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Cost-optimum analysis of building fabric renovation in a Swedish multi-story residential building
Energy and Buildings 84 (2014) 662–673
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Cost-optimum analysis of building fabric renovation in a Swedish multi-story residential building Farshid Bonakdar ∗ , Ambrose Dodoo, Leif Gustavsson Sustainable Built Environment, Faculty of Technology, Linnaeus University, Växjö SE-35195, Sweden
a r t i c l e
i n f o
Article history: Received 24 March 2014 Received in revised form 2 June 2014 Accepted 2 September 2014 Available online 10 September 2014 Keywords: Building renovation Building fabric Energy simulation Space heating Insulation Energy efficiency Cost-optimum renovation Sustainability Windows
a b s t r a c t In this study, we analysed the cost-optimum level of building fabric elements renovation in a multi-story residential building. We calculated final energy use for space heating of the building considering a wide range of energy efficiency measures, for exterior walls, basement walls, attic floor and windows. Different extra insulation thicknesses for considered opaque elements and different U-values for new windows were used as energy efficiency measures. We calculated difference between the marginal saving of energy cost for space heating and the investment cost of implemented energy efficiency measures, in order to find the cost-optimum measure for each element. The implications of building lifespans, annual energy price increase and discount rate on the optimum measure were also analysed. The results of the analysis indicate that the contribution of energy efficiency measures to the final energy use reduces, significantly, by increasing the thickness of extra insulation and by reducing the U-value of new windows. We considered three scenarios of business as usual (BAU), intermediate and sustainability, considering different discount rates and energy price increase. The results of this analysis suggest that the sustainability scenario may offer, approximately, 100% increase in the optimum thickness of extra insulation compared to BAU scenario. However, the implication of different lifespans of 40, 50 or 60 years, on the optimum measure appears to be either negligible or very small, depending on the chosen scenario. We also calculated the corresponding U-value of the optimum measures in order to compare them with the current Swedish building code requirements and passive house criteria. The results indicate that all optimum measures meet the Swedish building code. None of the optimum measures, however, meet the passive house criteria in BAU scenario. This study suggests that the employed method of building renovation cost-optimum analyses can be also applied on new building construction to find the cost-optimum design from energy conservation point of view. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Buildings account for 40% of total primary energy use [1] and 36% of CO2 emissions [2] in the European Union (EU). The EU directive on energy performance of building [3] requires member states to set minimum requirements for energy performance of buildings and building elements. That includes existing buildings that are subject to major renovation. This directive demands for considering cost-optimal balance between the investment and the saved energy cost during the lifespan of a building. According to EU Parliament Directive of 2012/27/EU [4], the existing building stock represents the single biggest potential sector for energy savings. It suggests that buildings are crucial to achieve the EU objective of reducing greenhouse gas emissions by 80–95% by 2050 compared
∗ Corresponding author. Tel.: +46 470 767595; fax: +46 470 768540. E-mail address: [email protected] (F. Bonakdar). http://dx.doi.org/10.1016/j.enbuild.2014.09.003 0378-7788/© 2014 Elsevier B.V. All rights reserved.
to 1990. The Swedish government targets 20 and 50% total final energy use reduction per heated building area by 2020 and 2050, respectively, using 1995 as the reference [5]. Directive 2012/27/ EU urges member states to establish a long-term strategy for mobilising investment in building renovation. This strategy should identify and then include cost-effective approaches to renovation, depending on the building type and climate zone. Energy is used during the whole life cycle of a building, i.e. construction, operation and end-of-life phases. Various researchers have studied final energy use in the entire life cycle of buildings (e.g. [6–10]) and show that the operation phase contributes, significantly, to the life cycle final energy use of buildings. Ramesh et al. [8] conducted a literature review study on life cycle final energy analysis of 73 residential and office buildings in northern and central Europe, Canada, tropical region of Asia and Australia. Their results suggested that the final operation energy use contributes to about 80 to 90% of life cycle energy use in residential buildings. Space heating of buildings is a substantial part of total operation energy.
F. Bonakdar et al. / Energy and Buildings 84 (2014) 662–673
According to the European Environment Agency [11] space heating accounts for about 68% of total operation energy use of buildings in European countries. Improved energy efficiency measures for space heating of existing buildings can provide substantial opportunity to reduce the primary energy use and CO2 emission. In Sweden, there is a significant potential to reduce primary energy use by decreasing the space heating demand of existing buildings. About 40,000 apartment buildings with almost 920,000 dwellings and about 480,000 single family houses were constructed between 1961 and 1975 in Sweden [12]. Most of these buildings are still in good condition from serviceability point of view and are projected to undergo major renovation within the next 20 years [13]. There are numerous energy efficiency measures that can reduce final operation energy use of buildings. The measures may include ventilation heat recovery systems, efficient hot water taps, efficient electrical appliances and improved thermal performance of building fabric elements. Various researchers have studied energy implication of different energy efficiency measures for building renovation. Gustavsson et al. [14] analysed a multi-story woodframe residential building constructed in 1995 in southern part of Sweden. They evaluated the effects of various energy efficiency measures on district heated (henceforth DH) buildings. They found that implementing more energy-efficient doors and windows, additional exterior walls insulation and additional roof insulation could reduce the final space heating by 35%. Dodoo et al. [5] analysed the effect of retrofitting a wood-frame building to a passive house standard. They considered improved water taps and building elements as well as ventilation heat recovery. They found that space heating could be reduced by 39% by improving the insulation on external walls and roof and changing doors and windows. The costeffectiveness of the building energy renovation, however, was not analysed in these studies. In another study, Ouyang et al. [15] analysed a 27-year old residential building in China. They considered six energy efficiency measures including external doors and windows improvement, adding insulation on the exterior walls and the roof, applying light colour on the envelope and applying curtains or blinds to exterior windows. They calculated final energy use and CO2 emission and analysed the economic implication of considered energy efficiency measures. They suggested that the considered measures are not cost effective unless the government provides subsidy and increase electricity price. The considered information of energy balance and economy analysis, however, has not been provided in details in this study. Dall’O’ et al. studied the energy saving potential of retrofitting the residential building stocks in five municipalities of Milan in Italy [16]. They considered windows replacement, facade extra insulation, roof extra insulation and air loss reduction of ventilation. They considered three economic scenarios: no incentive, tax deduction of 36% and tax deduction of 55%. The energy and economic analysis was performed to calculate the simple payback time for considered measures. Wahlström et al. [17] studied the implications of new building regulation on the major renovation of apartment buildings. They also analysed the profitability of energy-efficiency measures of existing multifamily houses. Their analysis involve the optimal life cycle costs of energy-efficiency measures in combination with four types of heating systems, considering 30 years calculation period and 3% discount rate. Ecofys report of cost-effectiveness climate protection [18] quantified the required investments and cost-effectiveness of energy efficient building envelope elements for cold, moderate and warm climate zones in Europe. In another report of Ecofys [19], the feasibility of deep renovation in European countries was studied. This report used case-studies for deep renovation programme in German low energy building stock. The results were then extrapolated to other European countries. The price level indices, mortgage
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rates, inflation rates, energy prices and heating degree days were taken into account in this study. They suggested that superficial renovations of buildings increase the risk of missing Europe long term climate target and that immediate deep renovation action is necessary for the European building stock. In this study, we analysed the optimum level of renovating the building fabric elements. We calculated the marginal difference between the saving of final energy cost for space heating due to energy efficiency measures and the cost of implementing those measures to renovate building fabric elements. Changing the existing windows to the ones with lower U-value, implementing extra insulation on exterior walls, basement walls and attic floor were considered, in order to find the optimum U-value for windows and thickness for extra insulation. The implication of different parameters such as discount rates, energy price increases and the lifespans of considered energy efficiency measures on cost-optimum measures were then analysed. 2. Methods 2.1. General approach We considered an existing building and studied the implication of energy renovation measures on final energy use for space heating. We analysed the contribution of thermal performance improvement of the building fabric elements to the final energy demand. The optimum choices of efficiency measures of individual elements were then analysed, from economic point of view. The overall approach of our study consists of the following parts: (1) Modelling the energy balance of the building to calculate final energy for space heating; (2) analysing the contribution of each energy efficiency measure to final energy savings; (3) performing the cost-optimisation analysis for each considered elements; (4) analysing the sensitivity of optimum measures to discount rates, energy price increase and lifespans of the considered elements. 2.2. Case-study building This study is based on a 50-year old multi-story residential building located in the city of Växjö in south of Sweden. It was constructed in 1964 as part of the Million Programme, running from 1960s to early 1970s in Sweden [12]. The existing residential building stock of Sweden appears to be relatively old but still in good condition from serviceability perspective. The housing statistics in the European Union [20] indicates that 19, 25 and 39% of the existing residential building in Sweden in 2008 are above 80, 70 and 60 years old, respectively. This report also indicates that 100% of existing buildings in the year 2008 in Sweden were equipped with central heating, hot running water and bath and shower. This may be used as a qualitative indication of building general condition for the existing residential buildings. This indication is, in average, 98, 97 and 83% in the UK, France and Poland, respectively [20]. The case-study building has eighteen apartments in three floors and six flats on ground floor. It is a concrete-frame building with brick cladding. Fig. 1 shows a view of the building. Total heated floor area of the building is 1430 m2 . Total ventilated volume is 3710 m3 which includes total volume of living space and the volume of common space, e.g. stair case where different temperatures are required. The required information of the building for the analysis was extracted from existing drawings provided by the building
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Table 1 Total area (m2 ) of the building fabric elements. Building elements on each facade
Exterior walls of facade
Basement walls, above ground level
Basement walls, below ground level
Windows and the glass share of doors
Attic floor
South facade North facade West facade East facade
160 220 107 107
38 22 12 18
110
127 55 7.5 6.5
400
Fig. 1. South-west view of the case-study building.
