Cost curves of energy efficiency investments in buildings – Methodologies and a case study of Lithuania

Energy Policy 115 (2018) 148–157

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Cost curves of energy efficiency investments in buildings – Methodologies and a case study of Lithuania

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Agne Toleikyte , Lukas Kranzl, Andreas Müller Energy Economics Group, Institute of Energy Systems and Electrical Drives Technische Universität Wien, Vienna, Austria

A R T I C L E I N F O

A B S T R A C T

Keywords: Building sector Energy demand Energy efficiency measures Cost curves Cost-effectiveness

This paper aims to calculate potential energy savings for space heating and hot water by 2030 for the Lithuanian building sector by implementing energy efficiency solutions. Policy recommendations are derived by showing which buildings and energy efficiency measures should be addressed in order to determine the full energy saving potential in the most effective way. Different cost curves for energy savings potential are applied, and these curves show the investor perspective and overall economic perspective. Final energy demand can be reduced by 56% by year 2030 if the least-cost energy efficiency solutions for each building type are selected. Energy performance class A implementation for the apartment buildings built before 1990 and supplied by district heating is the most cost-effective measure. If we consider the overall economic perspective, energy performance class A++ (deep renovation) for the same buildings is the most cost-effective measure. The results call for (I) policies to support building renovation that address buildings with low energy performance instead of subsidising energy prices and (II) policies promoting deep renovation (A+, A++) in order to avoid lock-in effects and ensure the transition of the Lithuanian building stock towards nearly zero-energy buildings (nZEBs).

1. Introduction The EU has proposed a 40% goal for the reduction of GHG emissions by 2030, together with targets of 27% for both renewable energy and improved energy efficiency. In the Clean Energy for All Europeans package, the European Parliament and Council proposed a binding 30% energy efficiency target for 2030, up from the current target of at least 27%. This aim is particularly addressing the building sector (Arias Cañete et al., 2017). The building sector within the European Union accounts for about 40% of final energy consumption (European Commission, 2017). European households in EU-28 were responsible for 26% of the final energy consumption in 2012 (Eurostat, 2014). Increasing the renovation rate, renovation quality and effectiveness of building renovation are the key activities to achieve the targets (Arias Cañete et al., 2017). However, the building sector is very complex, and cost-effective investments, especially effective public investments, require detailed analyses of the building sector. Such analyses must consider a building's thermal characteristics, climate conditions and supplied energy fuel prices. The Lithuanian National Energy Efficiency Action Plan claims that the highest potential to achieve total national energy savings is in residential buildings. Energy efficiency improvements in residential

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buildings are expected to contribute to total energy savings by 1000 GWh by the year 2020 (European Commission, 2013c). Under the implementation of the Energy Efficiency Directive of the European Parliament (Art 4, EED), Lithuania defined its priority to finance the renovation of multi-family houses that were built before 1993, which are buildings of Energy Performance Classes (EPCs) E, F and G (European Commission, 2013c). Although the renovation of the multi-family houses is the main instrument for achieving national energy savings, the rate of renovation is very low. In the last decade, just 2.6% of the total multi-family houses stock has been renovated (Bointner et al., 2014). One of the reasons for this meagre progress is that the renovations have been hampered by a lack of clear and long-term strategies thus resulting in low incentives from the public for thermal building renovations as well as other instruments that support a smooth renovation process (Bointner et al., 2014). Another barrier is the subsidisation of energy prices, which makes the thermal renovation less cost-effective. Conservation supply curves and marginal abatement cost curves are well-established instruments that show the economic assessment of investments and energy-related benefits. These curves are widely used in academic journals and scientific reports, and they can be applied in many different sectors, including the building sector (Jakob, 2006), (Wächter, 2013), (Kesicki, 2012), (Jaccard, 2010). These curves are

Corresponding author. E-mail address: [email protected] (A. Toleikyte).

https://doi.org/10.1016/j.enpol.2017.12.043 Received 8 May 2017; Received in revised form 12 December 2017; Accepted 25 December 2017 0301-4215/ © 2018 Elsevier Ltd. All rights reserved.

