 20 26 2 27 27 0 0 43 116 51 126
AB 260 98 < 40 53 13 35 21 0 0 15 109 672
Office 400 76 < 10 20 7 16 8 15 14 0 61 34 107
School 357 86 < 10 17 4 11 7 12 12 0 64 46 119
Bucharest (RO) SFH 392 149 < 40 19 33 54 33 24 4 0 154 40 181
AB 307 125 < 75 27 9 43 43 20 3 12 39 28 96
Office 379 198 < 30 27 8 80 37 48 11 38 131 1 90
School 381 237 < 15 34 1 108 28 23 7 8 162 29 106
Vienna (AT) SFH 451 97 < 30 51 28 38 30 0 0 0 98 248
AB 344 103 < 55 57 32 52 38 0 0 13 113 18 31
Office 525 75 < 10 43 18 9 11 17 5 5 49 11 70
School 540 77 < 15 45 33 8 12 9 0 8 47 10 57
Paris (FR) SFH 363 126 < 30 29 14 49 36 0 0 0 177 39 89
AB 336 99 < 55 27 13 30 30 0 0 18 173 196 296
Office 493 180 < 10 47 35 80 14 15 0 188 39 9 58
School 452 222 < 10 35 10 110 7 6 3 324 62 34 134
Prague (CZ) SFH 519 159 < 55 4 33 65 58 0 0 0 58 201 374
AB 303 164 < 100 30 7 122 40 0 0 38 38 8 134
Office 615 118 < 25 42 34 19 26 10 0 4 40 79 111
School 579 110 < 10 38 12 28 35 0 0 8 72 154 305
Berlin (DE) SFH 348 85 < 40 30 0 36 30 0 0 37 130 39 114
AB 319 161 < 70 38 29 47 47 0 0 22 189 31 45
Office 442 68 < 15 40 29 13 17 9 0 28 87 62 89
School 398 49 < 20 22 2 23 26 0 0 50 58 128 198
Helsinki (FI) SFH 203 76 < 65 64 80 72 0 0 42 42 100 110
AB 195 219 < 95 19 13 52 52 0 0 0 29 162 163
Office 371 109 < 35 56 34 31 28 0 0 27 27 72 131
School 339 179 < 30 47 25 48 20 0 0 0 55 70 154
a
If present, the reduction due to heat recovery strategies is taken into account
b
From thermal panels, PV systems and heat pumps, if present. This amount includes self-consumed and exported electricity
356 Energy Efficiency (2018) 11:337369
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Calculating the global cost
The global costs associated to each building variant
were estimated over a period of 30 years,
13
including
the capital costs (initial investment) for renovation, the
costs for the substitution of building elements with a
lifetime lower than 30 years, the annual maintenance
costs, the operating energy costs, the disposal costs, and
the final value of considered technologies. Considering
a financial perspective, the applicable taxes were con-
sidered and all cost items were discounted to 2011 with
real interest rates typical of the contests taken into ac-
count and based on the EUROSTAT statistics.
14
The
equation of global cost can be written as (Eq. 1):
CGτðÞ¼CI þ
f
τ
i¼1
Ca;ijðÞRdiðÞ

Vf;τjðÞ

ð1Þ
with C
G
(τ) the global cost referred to the starting year τ
0
,
CI the initial investment costs, C
a,i
(j) the annual cost for
component jat the year i,R
d.
(i) the discount rate for year
i,andV
f,τ
(j) the final value of component jat the end of
the calculation period.
The costs over the calculation period were discounted
by means of the discount factor R
d
, which is calculated
as (Eq. 2):
RdpðÞ¼ 1
1þr=100

p
ð2Þ
where pis the number of years of the period and ris the
real interest rate.
The cost database, on which the calculation was done,
was populated involving national experts who have pro-
vided data for the costs of materials, building elements,
and related labor. The experts referred mainly to two types
of references: existing national (or regional) databases
derived from large market-based data gathering and anal-
ysis of available data from recent renovation projects and
standard commercial offers. In these data collection activ-
ity, the main complementary works associated to each
refurbishment action were taken into account (e.g., reno-
vation of the doorsteps due to interventions on the floors
and suspended ceiling modification associated with the
installation of an air distribution system).
References on the cost data collected are provided in
Tables 13 and 14 for all technologies already introduced
above. About this, it is important to notice that signifi-
cant deviations among countries were observed for
some technologies. This reflects the economic differ-
ences of the contexts considered, from which the cost of
labor mainly depends, but also the lack of harmoniza-
tion between the national references used.