owner. This includes the details of geometry and thermal characteristics of building fabric elements. The areas of building fabric elements are shown in Table 1. Building attic floor consists of a concrete slab with the thickness of 200 mm and mineral wool insulation of 150 mm in its initial state. The existing windows of the building have the U-value of 2.9 W/m2 K [21]. The details of exterior walls are different in different sides of the building. The eastern and western exterior walls consist of 140 mm concrete, 100 mm mineral wool with thermal conductivity of 0.04 W/m K and 120 mm brick cladding. The northern and southern exterior walls consist of 70 mm lightweight concrete, 100 mm mineral wool with thermal conductivity of 0.04 W/m K and 120 mm brick cladding. The basement exterior walls consist of concrete with mineral wool insulation on the internal side of the walls [21]. The connections between exterior walls and floor slabs as well as the corners of the building, where two walls are connected together, are recognised to be the main sections for thermal bridges and considered in our building energy simulation. The airtightness of the building is about 0.8 l/m2 /s [22]. The ventilation system of the building is an exhaust air fan that is, constantly, working every day during the entire year. We assumed that it has the pressure of 200 Pa and efficiency of 50% with the flow rate of 0.35 l/m2 /s [23]. The case-study building is heated by district heating system in the city of Växjö where more than 95% of the produced district heating is based on biomass-based. production unit with the overall conversion efficiency of about 107% [24]. 2.3. Energy efficiency measures Different U-values for new windows and different thicknesses of extra insulation materials for exterior and basement walls and attic floor were considered for the analysis. We considered mineral wool panels, cellplast panels and mineral wool blanket as additional insulation on exterior walls of the facade, external side of the basement walls and attic floor, respectively. The existing windows were assumed to be replaced with improved triple glazed windows with lower U-values. The U-value reduction of windows may reduce solar transmittance as well [25]. Total and direct solar transmittances of new windows were taken into account in the building energy balance simulation. We assumed that indoor temperature of living area is influenced by windows improvement. The indoor temperature of living area was considered to reduce from 22 ◦ C to
21 ◦ C after implementing efficient windows assuming that the user thermal comfort could be maintained at lower indoor temperature due to the increased inside surface temperature of the new windows. Different thicknesses of considered insulation materials and different improved U-value of windows and the investment cost of implementing all considered measures were calculated to find the optimum thickness of extra insulation and optimum improved U-value of windows. Table 2 shows the U-values of the building fabric elements in initial state and the thermal conductivities of new insulation materials as well. The different thicknesses of extra insulation materials and improved U-value of windows, between considered ranges (Table 2) were chosen. These ranges are based on the common practice and market availability of insulation materials. There are limitations with regard to considered measures from the practicality point of view. For instance, we may need to take the practical issues of applying 500 mm thick insulation on the exterior walls that require enough roof overhangs into account or to consider space availability for placing 500 mm thick insulation on the attic floor. Furthermore, we have not considered renovations needs that may reduce the investment cost of energy efficiency measures. In this study, our focus is to introduce and investigate a method to analyse the cost-optimum renovation of building fabric elements. Therefore, the larger range of insulation thicknesses could provide the opportunity to evaluate the methods validity. However, these issues might be considered in further studies. 2.4. Building simulation for final energy demand Final energy use reduction of the building was calculated by modelling the building energy balance before and after implementing the energy efficiency measures. We used the programme of VIP+ [23] to perform the calculations. VIP+ is a programme that simulates the energy balance of buildings. It analyses heat storage capacity in the building structure considering different thermo-physical properties, e.g. materials heat capacity, density and thermal conductivity. The model takes the building’s geometry, orientation, ventilation system, indoor and outdoor temperature into account and it built on finite difference method [23]. The simulation period is one complete year (365 days) from 1st of January to the end of December. It is a dynamic simulation and the results are hour by hour. Ambient temperature, relative humidity, wind velocity and the sun radiation, for the city of Växjö were taken from the defined climate data in VIP+ based on average hourly values between 1996 and 2005 [23]. The programme has been validated by International Energy Agency building energy simulation test (IEA-BESTEST), ASHRAE-BESTEST and CEN-15265 [23]. 2.5. Cost-optimum analysis In order to do the cost-optimum analysis of the efficiency measures on the building fabric elements, we need to estimate the required investment for implementing the efficiency measure and calculate the net present value (henceforth NPV) of the saved energy cost. We used the renovation work tariff in Sweden [26] to estimate the cost of implementing the energy efficiency measures
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Table 2 The initial state of building elements and considered energy efficiency measures for each individual element. Building fabric elements
Initial U-value (W/m2 K)
Energy efficiency measures
The range of considered thicknesses (mm) for extra insulation and U-values (W/m2 K) for new windows
Exterior walls of the facade
0.307
45 to 510
Basement exterior walls
0.626
Attic floor
0.248
Windows
2.9
Extra mineral wool panels (-value = 0.034 W/m K) Extra insulation of EPS panel (-value = 0.039 W/m K) Extra mineral wool (-value = 0.037 W/m K) Replacing the existing windows by the new windows with lower U-value
(investment cost). The cost of required materials, installation and construction work as well as the required man-hour for each work, the cost of excavation for basement walls insulation and required scaffolding for the works on the exterior walls of the facades were taken into account. This cost estimation reference book includes the average cost of the materials and construction work in the Swedish market. All costs, used in this study, refer to the year 2014 average exchange rate of D 1 = 8.9 SEK, based on the European Central Bank [27]. The economic benefit of reduced final energy use due to energy efficiency measures was calculated as the NPV of saved energy cost for different lifespans of the energy efficiency measures. We used DH supplier tariff [28] in the city of Växjö for the year 2013 in order to calculate the space heating cost of the building from end-user point of view. The following equation was used to calculate the NPV of saved energy cost. NPV =
n i=1
Fi (1 + r)ˆi
The DH energy price (€/kWh)
where F is the annual saved energy cost (reduction on energy bill for space heating, for the year i); r is the discount rate; n is the number of years (lifespan). We applied the annual energy price increase on the calculation by considering the variable energy price for every year, from the first year of calculation until the last year of considered lifespan. The real household energy price increase of DH between 1993 and 2011, including energy tax and VAT, is illustrated in Fig. 2 [29]. This trend shows about 2% energy price increase per year. We considered 40, 50 and 60 years lifespans for this calculation. The lifespan of the materials in building element are uncertain as it depends on the quality of materials, quality of the construction technology and the maintenance regime. The existing insulation materials and windows are 50 to 60 years old. We assume that the new available insulation materials and today’s common practice 0.09 0.08 0.07 0.06 0.05 0.04 1993
1996
1999
2002 The year
2005
2008
2011
Fig. 2. Real DH energy price for household in Sweden including energy tax and VAT between 1993 and 2011 (D /kW h).
70 to 300 50 to 500 1.2 to 0.6
of implementing them could provide approximately the same or a longer lifespan. The thermal conductivity of the building fabric elements was assumed to remain constant during the considered lifespans of improved elements after renovation. We used different discount rates, in order to calculate NPV of energy saving and its implication on the cost-optimum of the energy efficiency measures. The guideline for the European Commission Delegated Regulation No. 244/2012 [30] requires EU member states to perform sensitivity analysis on, at least, two discount rates for each calculation in which one rate shall be 4%. It suggests that a higher discount rate reflects a commercial approach, whereas a lower rate (typically between 2 and 4%) reflects the benefits that energy efficiency investment may offer to building occupants during building lifespan. The US Department of Energy [31] suggests 3% discount rate for performing life cycle cost analysis of potential energy conservation and renewable energy investments in existing and new buildings. Energy efficiency measures may reduce the potential risk of capital investment. Therefore, discount rate is usually calculated on risk-free basis for sustainable buildings [32]. Zalejska-Jonsson [33] calculated discount rate of 2%, assuming risk-neutral investor. Discount rate was calculated to be 5%, when she assumed a market risk of 3%. We analysed three scenarios with regard to discount rates and energy price increase. These are: (i) discount rate of 1% with annual energy price increase of 3%; (ii) discount rate of 3% with annual energy price increase of 2%; and (iii) discount rate of 5% with annual energy price increase of 1%. The first scenario provides, economically, the opportunity to implement more energy efficient measures. Consequently, final energy use for space heating can be reduced more than the cases where other two scenarios would be considered. This scenario is called Sustainability scenario in this study. In contrast, considering the third scenario does not, economically, provide motivation to implement energy efficient measures as much as the first and second scenarios. This scenario is called business-as-usual (BAU) in this study as the owner of the building may prefer not to consider any major renovation. We considered 3 and 2% of discount rate and annual energy price increase, respectively, for intermediate scenario. In order to find the optimum measure of each element, we calculated the difference between the marginal energy cost saving and the corresponding marginal investment for consecutive measures for the considered elements. In this method, the ultimate target is to maximise the function of f(x) = S(x) − I(x) ; where S(x) is the NPV of saved final energy cost and I(x) is the capital investment for implementing the measure. The maximum point of the function f(x) is where the derivative of this function is equal to zero i.e. ␦f(x) /␦x = (␦S(x) /␦x) − (␦I(x) /␦x) = 0. This point represents the optimum measure. The derivative of the function f(x) is described as “marginal cost difference” in this study. This calculation was done
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Table 3 Different thicknesses, improved U-value and investment cost of extra insulation on exterior walls. Building fabric elements
Energy efficiency measures
Thicknesses of extra insulation (mm)
Improved U-value (W/m2 K)
Final energy for space heating (kWh/m2 /year)
Exterior walls of the facade
Extra mineral wool panels with air gap and new cladding consideration
45
0.218
89.84
7.67
87,000
70
0.181
87.59
9.92
88,400
95
0.160
85.95
11.56
89,500
120
0.143
84.72
12.79
90,400
145
0.130
83.75
13.76
91,600
170
0.118
82.97
14.54
92,700
195
0.111
82.32
15.19
94,100
215
0,104
81.80
15.73
95,600
240
0.095
81.40
16.11
97,500
265
0.089
80.99
16.52
99,300
290
0.083
80.64
16.87
100,900
340
0.077
80.27
17.24
102,900
410
0.065
79.88
17.63
106,300
510
0.055
79.58
17.93
110,900
for a wide range of extra insulation thicknesses for opaque elements and different U-values for new windows.
Saved final energy (kWh/m2 /year)
Investment cost (D )
elements and the reduced U-value of new windows to the final energy demand for space heating are illustrated in Figs. 3 and 4, respectively.
3. Results
3.1. Reduced final energy demand for space heating The considered efficiency measures of each individual element were shown and described in Tables 3–6. The contribution of increased thickness of extra insulation on the considered
Final energy for space heating (kWh/m2/year)
100
Extra insulaon on ac floor
95 90
Extra insulaon on basement walls
85 80 75 70
0
100
200
300
Extra insulaon on exterior walls
Extra insulation thickness (mm)
3.2. Optimum measures of energy efficiency for considered elements The calculated marginal cost difference for extra insulation with different thicknesses is shown in Table 7. This Table represents the results of the intermediate scenario. The estimated cost of investment includes scaffolding. Similarly, the optimum measure calculation was performed for other considered elements. Figs. 5–8 illustrate the results of calculated marginal cost difference of measures, considering the three economic scenarios for 50 years lifespan. The implications of three economic scenarios on the optimum measure for the renovation of individual elements are shown in these figures. Figs. 9–12 illustrate the results of calculated marginal cost difference of measures, considering three lifespans of 40, 50 and
Final energy for space heating (kWh/m2/year)
Tables 3–5 show the improved U-values of exterior walls of the facade, basement wall and attic floor, respectively, due to implementing different thicknesses of extra insulation. Table 6 shows different U-values of new windows that were considered in the analysis. The required investment costs of the measures implementation are also shown in Tables 3–6. The final energy demand for space heating is 97.5 kWh/m2 /year before implementing any energy efficiency measure.
100 95 90 85 80 75 70
2.7
2.4
2.1
1.8
1.5
1.2
0.9
0.6
Improved windows U-value (W/m2K) Fig. 3. Contribution of extra insulation thickness of opaque elements to reduced final energy for space heating.
Fig. 4. Contribution of improved windows to reduced final energy for space heating.
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Table 4 Different thicknesses, improved U-value and investment cost of extra insulation on basement walls. Building fabric elements
Energy efficiency measures
Thicknesses of extra insulation (mm)
Improved U-value (W/m2 K)
Final energy for space heating (kWh/m2 /year)
Saved final energy (kWh/m2 /year)
Basement exterior walls
Extra insulation of EPS (cellplast) panels
70 100 170 240 270 300
0.295 0.240 0.168 0.129 0.177 0.108
93.50 92.81 91.89 91.39 91.23 91.11
4.01 4.70 5.62 6.12 6.28 6.40
Investment cost (D ) 5500 6000 8900 11,800 13,700 15,700
Table 5 Different thicknesses, improved U-value and investment cost of extra insulation on attic floor. Building fabric elements
Energy efficiency measures
Thicknesses of extra insulation (mm)
Improved U-value (W/m2 K)
Final energy for space heating (kWh/m2 /year)
Saved final energy (kWh/m2 /year)
Attic floor
Extra mineral wool
50 100 150 200 250 300 350 400 450 500
0.186 0.148 0.124 0.106 0.093 0.083 0.074 0.067 0.062 0.057
95.66 94.57 93.84 93.33 92.94 92.64 92.40 92.21 92.05 91.91
1.85 2.94 3.67 4.18 4.57 4.87 5.11 5.30 5.46 5.60
Saved final energy (kWh/m2 /year)
Investment cost (D ) 3700 4800 7900 9000 12,200 13,200 16,100 17,200 20,000 21,100
Table 6 Different U-value and investment cost of new windows. Building fabric elements
Energy efficiency measures
New windows U-value (W/m2 K)
Total solar transmittance (%)
Final energy for space heating (kWh/m2 /year)
Windows
Removing the existing windows and installing the new windows with lower U-value
1.4 1.2 1.1 0.9 0.8 0.7 0.6
62 60 56 52 51 49 47
79.37 76.35 75.99 74.14 72.92 71.99 71.07
60 years for sustainability scenario. The implications of lifespans of the measures after renovation on the optimum measure are shown in these figures. The marginal cost difference for different extra insulation thicknesses of attic floor (Figs. 7 and 11) appear to move, consecutively, up and down while the insulation thickness
18.14 21.16 21.52 23.37 24.59 25.52 26.44
Investment cost (D ) 90 000 104 000 113 000 137 000 154 000 175 000 203 000
increases. This is mainly due to the cost estimation method that is used in this study [26]. According to this tariff, the allocated working hours for each extra insulation changes, proportionally, with different thicknesses. The trend of marginal cost difference, though, follows an overall decrement.
Fig. 5. Marginal cost difference of exterior walls, for 50 years lifespan for the intermediate, BAU and sustainability scenarios
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Table 7 Marginal cost difference calculation for different thicknesses of extra insulation on exterior walls for the intermediate scenario (discount rate of 3% and energy price increase of 2%), assuming different lifespans. Thickness of extra insulation (mm)
Final energy for space heating (MWh/year)
NPV of final energy cost for space heating (kD ) 40 years lifespan
50 years lifespan
60 years lifespan
Marginal cost difference (kD )
45
133.0
296
354
406
–
–
–
70
129.6
289
345
396
5.56
6.92
8.14
95
127.2
284
339
389
3.94
4.92
5.80
120
125.4
280
335
384
2.92
3.67
4.34
145
124.0
277
331
380
1.80
2.38
2.91
170
122.8
275
328
377
1.33
1.80
2.23
195
121.8
273
326
374
0.61
1.00
1.35
215
121.0
271
324
372
−0.01
0.29
0.55
240
120.5
270
322
370
−0.55
−0.29
−0.05
265
119.9
269
321
368
−0.53
−0.28
−0.06
290
119.3
267
320
367
−0.49
−0.28
−0.08
340
118.8
266
318
365
−0.86
−0.63
−0.43
410
118.2
265
317
364
−2.31
−2.10
−1.91
510
117.8
264
316
363
−4.02
−3.90
−3.80
40 years lifespan
50 years lifespan
60 years lifespan
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Fig. 6. Marginal cost difference of basement walls, for 50 years lifespan for the intermediate, BAU and sustainability scenarios.
Fig. 7. Marginal cost difference of attic floor, for 50 years lifespan for the intermediate, BAU and sustainability scenarios.
Fig. 8. Marginal cost difference of windows, for 50 years lifespan for the intermediate, BAU and sustainability scenarios.
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Fig. 9. Marginal cost difference of exterior walls for different lifespans, considering sustainability scenarios.
Fig. 10. Marginal cost difference of basement walls for different lifespans, considering sustainability scenarios.
Fig. 11. Marginal cost difference of attic floor for different lifespans, considering sustainability scenarios.
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Fig. 12. Marginal cost difference of windows for different lifespans, considering sustainability scenarios.