Also, in the global cost calculations, several assump-
tions were needed and, instead of using the estimated
long-term energy price developments proposed by the
Commission Guidelines (European Parliament 2012a,
b), the POLES scenarios were applied also for foresee-
ing the energy prices over the calculation period. They
are shown in Fig. 4.
13
It has to be noticed that this calculation period was used for both
residential and non-residential building types, in order to obtain com-
parable results. This choice introduces a difference with respect to the
methodology described in the Commissions Guidelines, which sets at
20 years, the calculation period for non-residential buildings.
14
http://epp.eurostat.ec.europa.eu/
Fig. 7 Breakdown of the costs associated with the retrofit solutions represented by the base refurbishment level and the cost-optimal and
NZEB benchmarks for the Spanish apartment blocks
Energy Efficiency (2018) 11:337369 357
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Tabl e 1 7 Envelope transmittances of the benchmarks selected in the cost-optimal and NZEB areas for each building type and climate. For
opaque surfaces, Uvalues greater than 0.6 W/m
2
K refer to the original (not renovated) elements
Climate and building type Envelope thermal transmittance [W/m
2
°K]
Cost-optimal NZEB
Wall Roof Basement Window Wall Roof Basement Window
Seville (ES) SFH 0.31 0.33 0.31 2.60 0.31 0.33 0.31 1.71
AB 0.31 0.33 0.31 5.83 0.22 0.23 0.22 1.69
Office 1.37 1.29 1.54 2.72 0.16 0.13 0.20 2.11
School 0.46 0.53 0.55 5.85 0.28 0.21 0.31 2.10
Madrid (ES) SFH 0.31 0.23 0.50 2.60 0.18 0.12 0.22 1.71
AB 0.31 0.23 0.50 2.58 0.18 0.12 0.22 1.69
Office 1.37 1.29 1.54 2.72 0.16 0.13 0.20 2.11
School 1.37 2.19 2.57 2.71 0.16 0.13 0.21 2.10
Rome (IT) SFH 0.30 0.32 0.32 2.60 0.22 0.23 0.23 1.71
AB 0.30 0.32 0.32 1.69 0.22 0.23 0.23 1.69
Office 0.27 0.20 0.29 2.11 0.15 0.13 0.21 2.11
School 0.27 0.20 0.29 2.10 0.15 0.13 0.21 2.10
Milan (IT) SFH 0.17 0.12 0.23 1.71 0.17 0.12 0.23 1.71
AB 0.22 0.18 0.32 1.69 0.17 0.12 0.23 1.69
Office 0.27 0.20 0.29 0.77 0.13 0.13 0.21 0.77
School 0.27 0.20 0.29 0.77 0.13 0.13 0.21 0.77
Bucharest (RO) SFH 0.22 0.18 0.30 1.03 0.18 0.12 0.22 1.03
AB 0.18 0.12 0.22 1.03 0.18 0.12 0.22 1.03
Office 1.34 1.01 1.10 2.11 0.12 0.10 0.19 0.77
School 1.34 0.70 1.10 2.10 0.12 0.10 0.19 0.77
Vienna (AT) SFH 0.22 0.17 0.33 1.71 0.17 0.12 0.23 1.03
AB 0.17 0.12 0.23 1.03 0.17 0.12 0.23 1.03
Office 0.15 0.15 0.27 0.77 0.11 0.11 0.20 0.77
School 0.16 0.16 0.27 0.77 0.16 0.16 0.27 0.77
Paris (FR) SFH 0.32 0.22 0.57 1.71 0.18 0.12 0.24 1.71
AB 0.18 0.13 0.24 1.69 0.18 0.13 0.24 1.69
Office 1.06 1.65 3.44 2.11 0.12 0.11 0.22 0.77
School 1.17 1.57 1.74 2.11 0.13 0.11 0.21 0.77
Prague (CZ) SFH 0.22 0.17 0.30 1.03 0.17 0.12 0.22 1.03
AB 0.63 0.65 1.24 2.66 0.17 0.11 0.22 1.03
Office 0.15 0.09 0.22 0.78 0.15 0.09 0.22 0.78
School 0.16 0.10 0.22 0.77 0.16 0.10 0.22 0.77
Berlin (DE) SFH 0.21 0.17 0.29 1.03 0.16 0.12 0.21 0.70
AB 0.16 0.12 0.23 0.70 0.16 0.12 0.23 0.70
Office 0.16 0.14 0.27 0.77 0.11 0.10 0.19 0.77
School 0.16 0.15 0.27 0.77 0.11 0.10 0.19 0.77
Helsinki (FI) SFH 0.17 0.12 0.48 1.03 0.17 0.09 0.48 0.70
AB 0.17 0.10 0.48 1.03 0.17 0.10 0.48 1.03
Office 0.09 0.09 0.16 0.78 0.13 0.12 0.21 0.78
School 0.14 0.12 0.23 0.77 0.10 0.09 0.17 0.77
358 Energy Efficiency (2018) 11:337369
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Where PV systems were installed, two different eco-
nomic values were associated to the self-consumed and
the exported electricity: the market price was used to the
self-consumed energy (i.e., an avoided electric con-
sumption); a lower value was considered for the
exported electricity instead (i.e., the 35% of the market
price). Taking into account that this differentiation does
not have an impact on the energy performance calcula-
tions (because a different primary energy factor was not