Table 8 Optimum measures and their corresponding U-value of the elements for different lifespans and economic scenarios. Scenarios
BAU
Lifespan (years)
Intermediate
Sustainability
40
50
60
40
50
60
40
50
60
Extra insulation thickness (mm) U-value (W/m2 K)
185
185
185
210
240
260
340
390
420
Basement walls
Extra insulation thickness (mm) U-value (W/m2 K)
130
Attic floor
Extra insulation thickness (mm) U-value (W/m2 K)
200
Exterior walls
New windows U-value (W/m2 K)
0.114
0.203
0.114 130 0.203 200
0.114 130 0.203 200
0.106 170 0.168 300
BBR-12 criteria (W/m2 K)
0.097 0.091 0.077 0.068 0.064 0.18 190
210
240
260
270
300
300
400
500
500
Passive house criteria (W/m2 K)
0.10
No criteria for the basement 0.155 0.143 0.129 0.121 0.117 walls
0.106
0.106
0.106
0.083
0.083 0.083 0.067 0.057 0.057 0.13
0.08
1.2
1.2
1.2
1.2
1.2
0.9
3.3. The optimum measures of energy efficiency Table 8 shows the optimum insulation thickness of considered opaque elements and the optimum U-value of windows for the considered economic scenarios and lifespans. This was obtained from the calculated marginal cost difference for all measures of the considered elements. The requirements of Swedish building code (BBR-12) and the criteria of passive house [34–36] for the U-value of building fabric elements are also shown in Table 8 as well. 4. Discussion and conclusions In this study, we performed an hourly-based energy balance analysis of a building considering different energy efficiency measures on building fabric elements. The different thicknesses of extra insulation on opaque elements and improved windows with different U-values were analysed as energy efficiency measures, in order to find cost-optimum measure. The results of the analysis indicate that increasing the thickness of extra insulation and reducing the U-value of new windows do not reduce final energy use for space heating with a linear trend. The results suggest that the contribution of energy efficiency measures to the final energy use reduces by increasing the thickness of extra insulation and by reducing the U-value of new windows. The results show that 150 mm extra insulation on exterior walls, basement walls and attic floor reduce the final energy use by, respectively, 14, 6 and 4%. Whilst, doubling the thickness (300 mm) of extra insulation on the elements, by the same order, shows 17, 7 and 6% reduction in space heating demand. Similarly, the improvement of existing windows by replacing them with the windows of 1.2 W/m2 K U-value results in 22% reduction of
1.2
1.2
1.1
0.9
1.2
space heating demand. Whilst considering windows of 0.6 W/m2 K U-value reduces space heat demand by 27% of the initial state. In order to find the cost-optimum measure, the difference between marginal saving of energy cost and marginal cost of initial investment for implementing the considered measures was analysed. The marginal cost difference for the considered elements appears to have a significant reduction when the initial measure is implemented. This is due to the required cost of construction and installation work for the measures. This cost is included in the marginal cost difference calculation for the initial measure of considered elements. Whilst, it is eliminated when marginal cost difference is calculated for the following measures of each element. This is more notable in windows and basement walls improvement as the initial preparation, construction and installation work contributes, significantly, to the total cost of implementing measures. The considered range of extra insulation thicknesses for the opaque elements e.g. 510 mm thick insulation, may rise practical issues. This issue can be resolved by using new type of insulation materials that have very low thermal conductivity, such as vacuum insulation panels, to achieve same U-value as those in this study, while having less thickness. This consideration is to consider and analyse in the further studies. The implication of different lifespans and different economic scenarios on the optimum measure for the considered elements was also analysed. In the case of exterior walls, moving from BAU scenario to sustainability scenario, may offer an optimum insulation thickness with 84, 110 and 130% increase for 40, 50 and 60 years lifespan, respectively. The results indicate an average of 100% increase in optimum thickness for basement walls and attic floor. In the case of windows, the results suggest no change in the windows
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optimum U-value comparing BAU with sustainability scenarios for 40 years lifespan. Whilst, it indicates that the U-value of windows optimum measure can be as low as 0.9 W/m2 K for 60 years lifespan. The results show that measures lifespan implication on the optimum thickness and optimum U-value is not as significant as the ones of economic scenarios. The optimum thicknesses of opaque elements and U-values of windows do not change for different lifespans in the case of having BAU scenario. In sustainability scenario though, the optimum thicknesses of extra insulation appear to increase up to 25% when the lifespan increases from 40 to 60 years. The corresponding U-values of the optimum measures were calculated in order to be compared with the current Swedish building code of BBR-2012 requirements and passive house criteria [34–36]. The exterior walls optimum measures of all considered scenarios and lifespans have lower U-value than the building code requirement, i.e. 0.18 W/m2 K. However, the optimum measures of BAU scenario do not meet the passive house criteria i.e. 0.10 W/m2 K. All scenarios and lifespans of the attic floor optimum measures appear to meet the building code requirement, i.e. 0.13 W/m2 K. But, the BAU scenario of this measure could not meet the passive house criteria, i.e. 0.08 W/m2 K. In the case of windows improvement, all scenarios and lifespans meet the building code requirements, i.e. 1.2 W/m2 K. However, the sustainability scenario with 60 years lifespan is the only measure that meets the passive house criteria, i.e. 0.9 W/m2 K. The results of this study indicate that the cost-optimum level of energy efficiency measures are, significantly, influenced by the economic parameters that are used for the calculation of NPV of saved energy cost for space heating demand. Analysing the results indicates that considering the sustainable scenario may, strongly, influence the optimum thickness of extra insulation for opaque elements and the U-value of new windows, in comparison with the BAU scenario. Whilst, the contribution of three considered lifespans appear to be less effective to the optimum measures compare to the considered scenarios. However, the implication of considered scenarios and lifespans varies in different studied elements. The required investment for implementing the measures appears to be an important parameter on cost-optimum measure. This parameter is quite sensitive to the construction work and the required materials for buildings renovation. The cost of involved parameters in the building renovation varies during the life time of the building and also in different locations. Therefore, the results of this study are valid within the context of the assumptions and the case-study characteristics. Having stated that, the validity of the employed method for the purpose of approaching the cost-optimum measure for existing buildings renovation as well as for new buildings construction can be suggested. The member states of the European Union are required by “Guidelines accompanying Commission Delegated Regulation (EU) n. 244/2012” 2012/C 115/01 [30] to define reference building for the cost-optimal strategy of implementing the energy efficiency measures. The reference building is supposed to represent the typical and average building stock in a certain member state. Our casestudy building has almost same characteristics as many Swedish multi-story residential buildings from early 1970s. Therefore, our case-study building can be established as the reference building for the residential buildings with the same age and similar conclusions may be drawn for these buildings. However, the big difference in climate condition from north to south of Sweden makes it more complex to draw general conclusions of the results. Therefore, the cost efficiency analysis of, for example, the heating efficiency improvement of buildings may be further studied, considering each climatic zone of Sweden. In this study, the focus is on individual building fabric elements. Whilst, the different combinations of the elements may be
considered as renovation packages. Depending on the considered elements for each package, the cost-optimum measures might vary due to the total investment that may be reduced and also the interaction of the elements that influence the final energy for space heating demand. Another scenario is the case where the building is already in need of renovation for maintenance purpose. In such a case, the allocated investment for the energy conversation purpose is lower than the case where the building does not need renovation for maintenance purpose. These scenarios are to be analysed in the further studies. Acknowledgments The authors gratefully acknowledged Ronnebyhus® and the Municipality of the city of Växjö that financially and technically support our research. References [1] European Parliament, Directive 2010/31/EU of the European Parliament and the Council on the energy performance of buildings, Official Journal of the European Union (2010) 13–35. [2] S. Ecofys, Principles for Nearly Zero-Energy Buildings, Ecofys Germany GmbH, Danish Building Research Institute (SBi), 2011, pp. 99. [3] European Parliament, Directive 2002/91/EC of the European Parliament and the Council on the energy performance of buildings, Official Journal of the European Union (2002) 65–71. [4] European Parliament, Directive 2012/27/EU of the European Parliament and of the Council of 25 October 2012 on energy efficiency, Official Journal of the European Union 55 (2012) 97. [5] A. Dodoo, L. Gustavsson, R. Sathre, Life cycle primary energy implication of retrofitting a wood-framed apartment building to passive house standard, Resources, Conservation and Recycling 54 (12) (2010) 1152–1160. [6] C. Thormark, A low energy building in a life cycle—its embodied energy: energy need for operation and recycling potential, Building and Environment 37 (4) (2002) 429–435. [7] K. Adalberth, Energy use in four mulri-family houses during their life cycle, International journal of Low Energy and Sustainable Buildings 1 (1999) 1–20. [8] T. Ramesh, R. Prakash, K.K. Shukla, Life cycle energy analysis of buildings: an overview, Energy and Buildings 42 (10) (2010) 1592–1600. [9] I. Sartori, A.G. Hestnes, Energy use in the life cycle of conventional and lowenergy buildings: a review article, Energy and Buildings 39 (3) (2007) 249–257. [10] J.F. Karlsson, B. Moshfegh, A comprehensive investigation of a low-energy building in Sweden, Renewable Energy 32 (11) (2007) 1830–1841. [11] EEA, Consumption and the Environment, The European Environment Agency, Copenhagen, 2012 (update, 2012). [12] T. Hall, S. Viden, The Million Homes Programme: a review of the great Swedish planning project, Planning Perspectives 20 (2005) 27. [13] L. Itard, et al., Building Renovation and Modernisation in Europe: State of the Art Review, TUDelft, The Netherland, 2008. [14] L. Gustavsson, et al., Primary energy implications of end-use energy efficiency measures in district heated buildings, Energy and Buildings 43 (2011) 11. [15] J. Ouyang, et al., A methodology for energy-efficient renovation of existing residential buildings in China and case study, Energy and Buildings 43 (9) (2011) 2203–2210. [16] G. Dall’O’, A. Galante, G. Pasetti, A methodology for evaluating the potential energy savings of retrofitting residential building stocks, Sustainable Cities and Society 4 (0) (2012) 12–21. [17] Å. Wahlström, P. Filipsson, C. Heincke, Cost optimal energy efficiency in multifamily houses, CIT Energy Management, Göteborg, Sweden, 2013. [18] C. Petersdorff, et al., Cost-effective Climate Protection in the EU Building Stock, Ecofys, Cologne, Germany, 2005. [19] A.H. Hermelink, A. Mueler, Economics of deep renovation, in: Implication of a Set of Case Studies, Ecofys, Eurima, 2011. [20] K. Dol, M. Haffner, Housing Statistics in the European Union, OTB Research Institute for the Built Environment, Delft University of Technology, Delft, Netherland, 2010. [21] J. Jansson, T. Nilsson, Energieffektivisering av rekordårens flerbostadshus, in: Byggteknik LNU, Linnéuniversitetet, Institutionen för teknik, Växjö, Sweden, 2011, pp. 117. [22] Y. Zou, Classification of Buildings with Regard to Airtightness, Department of Civil and Environmental Engineering, Chalmers University of Technology, Götenborg, Sweden, 2010. [23] StruSoft AB, Structural Design Software, VIP-Energy, StruSoft AB, Sweden, 2012. [24] N.L. Truong, A. Dodoo, L. Gustavsson, Effects of heat and electricity saving measures in district-heated multistory residential buildings, Applied Energy 118 (0) (2014) 57–67. [25] H. Bülow-Hübe, Energy-efficient Window Systems, Effects on Energy Use and Daylight in Buildings, Department of Construction and Architecture, Lund University, Lund, 2001, pp. 248.