used for the exported electricity), it was assumed that
50% of electricity yearly generated was self-consumed
in the building by the electric loads of thermal systems
and lighting. The remaining 50% was evaluated as
exported to the grid. The influence of this simplifying
Tabl e 1 8 Qualitative summary of the thermal systems implemented in the benchmarks selected in the cost-optimal and NZEB areas for each
building type and climate
Climate and
building type
Cost Opmal NZEB
High-efficiency
H/C generator(s)
Heat
recovery
strategy
High-efficiency
lighng
Thermal
solar
system
Photovoltaic
system
Automac
natural
venlaon
High-efficiency
H/C generator(s)
Heat
recovery
High-efficiency
lighng
Thermal
solar
system
Photovoltaic
system
Automac
natural
venlaon
Seville
(ES)
SFH
AB
Office
School
Madrid
(ES)
SFH
AB
Office
School
Rome
(IT)
SFH
AB
Office
School
Milan
(IT)
SFH
AB
Office
School
Bucharest
(RO)
SFH
AB
Office
School
Vienna
(AT)
SFH
AB
Office
School
Paris
(FR)
SFH
AB
Office
School
Prague
(CZ)
SFH
AB
Office
School
Berlin
(DE)
SFH
AB
Office
School
Helsinki
(FI)
SFH
AB
Office
School
Energy Efficiency (2018) 11:337369 359
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assumption on the final results was assessed (see below
BMain results^section).
The other main assumptions regarding costs include
the choice of the annual maintenance cost and the
lifespan of the technologies studied. Both of these data
were taken from the standard EN 15459 (CEN 2007d).
Moreover, annual increase rates of costs of the refur-
bishment actions were taken into account. Specifically, in
accordance with Hermelink et al. (2013), an increase rate
of 12% per year was applied to the insulation measures;
to the low-grade renovation alternatives of window sys-
tems; to solar shading devices, lighting systems, and con-
densing boilers; and to sub-components of distribution,
emission, and control. For the high-grade window solu-
tions and to several system options (standard gas boilers,
heat pumps and chillers, heat exchangers, and ST and PV
panels),adecreaserateof13%peryearwasused.
In accordance with the EPBD framework, some eco-
nomic parameters were considered static over the calcu-
lation period. While for the macroeconomic perspective,
a real interest rate of 3%
15
was used, that one relative to
the financial point of view was calculated for each context
(Table 15) as difference between the nominal (market)
interest rate and the inflation rate. As source, the
EUROSTAT data over the period 20082011 were used.
The tax references needed under financial perspective
were collected by the national experts, and the costs of
the environmental externalities (carbon price, in /tCO
2
)
used in the macroeconomic one were obtained with the
POLES model as a trend over the period 20112050.
To obtain absolute references, the incentive policies
in force in the studied national/regional contexts were
not taken into account.
Identification of targets and benchmarks
ReferringtotheschemeshowninFig.5,thetargetswere
quantified by post-processing procedures that have auto-
mated the analysis of clouds, resulting from the calculation
phase. As encouraged
16
by the EU Regulation (European
Parliament 2012a,b), the cost-optimal level was identified
as the minimum (net) primary energy level within the
interval (often quite large) with a global cost lower than
the absolute minimum one increased by 3%. Otherwise,
the NZEB target was obtained incrementing by 10 kWh/
m
2
/year the minimum primary energy achieved by the best
building variant (from the energy point of view). The
incremental factors (3% for global cost, 10 kWh/m
2
/year
for NZEB, as well as those discussed below) are not
provided by the Commission Guidelines or by other refer-
ences. They were defined so as to be suitable for defining
targets accessible to different retrofit options.