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Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Cost-optimum analysis of building fabric renovation in a Swedish multi-story residential building Farshid Bonakdar ∗ , Ambrose Dodoo, Leif Gustavsson Sustainable Built Environment, Faculty of Technology, Linnaeus University, Växjö SE-35195, Sweden
a r t i c l e
i n f o
Article history: Received 24 March 2014 Received in revised form 2 June 2014 Accepted 2 September 2014 Available online 10 September 2014 Keywords: Building renovation Building fabric Energy simulation Space heating Insulation Energy efficiency Cost-optimum renovation Sustainability Windows
a b s t r a c t In this study, we analysed the cost-optimum level of building fabric elements renovation in a multi-story residential building. We calculated final energy use for space heating of the building considering a wide range of energy efficiency measures, for exterior walls, basement walls, attic floor and windows. Different extra insulation thicknesses for considered opaque elements and different U-values for new windows were used as energy efficiency measures. We calculated difference between the marginal saving of energy cost for space heating and the investment cost of implemented energy efficiency measures, in order to find the cost-optimum measure for each element. The implications of building lifespans, annual energy price increase and discount rate on the optimum measure were also analysed. The results of the analysis indicate that the contribution of energy efficiency measures to the final energy use reduces, significantly, by increasing the thickness of extra insulation and by reducing the U-value of new windows. We considered three scenarios of business as usual (BAU), intermediate and sustainability, considering different discount rates and energy price increase. The results of this analysis suggest that the sustainability scenario may offer, approximately, 100% increase in the optimum thickness of extra insulation compared to BAU scenario. However, the implication of different lifespans of 40, 50 or 60 years, on the optimum measure appears to be either negligible or very small, depending on the chosen scenario. We also calculated the corresponding U-value of the optimum measures in order to compare them with the current Swedish building code requirements and passive house criteria. The results indicate that all optimum measures meet the Swedish building code. None of the optimum measures, however, meet the passive house criteria in BAU scenario. This study suggests that the employed method of building renovation cost-optimum analyses can be also applied on new building construction to find the cost-optimum design from energy conservation point of view. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Buildings account for 40% of total primary energy use [1] and 36% of CO2 emissions [2] in the European Union (EU). The EU directive on energy performance of building [3] requires member states to set minimum requirements for energy performance of buildings and building elements. That includes existing buildings that are subject to major renovation. This directive demands for considering cost-optimal balance between the investment and the saved energy cost during the lifespan of a building. According to EU Parliament Directive of 2012/27/EU [4], the existing building stock represents the single biggest potential sector for energy savings. It suggests that buildings are crucial to achieve the EU objective of reducing greenhouse gas emissions by 80–95% by 2050 compared
∗ Corresponding author. Tel.: +46 470 767595; fax: +46 470 768540. E-mail address: [email protected] (F. Bonakdar). http://dx.doi.org/10.1016/j.enbuild.2014.09.003 0378-7788/© 2014 Elsevier B.V. All rights reserved.
to 1990. The Swedish government targets 20 and 50% total final energy use reduction per heated building area by 2020 and 2050, respectively, using 1995 as the reference [5]. Directive 2012/27/ EU urges member states to establish a long-term strategy for mobilising investment in building renovation. This strategy should identify and then include cost-effective approaches to renovation, depending on the building type and climate zone. Energy is used during the whole life cycle of a building, i.e. construction, operation and end-of-life phases. Various researchers have studied final energy use in the entire life cycle of buildings (e.g. [6–10]) and show that the operation phase contributes, significantly, to the life cycle final energy use of buildings. Ramesh et al. [8] conducted a literature review study on life cycle final energy analysis of 73 residential and office buildings in northern and central Europe, Canada, tropical region of Asia and Australia. Their results suggested that the final operation energy use contributes to about 80 to 90% of life cycle energy use in residential buildings. Space heating of buildings is a substantial part of total operation energy.
F. Bonakdar et al. / Energy and Buildings 84 (2014) 662–673
According to the European Environment Agency [11] space heating accounts for about 68% of total operation energy use of buildings in European countries. Improved energy efficiency measures for space heating of existing buildings can provide substantial opportunity to reduce the primary energy use and CO2 emission. In Sweden, there is a significant potential to reduce primary energy use by decreasing the space heating demand of existing buildings. About 40,000 apartment buildings with almost 920,000 dwellings and about 480,000 single family houses were constructed between 1961 and 1975 in Sweden [12]. Most of these buildings are still in good condition from serviceability point of view and are projected to undergo major renovation within the next 20 years [13]. There are numerous energy efficiency measures that can reduce final operation energy use of buildings. The measures may include ventilation heat recovery systems, efficient hot water taps, efficient electrical appliances and improved thermal performance of building fabric elements. Various researchers have studied energy implication of different energy efficiency measures for building renovation. Gustavsson et al. [14] analysed a multi-story woodframe residential building constructed in 1995 in southern part of Sweden. They evaluated the effects of various energy efficiency measures on district heated (henceforth DH) buildings. They found that implementing more energy-efficient doors and windows, additional exterior walls insulation and additional roof insulation could reduce the final space heating by 35%. Dodoo et al. [5] analysed the effect of retrofitting a wood-frame building to a passive house standard. They considered improved water taps and building elements as well as ventilation heat recovery. They found that space heating could be reduced by 39% by improving the insulation on external walls and roof and changing doors and windows. The costeffectiveness of the building energy renovation, however, was not analysed in these studies. In another study, Ouyang et al. [15] analysed a 27-year old residential building in China. They considered six energy efficiency measures including external doors and windows improvement, adding insulation on the exterior walls and the roof, applying light colour on the envelope and applying curtains or blinds to exterior windows. They calculated final energy use and CO2 emission and analysed the economic implication of considered energy efficiency measures. They suggested that the considered measures are not cost effective unless the government provides subsidy and increase electricity price. The considered information of energy balance and economy analysis, however, has not been provided in details in this study. Dall’O’ et al. studied the energy saving potential of retrofitting the residential building stocks in five municipalities of Milan in Italy [16]. They considered windows replacement, facade extra insulation, roof extra insulation and air loss reduction of ventilation. They considered three economic scenarios: no incentive, tax deduction of 36% and tax deduction of 55%. The energy and economic analysis was performed to calculate the simple payback time for considered measures. Wahlström et al. [17] studied the implications of new building regulation on the major renovation of apartment buildings. They also analysed the profitability of energy-efficiency measures of existing multifamily houses. Their analysis involve the optimal life cycle costs of energy-efficiency measures in combination with four types of heating systems, considering 30 years calculation period and 3% discount rate. Ecofys report of cost-effectiveness climate protection [18] quantified the required investments and cost-effectiveness of energy efficient building envelope elements for cold, moderate and warm climate zones in Europe. In another report of Ecofys [19], the feasibility of deep renovation in European countries was studied. This report used case-studies for deep renovation programme in German low energy building stock. The results were then extrapolated to other European countries. The price level indices, mortgage
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rates, inflation rates, energy prices and heating degree days were taken into account in this study. They suggested that superficial renovations of buildings increase the risk of missing Europe long term climate target and that immediate deep renovation action is necessary for the European building stock. In this study, we analysed the optimum level of renovating the building fabric elements. We calculated the marginal difference between the saving of final energy cost for space heating due to energy efficiency measures and the cost of implementing those measures to renovate building fabric elements. Changing the existing windows to the ones with lower U-value, implementing extra insulation on exterior walls, basement walls and attic floor were considered, in order to find the optimum U-value for windows and thickness for extra insulation. The implication of different parameters such as discount rates, energy price increases and the lifespans of considered energy efficiency measures on cost-optimum measures were then analysed. 2. Methods 2.1. General approach We considered an existing building and studied the implication of energy renovation measures on final energy use for space heating. We analysed the contribution of thermal performance improvement of the building fabric elements to the final energy demand. The optimum choices of efficiency measures of individual elements were then analysed, from economic point of view. The overall approach of our study consists of the following parts: (1) Modelling the energy balance of the building to calculate final energy for space heating; (2) analysing the contribution of each energy efficiency measure to final energy savings; (3) performing the cost-optimisation analysis for each considered elements; (4) analysing the sensitivity of optimum measures to discount rates, energy price increase and lifespans of the considered elements. 2.2. Case-study building This study is based on a 50-year old multi-story residential building located in the city of Växjö in south of Sweden. It was constructed in 1964 as part of the Million Programme, running from 1960s to early 1970s in Sweden [12]. The existing residential building stock of Sweden appears to be relatively old but still in good condition from serviceability perspective. The housing statistics in the European Union [20] indicates that 19, 25 and 39% of the existing residential building in Sweden in 2008 are above 80, 70 and 60 years old, respectively. This report also indicates that 100% of existing buildings in the year 2008 in Sweden were equipped with central heating, hot running water and bath and shower. This may be used as a qualitative indication of building general condition for the existing residential buildings. This indication is, in average, 98, 97 and 83% in the UK, France and Poland, respectively [20]. The case-study building has eighteen apartments in three floors and six flats on ground floor. It is a concrete-frame building with brick cladding. Fig. 1 shows a view of the building. Total heated floor area of the building is 1430 m2 . Total ventilated volume is 3710 m3 which includes total volume of living space and the volume of common space, e.g. stair case where different temperatures are required. The required information of the building for the analysis was extracted from existing drawings provided by the building
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Table 1 Total area (m2 ) of the building fabric elements. Building elements on each facade
Exterior walls of facade
Basement walls, above ground level
Basement walls, below ground level
Windows and the glass share of doors
Attic floor
South facade North facade West facade East facade
160 220 107 107
38 22 12 18
110
127 55 7.5 6.5
400
Fig. 1. South-west view of the case-study building.
owner. This includes the details of geometry and thermal characteristics of building fabric elements. The areas of building fabric elements are shown in Table 1. Building attic floor consists of a concrete slab with the thickness of 200 mm and mineral wool insulation of 150 mm in its initial state. The existing windows of the building have the U-value of 2.9 W/m2 K [21]. The details of exterior walls are different in different sides of the building. The eastern and western exterior walls consist of 140 mm concrete, 100 mm mineral wool with thermal conductivity of 0.04 W/m K and 120 mm brick cladding. The northern and southern exterior walls consist of 70 mm lightweight concrete, 100 mm mineral wool with thermal conductivity of 0.04 W/m K and 120 mm brick cladding. The basement exterior walls consist of concrete with mineral wool insulation on the internal side of the walls [21]. The connections between exterior walls and floor slabs as well as the corners of the building, where two walls are connected together, are recognised to be the main sections for thermal bridges and considered in our building energy simulation. The airtightness of the building is about 0.8 l/m2 /s [22]. The ventilation system of the building is an exhaust air fan that is, constantly, working every day during the entire year. We assumed that it has the pressure of 200 Pa and efficiency of 50% with the flow rate of 0.35 l/m2 /s [23]. The case-study building is heated by district heating system in the city of Växjö where more than 95% of the produced district heating is based on biomass-based. production unit with the overall conversion efficiency of about 107% [24]. 2.3. Energy efficiency measures Different U-values for new windows and different thicknesses of extra insulation materials for exterior and basement walls and attic floor were considered for the analysis. We considered mineral wool panels, cellplast panels and mineral wool blanket as additional insulation on exterior walls of the facade, external side of the basement walls and attic floor, respectively. The existing windows were assumed to be replaced with improved triple glazed windows with lower U-values. The U-value reduction of windows may reduce solar transmittance as well [25]. Total and direct solar transmittances of new windows were taken into account in the building energy balance simulation. We assumed that indoor temperature of living area is influenced by windows improvement. The indoor temperature of living area was considered to reduce from 22 ◦ C to
21 ◦ C after implementing efficient windows assuming that the user thermal comfort could be maintained at lower indoor temperature due to the increased inside surface temperature of the new windows. Different thicknesses of considered insulation materials and different improved U-value of windows and the investment cost of implementing all considered measures were calculated to find the optimum thickness of extra insulation and optimum improved U-value of windows. Table 2 shows the U-values of the building fabric elements in initial state and the thermal conductivities of new insulation materials as well. The different thicknesses of extra insulation materials and improved U-value of windows, between considered ranges (Table 2) were chosen. These ranges are based on the common practice and market availability of insulation materials. There are limitations with regard to considered measures from the practicality point of view. For instance, we may need to take the practical issues of applying 500 mm thick insulation on the exterior walls that require enough roof overhangs into account or to consider space availability for placing 500 mm thick insulation on the attic floor. Furthermore, we have not considered renovations needs that may reduce the investment cost of energy efficiency measures. In this study, our focus is to introduce and investigate a method to analyse the cost-optimum renovation of building fabric elements. Therefore, the larger range of insulation thicknesses could provide the opportunity to evaluate the methods validity. However, these issues might be considered in further studies. 2.4. Building simulation for final energy demand Final energy use reduction of the building was calculated by modelling the building energy balance before and after implementing the energy efficiency measures. We used the programme of VIP+ [23] to perform the calculations. VIP+ is a programme that simulates the energy balance of buildings. It analyses heat storage capacity in the building structure considering different thermo-physical properties, e.g. materials heat capacity, density and thermal conductivity. The model takes the building’s geometry, orientation, ventilation system, indoor and outdoor temperature into account and it built on finite difference method [23]. The simulation period is one complete year (365 days) from 1st of January to the end of December. It is a dynamic simulation and the results are hour by hour. Ambient temperature, relative humidity, wind velocity and the sun radiation, for the city of Växjö were taken from the defined climate data in VIP+ based on average hourly values between 1996 and 2005 [23]. The programme has been validated by International Energy Agency building energy simulation test (IEA-BESTEST), ASHRAE-BESTEST and CEN-15265 [23]. 2.5. Cost-optimum analysis In order to do the cost-optimum analysis of the efficiency measures on the building fabric elements, we need to estimate the required investment for implementing the efficiency measure and calculate the net present value (henceforth NPV) of the saved energy cost. We used the renovation work tariff in Sweden [26] to estimate the cost of implementing the energy efficiency measures
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Table 2 The initial state of building elements and considered energy efficiency measures for each individual element. Building fabric elements
Initial U-value (W/m2 K)
Energy efficiency measures
The range of considered thicknesses (mm) for extra insulation and U-values (W/m2 K) for new windows
Exterior walls of the facade
0.307
45 to 510
Basement exterior walls
0.626
Attic floor
0.248
Windows
2.9
Extra mineral wool panels (-value = 0.034 W/m K) Extra insulation of EPS panel (-value = 0.039 W/m K) Extra mineral wool (-value = 0.037 W/m K) Replacing the existing windows by the new windows with lower U-value
(investment cost). The cost of required materials, installation and construction work as well as the required man-hour for each work, the cost of excavation for basement walls insulation and required scaffolding for the works on the exterior walls of the facades were taken into account. This cost estimation reference book includes the average cost of the materials and construction work in the Swedish market. All costs, used in this study, refer to the year 2014 average exchange rate of D 1 = 8.9 SEK, based on the European Central Bank [27]. The economic benefit of reduced final energy use due to energy efficiency measures was calculated as the NPV of saved energy cost for different lifespans of the energy efficiency measures. We used DH supplier tariff [28] in the city of Växjö for the year 2013 in order to calculate the space heating cost of the building from end-user point of view. The following equation was used to calculate the NPV of saved energy cost. NPV =
n i=1
Fi (1 + r)ˆi
The DH energy price (€/kWh)
where F is the annual saved energy cost (reduction on energy bill for space heating, for the year i); r is the discount rate; n is the number of years (lifespan). We applied the annual energy price increase on the calculation by considering the variable energy price for every year, from the first year of calculation until the last year of considered lifespan. The real household energy price increase of DH between 1993 and 2011, including energy tax and VAT, is illustrated in Fig. 2 [29]. This trend shows about 2% energy price increase per year. We considered 40, 50 and 60 years lifespans for this calculation. The lifespan of the materials in building element are uncertain as it depends on the quality of materials, quality of the construction technology and the maintenance regime. The existing insulation materials and windows are 50 to 60 years old. We assume that the new available insulation materials and today’s common practice 0.09 0.08 0.07 0.06 0.05 0.04 1993
1996
1999
2002 The year
2005
2008
2011
Fig. 2. Real DH energy price for household in Sweden including energy tax and VAT between 1993 and 2011 (D /kW h).
70 to 300 50 to 500 1.2 to 0.6
of implementing them could provide approximately the same or a longer lifespan. The thermal conductivity of the building fabric elements was assumed to remain constant during the considered lifespans of improved elements after renovation. We used different discount rates, in order to calculate NPV of energy saving and its implication on the cost-optimum of the energy efficiency measures. The guideline for the European Commission Delegated Regulation No. 244/2012 [30] requires EU member states to perform sensitivity analysis on, at least, two discount rates for each calculation in which one rate shall be 4%. It suggests that a higher discount rate reflects a commercial approach, whereas a lower rate (typically between 2 and 4%) reflects the benefits that energy efficiency investment may offer to building occupants during building lifespan. The US Department of Energy [31] suggests 3% discount rate for performing life cycle cost analysis of potential energy conservation and renewable energy investments in existing and new buildings. Energy efficiency measures may reduce the potential risk of capital investment. Therefore, discount rate is usually calculated on risk-free basis for sustainable buildings [32]. Zalejska-Jonsson [33] calculated discount rate of 2%, assuming risk-neutral investor. Discount rate was calculated to be 5%, when she assumed a market risk of 3%. We analysed three scenarios with regard to discount rates and energy price increase. These are: (i) discount rate of 1% with annual energy price increase of 3%; (ii) discount rate of 3% with annual energy price increase of 2%; and (iii) discount rate of 5% with annual energy price increase of 1%. The first scenario provides, economically, the opportunity to implement more energy efficient measures. Consequently, final energy use for space heating can be reduced more than the cases where other two scenarios would be considered. This scenario is called Sustainability scenario in this study. In contrast, considering the third scenario does not, economically, provide motivation to implement energy efficient measures as much as the first and second scenarios. This scenario is called business-as-usual (BAU) in this study as the owner of the building may prefer not to consider any major renovation. We considered 3 and 2% of discount rate and annual energy price increase, respectively, for intermediate scenario. In order to find the optimum measure of each element, we calculated the difference between the marginal energy cost saving and the corresponding marginal investment for consecutive measures for the considered elements. In this method, the ultimate target is to maximise the function of f(x) = S(x) − I(x) ; where S(x) is the NPV of saved final energy cost and I(x) is the capital investment for implementing the measure. The maximum point of the function f(x) is where the derivative of this function is equal to zero i.e. ␦f(x) /␦x = (␦S(x) /␦x) − (␦I(x) /␦x) = 0. This point represents the optimum measure. The derivative of the function f(x) is described as “marginal cost difference” in this study. This calculation was done
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Table 3 Different thicknesses, improved U-value and investment cost of extra insulation on exterior walls. Building fabric elements
Energy efficiency measures
Thicknesses of extra insulation (mm)
Improved U-value (W/m2 K)
Final energy for space heating (kWh/m2 /year)
Exterior walls of the facade
Extra mineral wool panels with air gap and new cladding consideration
45
0.218
89.84
7.67
87,000
70
0.181
87.59
9.92
88,400
95
0.160
85.95
11.56
89,500
120
0.143
84.72
12.79
90,400
145
0.130
83.75
13.76
91,600
170
0.118
82.97
14.54
92,700
195
0.111
82.32
15.19
94,100
215
0,104
81.80
15.73
95,600
240
0.095
81.40
16.11
97,500
265
0.089
80.99
16.52
99,300
290
0.083
80.64
16.87
100,900
340
0.077
80.27
17.24
102,900
410
0.065
79.88
17.63
106,300
510
0.055
79.58
17.93
110,900
for a wide range of extra insulation thicknesses for opaque elements and different U-values for new windows.