To provide exemplary technological benchmarks (i.e.,
packages of exemplary retrofit options satisfying the tar-
gets), a portion of the Energy-Cost domain was studied for
both targets. These areas are limited inferiorly by the lower
frontier of cost-energy cloud (i.e., the profile of cost-opti-
mality), and they were defined applying a range of
± 5 kWh/m
2
/year in net primary energy and an upper limit
of cost equal to the minimum global cost for the specific
target increased by 10%. These factors were chosen for
identifying areas populated by a number of building vari-
ants neither too small nor too big (i.e., about 2050).
To apply the EPBD principle of priority of efficiency
solutions involving the building envelope,
17
the build-
ing variants within these areas were further filtered.
Firstly, only the cases with energy needs for heating
and cooling lower than the minimum value incremented
by 10 kWh/m
2
/year were considered. Then, the
resulting variants were statically analyzed to recognize
the more frequently occurring technologies. If the result
obtained was not representative of any real variant pres-
ent in the studied area, priority was given firstly to the
most recurrent envelope combination and then to those
relative to thermal systems and RES technologies.
Results and discussion
Main results
The main aim of this study is to find possible targets of
(net) primary energy representative of the cost-optimal
and nearly zero-energy levels and to provide examples
15
This value is suggested as reference by the Commission Guidelines
(European Parliament 2012a,b).
16
BIn cases where the outcome of the cost-optimal calculations gives
the same global costs for different levels of energy performance,
Member States are encouraged to use the requirements resulting in
lower use of primary energy as the basis for comparison with the
existing minimum energy performance requirements^(Annex I, Cap.
6-2).
17
BMember States shall take the necessary measures to ensure that
minimum energy performance requirements are set for building ele-
ments that form part of the building envelope and that have a signifi-
cant impact on the energy performance of the building envelope when
they are replaced or retrofitted, with a view to achieving cost-optimal
levels^(Article 4).
360 Energy Efficiency (2018) 11:337369
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of the associated complete retrofit solutions (i.e., tech-
nological benchmarks), for all climates (10) and build-
ing types (4).
In accordance with the methodology described in the
previous section, 40 data sets were plotted on the
Energy-Cost plane, obtaining 40 characteristic clouds.
For example, Fig, 6shows the results obtained in terms
of annual (net) primary consumption (x-axis) and global
costs (y-axis) for the apartment block in Vienna.
The analysis of clouds allows deriving some key ref-
erences. Table 16 provides an overview of results obtained
for each building type in each climate. The section
BTar gets ^shows the energy levels associated to three
characteristic points of every cloud (i.e., base refurbish-
ment level, cost-optimal target, and NZEB target), as well
as the percentage difference between the global costs
calculated for the targets with respect to the BRL. The
section BBenchmarks^shows the main energy perfor-
mance of the specific building variants (i.e., retrofit solu-
tions) selected within the cost-optimal and NZEB areas, as
well as the percentage difference between the investment
costs of these variants with respect to the BRL. All these
results refer to the financial perspective with base year
2011andtotheBReference^scenario discussed above.
About the targets shown, it is interesting to observe that
the cost-optimal levels imply an average reduction of 66%
in primary energy and of 27% in global costs, with respect
to the base refurbishment levels. Maximum values of net
primary energy for the NZEB targets
18
of 40, 75, and
100 kWh/m
2
were recognized as obtainable respectively
for the South, Central, and North European areas.Often (27
times out of 40), the NZEB levels result economically more
advantageous (lower global costs) than the b ase renovation
Levels, especially in the Central-North Europe.
About the investment coststhe main barrier to the
widespread diffusion of efficient refurbishmentsit has to
be noticed that their average increases with respect to the
BRL for the cost-optimal and NZEB targets are respec-
tively of 50 and 115%. However, some results demonstrate
the possibility to reduce the base refurbishment investment
costs, moving towards cost-optimal solutions. For in-
stance, this is the case of the residential types located in
Milan and Vienna, where the improvement of the building
envelopes allows avoid the expenditure related to the
installation or substitution of an active cooling system.
Interesting are also the cases of the apartment
blocks located in Spain (Seville and Madrid), where
the NZEB benchmarks have a lower investment cost
of the cost-optimal ones. However, in spite of the fact
they also have lower energy running costs, the global
SFH
AB
Office
School
Sevilla
Madrid
Rome
Milan
Bucharest
Vienna
Paris
Prague
Berlin
Helsinki
PV panels
high performance hgihepolevne efficiency generators (cond ensing boiler
or GSHP or district heang)
mechanincal venla on with
heat recovery
Fig. 8 Schematic representation of the technological benchmarks
obtained within the analyzed cost-optimal areas for all building
types in all climatic contexts. The 40 cost-optimal buildings are
collected in the appropriate set, depending on their classification
regarding the performance of the envelope, the efficiency of gen-
erators, the presence of a heat recovery strategy, and the presence
of a PV system
18
These maximum values are always associated to the apartment
block typethat shows a lower energy saving potential due to geometric
limits (e.g., lower available roof surface for solar systems).