Saved final energy (kWh/m2 /year)
Investment cost (D )
elements and the reduced U-value of new windows to the final energy demand for space heating are illustrated in Figs. 3 and 4, respectively.
3. Results
3.1. Reduced final energy demand for space heating The considered efficiency measures of each individual element were shown and described in Tables 3–6. The contribution of increased thickness of extra insulation on the considered
Final energy for space heating (kWh/m2/year)
100
Extra insulaon on ac floor
95 90
Extra insulaon on basement walls
85 80 75 70
0
100
200
300
Extra insulaon on exterior walls
Extra insulation thickness (mm)
3.2. Optimum measures of energy efficiency for considered elements The calculated marginal cost difference for extra insulation with different thicknesses is shown in Table 7. This Table represents the results of the intermediate scenario. The estimated cost of investment includes scaffolding. Similarly, the optimum measure calculation was performed for other considered elements. Figs. 5–8 illustrate the results of calculated marginal cost difference of measures, considering the three economic scenarios for 50 years lifespan. The implications of three economic scenarios on the optimum measure for the renovation of individual elements are shown in these figures. Figs. 9–12 illustrate the results of calculated marginal cost difference of measures, considering three lifespans of 40, 50 and
Final energy for space heating (kWh/m2/year)
Tables 3–5 show the improved U-values of exterior walls of the facade, basement wall and attic floor, respectively, due to implementing different thicknesses of extra insulation. Table 6 shows different U-values of new windows that were considered in the analysis. The required investment costs of the measures implementation are also shown in Tables 3–6. The final energy demand for space heating is 97.5 kWh/m2 /year before implementing any energy efficiency measure.
100 95 90 85 80 75 70
2.7
2.4
2.1
1.8
1.5
1.2
0.9
0.6
Improved windows U-value (W/m2K) Fig. 3. Contribution of extra insulation thickness of opaque elements to reduced final energy for space heating.
Fig. 4. Contribution of improved windows to reduced final energy for space heating.
F. Bonakdar et al. / Energy and Buildings 84 (2014) 662–673
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Table 4 Different thicknesses, improved U-value and investment cost of extra insulation on basement walls. Building fabric elements
Energy efficiency measures
Thicknesses of extra insulation (mm)
Improved U-value (W/m2 K)
Final energy for space heating (kWh/m2 /year)
Saved final energy (kWh/m2 /year)
Basement exterior walls
Extra insulation of EPS (cellplast) panels
70 100 170 240 270 300
0.295 0.240 0.168 0.129 0.177 0.108
93.50 92.81 91.89 91.39 91.23 91.11
4.01 4.70 5.62 6.12 6.28 6.40
Investment cost (D ) 5500 6000 8900 11,800 13,700 15,700
Table 5 Different thicknesses, improved U-value and investment cost of extra insulation on attic floor. Building fabric elements
Energy efficiency measures
Thicknesses of extra insulation (mm)
Improved U-value (W/m2 K)
Final energy for space heating (kWh/m2 /year)
Saved final energy (kWh/m2 /year)
Attic floor
Extra mineral wool
50 100 150 200 250 300 350 400 450 500
0.186 0.148 0.124 0.106 0.093 0.083 0.074 0.067 0.062 0.057
95.66 94.57 93.84 93.33 92.94 92.64 92.40 92.21 92.05 91.91
1.85 2.94 3.67 4.18 4.57 4.87 5.11 5.30 5.46 5.60
Saved final energy (kWh/m2 /year)
Investment cost (D ) 3700 4800 7900 9000 12,200 13,200 16,100 17,200 20,000 21,100
Table 6 Different U-value and investment cost of new windows. Building fabric elements
Energy efficiency measures
New windows U-value (W/m2 K)
Total solar transmittance (%)
Final energy for space heating (kWh/m2 /year)
Windows
Removing the existing windows and installing the new windows with lower U-value
1.4 1.2 1.1 0.9 0.8 0.7 0.6
62 60 56 52 51 49 47
79.37 76.35 75.99 74.14 72.92 71.99 71.07
60 years for sustainability scenario. The implications of lifespans of the measures after renovation on the optimum measure are shown in these figures. The marginal cost difference for different extra insulation thicknesses of attic floor (Figs. 7 and 11) appear to move, consecutively, up and down while the insulation thickness
18.14 21.16 21.52 23.37 24.59 25.52 26.44
Investment cost (D ) 90 000 104 000 113 000 137 000 154 000 175 000 203 000
increases. This is mainly due to the cost estimation method that is used in this study [26]. According to this tariff, the allocated working hours for each extra insulation changes, proportionally, with different thicknesses. The trend of marginal cost difference, though, follows an overall decrement.
Fig. 5. Marginal cost difference of exterior walls, for 50 years lifespan for the intermediate, BAU and sustainability scenarios
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Table 7 Marginal cost difference calculation for different thicknesses of extra insulation on exterior walls for the intermediate scenario (discount rate of 3% and energy price increase of 2%), assuming different lifespans. Thickness of extra insulation (mm)
Final energy for space heating (MWh/year)
NPV of final energy cost for space heating (kD ) 40 years lifespan
50 years lifespan
60 years lifespan
Marginal cost difference (kD )
45
133.0
296
354
406
–
–
–
70
129.6
289
345
396
5.56
6.92
8.14
95
127.2
284
339
389
3.94
4.92
5.80
120
125.4
280
335
384
2.92
3.67
4.34
145
124.0
277
331
380
1.80
2.38
2.91
170
122.8
275
328
377
1.33
1.80
2.23
195
121.8
273
326
374
0.61
1.00
1.35
215
121.0
271
324
372
−0.01
0.29
0.55
240
120.5
270
322
370
−0.55
−0.29
−0.05
265
119.9
269
321
368
−0.53
−0.28
−0.06
290
119.3
267
320
367
−0.49
−0.28
−0.08
340
118.8
266
318
365
−0.86
−0.63
−0.43
410
118.2
265
317
364
−2.31
−2.10
−1.91
510
117.8
264
316
363
−4.02
−3.90
−3.80
40 years lifespan
50 years lifespan
60 years lifespan
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F. Bonakdar et al. / Energy and Buildings 84 (2014) 662–673
Fig. 6. Marginal cost difference of basement walls, for 50 years lifespan for the intermediate, BAU and sustainability scenarios.
Fig. 7. Marginal cost difference of attic floor, for 50 years lifespan for the intermediate, BAU and sustainability scenarios.
Fig. 8. Marginal cost difference of windows, for 50 years lifespan for the intermediate, BAU and sustainability scenarios.
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Fig. 9. Marginal cost difference of exterior walls for different lifespans, considering sustainability scenarios.
Fig. 10. Marginal cost difference of basement walls for different lifespans, considering sustainability scenarios.
Fig. 11. Marginal cost difference of attic floor for different lifespans, considering sustainability scenarios.
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Fig. 12. Marginal cost difference of windows for different lifespans, considering sustainability scenarios.