Energy Efficiency (2018) 11:337369 361
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Tabl e 1 9 Influence of the boundary conditions on the cost-optimal targets, in terms of percentage difference in (net) primary energy with
respect to the reference condition (financial perspective with starting year 2011 and BReference^scenario)
Climate and building type Financial perspective Macroeconomic perspective
BAmbitious^(%) BReference^(%) BAmbitious^(%)
Seville (ES) SFH 13 19 13
AB 878
Office = = 10
School 22 = 20
Madrid (ES) SFH 19 10 37
AB 12 = 16
Office = = 29
School = = 36
Rome (IT) SFH 20 7 35
AB 13 = 30
Office 68 10 74
School 19 = 43
Milan (IT) SFH 13 = 21
AB 17 817
Office 70 15 88
School 25 = 33
Bucharest (RO) SFH 36 = 49
AB 7=
=
Office 72 = 63
School 50 = 30
Vienna (AT) SFH 9917
AB 10 = 14
Office 26 622
School 25 = 14
Paris (FR) SFH 25 10 16
AB 24 = 15
Office 73 = 16
School 58 33 36
Prague (CZ) SFH 14 = 45
AB = = =
Office 19 = 36
School = = 43
Berlin (DE) SFH 12 = =
AB 7=7
Office 22 = 18
School 11 79 19
Helsinki (FI) SFH 14 914
AB = = =
Office = 13 =
School 840 26
B=^no relevant variation (range between ± 5%)
362 Energy Efficiency (2018) 11:337369
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costs are slightly higher than the cost-optimal retrofit
solution. This can be explained by analyzing the
other cost items considered in the calculation. As
showninFig.7, the NZEB benchmarks have higher
replacement and maintenance costs, also because of
retrofit solutions with lower lifespan (e.g., fancoils)
compared to more expensive alternatives (e.g., radi-
ant floor). This type of result is due to the contingent
proximity between the cost-optimal and NZEB areas
for these Spanish cases, but it is also symptomatic of
the methodology applied (i.e., non based on multi-
stage optimization techniques).
In general, the NZEB area appears characterized by
medium-high and high recurrences of efficiency and
RES technologies in all countries and for both the build-
ing destinations. For instance, a typical NZEB building
has a well-insulated envelope (including insulation
layers of 1030 cm and double or triple low-e win-
dows), efficient generators (e.g., condensing boiler or
ground source heat pump or district heating) in some
case assisted by heat recovery strategies, and renewable
solar systems installed (normally both thermal and pho-
tovoltaic). More details are provided below in Tables 17
and 18 for each building and climatic condition.
Otherwise, the cost-optimal benchmarks are more
heterogonous. Various are the retrofit solutions able to
reach this target, that overall is characterized by the
competition between the deepest actions regarding
envelope, thermal systems, and solar renewable sys-
tems. Figure 8provides a qualitative overview of cost-
optimal benchmarks which are classified in function of
their strengths. As expected, it is difficult to minimize
the global costs applying a high-performance envelope,
very efficient generators, a heat recovery strategy, and a
PV plant at the same time. This occurs only for the
single-family houses located in Milan, Berlin, and
Helsinki, which lie in the intersection of all sets.
Filtering also on the energy needs for heating and
cooling (as discussed above), more than half (23 cases)
of the benchmarks obtained are characterized by
Fig. 9 Example of change in the lower profile of the Energy-Cost cloud depending on economical perspective and price scenario
0
25
50
75
100
125
150
175
200
225
-1%0%1%2%3%4%5%6%
Cost-Opmal target [kWh/m2/y]
Annual energy price development
Office - Milan School - Paris
Fig. 10 Dependency of the resulting cost-optimal target from the
energy prices development for two case studies (office in Milan
andschoolinParis)
Energy Efficiency (2018) 11:337369 363
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medium-high levels of insulation (1020 cm) and by
double or triple glazing low-e windows. In 16 cases, the
deep grade renovation of envelope is coupled with the
installation of an efficient generators (condensing boiler
or ground source heat pump or connection to district
heating). Only for four residential building variants,
there is also the presence of heat recovery strategies
and photovoltaic generation. Among these, it is interest-
ing the case ofthe single house inMilan, where the cost-
optimal variant results those with the best envelope
solutions
19
because it avoids the need for active cooling
systems. Differently, for other South European types
(particularly in the Spanish contexts, where the saving
potential of envelope strategies is lower and the solar
radiation is higher), the cost-optimal level can be repre-
sented by medium-low envelope renovations compen-
sated by photovoltaic systems.
About the thermal systems, normally, both cost-
optimal and NZEB targets require the substitution of
the original thermal generators with more efficient tech-
nologies and the insulation of distribution pipes.
Particularly, in the cost-optimal area, the penetration of
simple system layouts is favored (e.g., reversible heat
pump coupled to a single distribution and emission
system). Otherwise, the mechanical ventilation strate-
gies (often associated to heat recovery) can get into
economic competition with envelope and RES solu-
tions, also in the NZEB area.
20
Medium-low
temperature emission systems for heating often occur
both in the NZEB and cost-optimal areas. In some
climate contexts, biomass and district heating systems
occur with low frequency in the benchmark areas. This
might be due also to difficulties in defining the actual
primary energy factors, the investment costs (due to
different installation conditions), and the energy prices
(due to private negotiation).
RES technologies represent a key strategy to reach
the zero-energy target in all the analyzed contexts (e.g.,
also for the residential buildings of Berlin). Moreover,
the more efficient lighting strategies appear always a
good intervention to reach NZEB area, especially in
office buildings.
Being a crucial aspect of the EPBD framework, in
order to provide more detailed information about the
features of the selected retrofit solutions, the thermal
transmittances obtained for the main envelope elements
are presented in Table 17 and qualitative indications of
thermal systems adopted are shown in Table 18, for both
the cost-optimal and NZEB areas.
Sensitivity analysis
In compliance with the EU cost-optimal Regulation
21
(European Parliament 2012a,b), it is interesting to study
the influence of some key input data on the main calcu-
lation results. As discussed above, in the present study,
the macroeconomic perspective was also evaluated and
two energy price scenarios (BAmbitious^besides
BReference^)wereconsidered.
19
With automatized night natural ventilation and high-performance
solar shading systems, as well as high insulation levels and very low
infiltrations during the day.
20
In this study, the penetration of mechanical ventilation with or
without heat recovery, is compared with a good user behavior of
occupants, who correctly open windows when air changes are needed,
avoiding excessive openings. This helps to obtain natural ventilation
solutions in the cost-optimal and sometimes also in the minimum net
primary energy area more often with respect to mechanical ventilation.
Clear real time signals on IAQ and training of occupants, in this way,
could be a cost-effective strategy to reduce the initial investment,
annual, and energy costs, without reducing the indoor air quality.
21
BMember States shall undertake an analysis to determine the sensi-
tivity of the calculation outcomes to changes in the applied parameters,
coveringat least the impact of different energy price developments and
the discount rates for the macroeconomic and financial calculations,
ideally also other parameters which are expected to have a significant
impact on the outcome of the calculations such as price developments
for other than energy^(Article 3).
100
125
150
175
200
225
250
1% 2% 3% 4% 5% 6% 7% 8% 9% 10%
Cost-Opmal target [kWh/m2/y]
Real interest rate
(a)
100
125
150
175
200
225
250
3 5 7 10152025303540
Cost-Opmal target [kWh/m2/y]
Calculaon period [years]
(b)
Fig. 11 Dependency of the
resulting cost-optimal target from
the real interest rate (a) and the
calculation period (b)(officein
Milan)
364 Energy Efficiency (2018) 11:337369
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In order to provide a quantitative overview of the
influence of these standpoints on the lower frontier (i.e.,
the optimal frontier) of the Energy-Cost clouds, the
changes of the cost-optimal targets are reported in
Table 19. In general, the higher energy price scenario
(BAmbitious^) increases the global costs (mainly com-
posed of initial investment and running costs due to
energy) of the less efficient variants and leads to a lower
value of net primary energy for the cost-optimal level.
Not considering taxes and introducing the prices for
CO
2
emissions, as required by the macroeconomic per-
spective, the global costs of the more efficient refurbish-
ments decrease, moving again the cost-optimal target
towards the NZEB one. These effects are shown for an
exemplary case in Fig. 9.
The higher energy price scenarios increase the min-
imum global cost range and lead to a lower value of net
primary energy for cost-optimal levels, as well as the
increase of prices for CO
2
emissions (and eventual costs
related to environmental damages or other externalities).
In some cases, the cost-optimal profiles are very flat and
this can imply that a moderate change of input data
results in a significant variation of outputs.