Table 8 Optimum measures and their corresponding U-value of the elements for different lifespans and economic scenarios. Scenarios
BAU
Lifespan (years)
Intermediate
Sustainability
40
50
60
40
50
60
40
50
60
Extra insulation thickness (mm) U-value (W/m2 K)
185
185
185
210
240
260
340
390
420
Basement walls
Extra insulation thickness (mm) U-value (W/m2 K)
130
Attic floor
Extra insulation thickness (mm) U-value (W/m2 K)
200
Exterior walls
New windows U-value (W/m2 K)
0.114
0.203
0.114 130 0.203 200
0.114 130 0.203 200
0.106 170 0.168 300
BBR-12 criteria (W/m2 K)
0.097 0.091 0.077 0.068 0.064 0.18 190
210
240
260
270
300
300
400
500
500
Passive house criteria (W/m2 K)
0.10
No criteria for the basement 0.155 0.143 0.129 0.121 0.117 walls
0.106
0.106
0.106
0.083
0.083 0.083 0.067 0.057 0.057 0.13
0.08
1.2
1.2
1.2
1.2
1.2
0.9
3.3. The optimum measures of energy efficiency Table 8 shows the optimum insulation thickness of considered opaque elements and the optimum U-value of windows for the considered economic scenarios and lifespans. This was obtained from the calculated marginal cost difference for all measures of the considered elements. The requirements of Swedish building code (BBR-12) and the criteria of passive house [34–36] for the U-value of building fabric elements are also shown in Table 8 as well. 4. Discussion and conclusions In this study, we performed an hourly-based energy balance analysis of a building considering different energy efficiency measures on building fabric elements. The different thicknesses of extra insulation on opaque elements and improved windows with different U-values were analysed as energy efficiency measures, in order to find cost-optimum measure. The results of the analysis indicate that increasing the thickness of extra insulation and reducing the U-value of new windows do not reduce final energy use for space heating with a linear trend. The results suggest that the contribution of energy efficiency measures to the final energy use reduces by increasing the thickness of extra insulation and by reducing the U-value of new windows. The results show that 150 mm extra insulation on exterior walls, basement walls and attic floor reduce the final energy use by, respectively, 14, 6 and 4%. Whilst, doubling the thickness (300 mm) of extra insulation on the elements, by the same order, shows 17, 7 and 6% reduction in space heating demand. Similarly, the improvement of existing windows by replacing them with the windows of 1.2 W/m2 K U-value results in 22% reduction of
1.2
1.2
1.1
0.9
1.2
space heating demand. Whilst considering windows of 0.6 W/m2 K U-value reduces space heat demand by 27% of the initial state. In order to find the cost-optimum measure, the difference between marginal saving of energy cost and marginal cost of initial investment for implementing the considered measures was analysed. The marginal cost difference for the considered elements appears to have a significant reduction when the initial measure is implemented. This is due to the required cost of construction and installation work for the measures. This cost is included in the marginal cost difference calculation for the initial measure of considered elements. Whilst, it is eliminated when marginal cost difference is calculated for the following measures of each element. This is more notable in windows and basement walls improvement as the initial preparation, construction and installation work contributes, significantly, to the total cost of implementing measures. The considered range of extra insulation thicknesses for the opaque elements e.g. 510 mm thick insulation, may rise practical issues. This issue can be resolved by using new type of insulation materials that have very low thermal conductivity, such as vacuum insulation panels, to achieve same U-value as those in this study, while having less thickness. This consideration is to consider and analyse in the further studies. The implication of different lifespans and different economic scenarios on the optimum measure for the considered elements was also analysed. In the case of exterior walls, moving from BAU scenario to sustainability scenario, may offer an optimum insulation thickness with 84, 110 and 130% increase for 40, 50 and 60 years lifespan, respectively. The results indicate an average of 100% increase in optimum thickness for basement walls and attic floor. In the case of windows, the results suggest no change in the windows
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optimum U-value comparing BAU with sustainability scenarios for 40 years lifespan. Whilst, it indicates that the U-value of windows optimum measure can be as low as 0.9 W/m2 K for 60 years lifespan. The results show that measures lifespan implication on the optimum thickness and optimum U-value is not as significant as the ones of economic scenarios. The optimum thicknesses of opaque elements and U-values of windows do not change for different lifespans in the case of having BAU scenario. In sustainability scenario though, the optimum thicknesses of extra insulation appear to increase up to 25% when the lifespan increases from 40 to 60 years. The corresponding U-values of the optimum measures were calculated in order to be compared with the current Swedish building code of BBR-2012 requirements and passive house criteria [34–36]. The exterior walls optimum measures of all considered scenarios and lifespans have lower U-value than the building code requirement, i.e. 0.18 W/m2 K. However, the optimum measures of BAU scenario do not meet the passive house criteria i.e. 0.10 W/m2 K. All scenarios and lifespans of the attic floor optimum measures appear to meet the building code requirement, i.e. 0.13 W/m2 K. But, the BAU scenario of this measure could not meet the passive house criteria, i.e. 0.08 W/m2 K. In the case of windows improvement, all scenarios and lifespans meet the building code requirements, i.e. 1.2 W/m2 K. However, the sustainability scenario with 60 years lifespan is the only measure that meets the passive house criteria, i.e. 0.9 W/m2 K. The results of this study indicate that the cost-optimum level of energy efficiency measures are, significantly, influenced by the economic parameters that are used for the calculation of NPV of saved energy cost for space heating demand. Analysing the results indicates that considering the sustainable scenario may, strongly, influence the optimum thickness of extra insulation for opaque elements and the U-value of new windows, in comparison with the BAU scenario. Whilst, the contribution of three considered lifespans appear to be less effective to the optimum measures compare to the considered scenarios. However, the implication of considered scenarios and lifespans varies in different studied elements. The required investment for implementing the measures appears to be an important parameter on cost-optimum measure. This parameter is quite sensitive to the construction work and the required materials for buildings renovation. The cost of involved parameters in the building renovation varies during the life time of the building and also in different locations. Therefore, the results of this study are valid within the context of the assumptions and the case-study characteristics. Having stated that, the validity of the employed method for the purpose of approaching the cost-optimum measure for existing buildings renovation as well as for new buildings construction can be suggested. The member states of the European Union are required by “Guidelines accompanying Commission Delegated Regulation (EU) n. 244/2012” 2012/C 115/01 [30] to define reference building for the cost-optimal strategy of implementing the energy efficiency measures. The reference building is supposed to represent the typical and average building stock in a certain member state. Our casestudy building has almost same characteristics as many Swedish multi-story residential buildings from early 1970s. Therefore, our case-study building can be established as the reference building for the residential buildings with the same age and similar conclusions may be drawn for these buildings. However, the big difference in climate condition from north to south of Sweden makes it more complex to draw general conclusions of the results. Therefore, the cost efficiency analysis of, for example, the heating efficiency improvement of buildings may be further studied, considering each climatic zone of Sweden. In this study, the focus is on individual building fabric elements. Whilst, the different combinations of the elements may be
considered as renovation packages. Depending on the considered elements for each package, the cost-optimum measures might vary due to the total investment that may be reduced and also the interaction of the elements that influence the final energy for space heating demand. Another scenario is the case where the building is already in need of renovation for maintenance purpose. In such a case, the allocated investment for the energy conversation purpose is lower than the case where the building does not need renovation for maintenance purpose. These scenarios are to be analysed in the further studies. Acknowledgments The authors gratefully acknowledged Ronnebyhus® and the Municipality of the city of Växjö that financially and technically support our research. References [1] European Parliament, Directive 2010/31/EU of the European Parliament and the Council on the energy performance of buildings, Official Journal of the European Union (2010) 13–35. [2] S. Ecofys, Principles for Nearly Zero-Energy Buildings, Ecofys Germany GmbH, Danish Building Research Institute (SBi), 2011, pp. 99. [3] European Parliament, Directive 2002/91/EC of the European Parliament and the Council on the energy performance of buildings, Official Journal of the European Union (2002) 65–71. [4] European Parliament, Directive 2012/27/EU of the European Parliament and of the Council of 25 October 2012 on energy efficiency, Official Journal of the European Union 55 (2012) 97. [5] A. Dodoo, L. Gustavsson, R. Sathre, Life cycle primary energy implication of retrofitting a wood-framed apartment building to passive house standard, Resources, Conservation and Recycling 54 (12) (2010) 1152–1160. [6] C. Thormark, A low energy building in a life cycle—its embodied energy: energy need for operation and recycling potential, Building and Environment 37 (4) (2002) 429–435. [7] K. Adalberth, Energy use in four mulri-family houses during their life cycle, International journal of Low Energy and Sustainable Buildings 1 (1999) 1–20. [8] T. Ramesh, R. Prakash, K.K. Shukla, Life cycle energy analysis of buildings: an overview, Energy and Buildings 42 (10) (2010) 1592–1600. [9] I. Sartori, A.G. Hestnes, Energy use in the life cycle of conventional and lowenergy buildings: a review article, Energy and Buildings 39 (3) (2007) 249–257. [10] J.F. Karlsson, B. Moshfegh, A comprehensive investigation of a low-energy building in Sweden, Renewable Energy 32 (11) (2007) 1830–1841. [11] EEA, Consumption and the Environment, The European Environment Agency, Copenhagen, 2012 (update, 2012). [12] T. Hall, S. Viden, The Million Homes Programme: a review of the great Swedish planning project, Planning Perspectives 20 (2005) 27. [13] L. Itard, et al., Building Renovation and Modernisation in Europe: State of the Art Review, TUDelft, The Netherland, 2008. [14] L. Gustavsson, et al., Primary energy implications of end-use energy efficiency measures in district heated buildings, Energy and Buildings 43 (2011) 11. [15] J. Ouyang, et al., A methodology for energy-efficient renovation of existing residential buildings in China and case study, Energy and Buildings 43 (9) (2011) 2203–2210. [16] G. Dall’O’, A. Galante, G. Pasetti, A methodology for evaluating the potential energy savings of retrofitting residential building stocks, Sustainable Cities and Society 4 (0) (2012) 12–21. [17] Å. Wahlström, P. Filipsson, C. Heincke, Cost optimal energy efficiency in multifamily houses, CIT Energy Management, Göteborg, Sweden, 2013. [18] C. Petersdorff, et al., Cost-effective Climate Protection in the EU Building Stock, Ecofys, Cologne, Germany, 2005. [19] A.H. Hermelink, A. Mueler, Economics of deep renovation, in: Implication of a Set of Case Studies, Ecofys, Eurima, 2011. [20] K. Dol, M. Haffner, Housing Statistics in the European Union, OTB Research Institute for the Built Environment, Delft University of Technology, Delft, Netherland, 2010. [21] J. Jansson, T. Nilsson, Energieffektivisering av rekordårens flerbostadshus, in: Byggteknik LNU, Linnéuniversitetet, Institutionen för teknik, Växjö, Sweden, 2011, pp. 117. [22] Y. Zou, Classification of Buildings with Regard to Airtightness, Department of Civil and Environmental Engineering, Chalmers University of Technology, Götenborg, Sweden, 2010. [23] StruSoft AB, Structural Design Software, VIP-Energy, StruSoft AB, Sweden, 2012. [24] N.L. Truong, A. Dodoo, L. Gustavsson, Effects of heat and electricity saving measures in district-heated multistory residential buildings, Applied Energy 118 (0) (2014) 57–67. [25] H. Bülow-Hübe, Energy-efficient Window Systems, Effects on Energy Use and Daylight in Buildings, Department of Construction and Architecture, Lund University, Lund, 2001, pp. 248.
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