As discussed by Boermans et al. (2011), the assumed
development of energy prices is one of the most critical
input data because many energy prices have a strong
national (or regional or even local) influence and the
forecasts have to take into account expected longer-term
political and economic developments. Moreover, its
overall influence on the final results is not necessarily
linear, and indeed discontinuities can be observed. For
instance, referring again to the identification of the cost-
optimal target, this is the case of our school located in
Paris and mostly the office in Milan (Fig. 10). Here,
varying all energy prices (i.e.,electricity and natural gas)
by the same annual developments in the range 1/6%,
the optimum selection procedure reveals a pronounced
discontinuity between 2 and 3%. This effect is more
relevant for those building types characterized by a cost-
optimal frontier very flat.
Other calculation parameters for which a sensitivity
analysis is recommended by the EC Regulation are the
real interest rate and the calculation period. For these
variables, a more linear dependency was observed, as
shown in Fig. 11 for the example of the office located in
Milan. As expected, the cost-optimal target increases
with increasing real interest rate because the future
economic savings (greater for low net primary energy
levels) are more discounted at high interest rates.
Otherwise, the target decrease with increasing the cal-
culation period until the thirtieth year and slightly in-
crease after, because of the periodic costs for replace-
ment occurring at year 31,
22
which are greater for the
more efficient renovation packages.
Because of the assumption made on the self-
consumption of the electricity generated on-site by the
photovoltaic systems (set to 50% for all building types),
it is interesting to evaluate the influence of this variable
of the final results. As shown below for the critical case
of the Milanese office (Fig. 12), a minor influence was
observed, especially in the range 4570%.
Conclusions
The first cost-optimal calculations of the European
Member States
23
have been recently evaluated by the
European Commission (Boermans et al. 2015; Zirngibl
and Bendzalova 2015), and it is quite evident that dif-
ferent interpretations of the procedure prescribed by the
EPBD framework were adopted. The present large-scale
study provides reliable references obtained under com-
mon boundary conditions and calculation assumptions
for a representative sample of the EU-28 area. The
quantitative results found here for the refurbishment
sector are obviously depending on the typologies of
selected buildings, but they allow a direct comparison
between a high number of climatic and economic con-
texts across the EU.
Taking as reference the existing buildings of 60s
70s, the energy saving potential of found cost-optimal
22
According to Standard EN 15459 (CEN 2007d), a lifetime of
30 years was considered to the majority of envelope technologies.
100
125
150
175
200
225
250
25%
30%
35%
40%
45%
50%
55%
60%
65%
70%
Cost-Opmal target
[kWh/m2/y]
Self-consumed electricity from PV systems
Fig. 12 Dependency of the resulting cost-optimal target from the
percentage of self-consumed electricity from PV systems (office in
Milan)
23
The MSs reports are available on http://ec.europa.
eu/energy/en/topics/energy-efficiency/buildings
Energy Efficiency (2018) 11:337369 365
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
targets are very relevant (3688% in term of net primary
energy) for all analyzed cases and the achieved NZEB
levels resulted interesting also from an economic point
of view: their global costs (over 30 years) are often
lower than the respective base refurbishment levels (as
defined in this study) and never greater than 33%.
While a further recast of EPBD has been an-
nounced and it is under approval, it is interesting to
observe that the EPBD framework provides a useful
guidance for cost-optimal calculations. However, to
achieve a more uniform implementation in the
Member States (or at least to improve the comparison
possibilities), more detailed indications would be
needed and some boundary conditions should be
better defined. Taking into account the methodology
developed within this study and the application to a
quite large amount of building types and climatic/
economic conditions, some suggestions can be
provided.
The method used to calculate the energy demands
associated to the building renovations provides a
good compromise between detail and simulation ef-
fort, for this type of study. The preliminary choice to
develop the analysis avoiding search-optimization
techniques makes an easier comparison between ret-
rofit options (sometimes competing among them-
selves) and allows an easier assessment of the influ-
ence of the main calculation parameters. However,
the high number of building variants can complicate
the analysis and interpretation of final results, which
depend on many calculation factors.
The comparison of the retrofit variants in the primary
energy/global costs domain allows identifying quite
clearly some reference targets and technical solutions
that can guide the development of new energy require-
ments and targeted policy. However, the clouds (or
curves) obtained cannot show explicit information about
the energy needs for the different energy end-uses of a
building and the initial investment costs of a renovation
action. Details about these aspects should be explicitly
requested by the procedure and references about the
priority of technologies taken into account for the selec-
tion of benchmark should be clarified.
While, for new buildings, it is quite simple to define a
reference building variant (e.g., the one that meets the
current energy requirements), this aspect is not fully
regulated for existing buildings. For the calculation
experience here reported, the concept of base refurbish-
ment level was introduced to obtain homogeneous
building variants (in terms of functionality, esthetic as-
pect, and comfort levels) and to recognize which costs
could be omitted. This baseline has proved a useful
reference for a direct evaluation of the results, and it
should be proposed for further applications of the EPBD
calculation framework.
As a function of the cost range chosen, the cost-
optimal area can be very wide in terms of net primary
energy range and the simple encouragement for the
minimum target of (net) primary energy could represent
a too soft indication that could introduce discrepancies
between the analyses of the different Member States.
The choice of the cost range should be standardized: in
this study, an increment of 3% was applied on the
minimum value of global cost.
The collection of consistent and reliable data for costs
associated to the renovation actions is undoubtedly one
of the most critical steps of this kind of analysis.
Because erroneous data or non-homogeneous database
may have a substantial influence on the final results,
solid references should be defined and provided to
Member States by the European Commission. As
starting point, the national databases used for the first
run of cost-optimal calculations done by the Member
States, as well as those developed within parallel studies
(as the one discussed here), should be considered.
The EU cost-optimal methodology focuses on the
building variants of the lower frontier of the Energy-
Cost clouds. Of course, this part of the graphs repre-
sents the most profitable solutions in terms of global
costs, but also the variants with higher global costs
might represent interesting solutions in terms of en-
vironmental value or energy efficiency solutions that
might reach the cost-optimal area if supported with
incentive policies. To evaluate this possibility, it is
essential to define as much as possible the Energy-
Cost clouds, rather than limiting the analysis to opti-
mization procedures able to produce only the cost-
optimal curve.
Acknowledgements We are grateful to all Partners of the
ENTRANZE project for their contributions and in particular to
the project coordinator Lukas Kranzl (Energy Economics Group,
Vienna University of Technology) and to Maria Fernandez Boneta
and Ines Diaz Regodon (CENER) for great scientific and technical
support.
366 Energy Efficiency (2018) 11:337369
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Energy Efficiency (2018) 11:337369 367
Compliance with ethical standards
Conflict of interest The authors declare that they have no con-
flict of interest.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestrict-
ed use, distribution, and reproduction in any medium, provided
you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons license, and indicate if
changes were made.
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... Policy development for heating and cooling has been accompanied by increasing academic attention for the role of heat and heat planning in decarbonisation. At the EU level, this has included reviews of the heating sectors (Bertelsen & Mathiesen, 2020) and the built environment (Zangheri, et al., 2018), as well as historical analysis of transitions in heating and cooling (Bertelsen, Mathiesen and Paardekooper, 2021;Gross & Hanna, 2019). Parallel, research has developed various strategies for decarbonisation, including considering DH (for example Colmenar-Santos et al, 2016;Connolly et al., 2014;Kozarcanin, et al., 2020). ...
... When looking at another perspective of the heating sector in the form of energy performance of buildings, similar representations are observed; geographical (including specifically Scandinavia) ( Bartiaux et al., 2011), climatic conditions (Zangheri et al., 2018) but also political economies, for example "post-Socialist" representations (Cirman, Mandic, Zoric 2013). However, it is to be strongly noted that the useful typologies when assessing building stocks and renovations are usually disaggregated to the age, size, and type of building, rather than a characterisation of the stock overall between countries, since this much better captures the variance within the stock and facilitates more granular analysis, which can then be used to develop cross-country analysis (Filogamo, Peri, Rizzo, Giaccone, 2014;Loga, Stein, Diefenbach 2016). ...
Article
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In order to support European-wide transition of heating systems, it is useful to categorise the types of transitions that are necessary. Coherent actions are needed at (supra-)national level to support transition aligned with the energy efficiency first principle and long-term development of a smart energy system. Owing to the decentralised nature of heating, transition must also reflect particular local circumstances. This article uses commonalities between countries to create a representative typology, which can suggest appropriate policies for transition. Following the energy efficiency first principle, transition should include supply-side and demand-side efficiency to ensure coherency and efficient use of resources. Their comparative analysis supports implementing the energy efficiency first principle locally, and a more coherent European strategy for the heating sector. Methodologically, 14 national heating strategies are considered which include current and future energy system developments, demand- and supply side energy efficiency, hectare-level thermal mapping and energy system analysis. Four heat sector types are proposed and discussed. These are (1) extant heat planning traditions, aiming for more efficiency and integration; (2) extant heating infrastructure, aiming to refurbish and upgrade both building stock and existing heating infrastructure; (3) existing gas infrastructure, requiring radical transition; (4) and those without strong historic heat planning traditions.