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The first cost curve shows the building investors’ perspective, and the second shows the least-cost options to achieve energy saving targets.

often used as a tool for making political decisions and setting preferences for climate protection and energy-saving measures by determining their costs and benefits. These instruments enable investments in energy efficiency solutions to be prioritized by their costeffectiveness in order to achieve energy savings targets or to reduce greenhouse gas emissions. Although these tools deliver beneficial effects and are widely used by policymakers, the curves are often criticized for their lack of information about assumptions, their application of simplified methodology and misleading applications when costs are negative (Kesicki and Strachan, 2011), (Chappin, 2016), (Levihn, 2016), (Taylor, 2012). In this paper, we provide the methodology and application of different cost curve approaches to show the energy saving potential and cost-effectiveness of investments in energy efficiency solutions in the Lithuanian residential building sector. The calculation is based on a bottom-up approach of disaggregating the building sector and assessing the techno-economics of the investments in energy efficiency solutions. This paper aims to show the energy saving potential that can be reached by 2030 through implementing energy efficiency solutions in the residential building sector and applying least-cost options of the investments from the building investor's point of view and the overall economic point of view. Moreover, policy recommendations are derived to show which buildings and energy efficiency measures should be addressed and which policy instruments can be used in order to achieve energy savings targets in the most effective way. This paper contains the following steps: (I) the methodology is defined, starting with the breaking down of the building stock and showing the application of two concepts of cost curves; (II) the Lithuanian residential building stock and its energy demand for space heating and hot water are described; (III) results are provided which show the most feasible investments for different building types from the investor point of view and the most cost-feasible investments to achieve national energy savings targets and, finally, (IV) discussion and policy recommendations are derived.

2.1. Breaking down the Lithuanian building stock The building stock was categorized into 30 building typologies while taking into account building type, construction period and heating supply system. The building types were defined based on the available data sources regarding the total stock gross floor area by construction period and building type. These data were provided by the Lithuanian State Enterprise Centre of Registers, Lithuania (Valstybės įmonė registrų centras, 2014). Data on the energy supply systems and their shares were collected from the IEE project ENTRANZE (ENTRANZE, 2016). Two building types were defined, which are singlefamily houses and multi-family houses, and the five following construction periods were specified: 1800–1940, 1941–1960, 1961–1990, 1991–2009 and 2010–2012. Buildings were further distinguished by the supply systems, with heat being supplied by district heat, gas or a boiler with biomass. 2.2. Energy demand calculation For each building type, the final energy demand for space heating and hot water was calculated. Firstly, the determination of the specific energy needed for space heating was carried out using the monthly energy balance approach based on the EN13790 “Energy performance of buildings – Calculation of energy use for space heating and cooling” methodology (ISO 0, 1379, 2008). The calculation was conducted with the building simulation tool Invert-EE/Lab which can calculate monthly and yearly specific energy demand for space heating based on the abovementioned norm by providing the tool with the country-specific input data (Müller, 2015). The following data for typical Lithuanian buildings were assessed, and these data were necessary to calculate yearly energy need for space heating using the monthly energy balance approach:

2. Methodology

• Description of buildings and building components (building geo-

Energy savings potential for space heating and hot water in Lithuania's residential building stock by 2030 is shown using energy savings cost curves. To create the cost curves, the following main methodology steps were carried out. – Taking into account building type, construction period and heating supply system, 30 building types were defined. Additionally, data on the total building floor area were collected. The main data sources were project ENTRANZE, ZEBRA2020 and national statistics (Bointner et al., 2014), (Valstybės įmonė registrų centras, 2014), (ENTRANZE, 2016). – Based on the data, the following 15 energy efficiency solutions were defined: energy efficiency improvements of the building envelope and domestic hot water supply system (energy efficiency improvements of the building envelope are related to five building class standards from D to A++); installation of a non-grid connected heating system (heat pump, ground source) in combination with these five building class standards; and finally installation of a solar thermal system in combination with the five building class standards and the heat pump system. Energy efficiency solutions and their techno-economic data came from the Lithuanian cost-optimality report. – Energy savings and the cost of energy savings were calculated by implementing the abovementioned energy efficiency solutions. – Total energy demand and energy savings by 2030 in each building type and in the total building stock was estimated using the calculated renovation rates.

• • • •

metry, thermal transmittance of building envelope elements). The U-values of the building elements of the buildings built in different periods were defined in the Lithuanian cost optimality report (European Commission, 2013a) and in the Technical Regulation of Construction STR 2.01.09:2005 (Ministry of Environment of the Republic of Lithuania, 2005). Transmission and ventilation properties, including temperature adjustment factor of building elements, ventilation type, heat recovery type (ISO 13790, 2008), (Ministry of Environment of the Republic of Lithuania, 2005). Heat gains from internal heat sources and solar radiation, such as shading reduction factor, glazing type, area of glass, solar irradiance (ISO 13790, 2008), (Ministry of Environment of the Republic of Lithuania, 2005) Climate data, for example, monthly outdoor temperature, solar radiation. Occupation behaviour and comfort requirements, including user profiles, indoor temperature (set-point temperature), hot water demand (ISO 13790, 2008), (Ministry of Environment of the Republic of Lithuania, 2005).

The yearly energy demand for space heating was calculated for each building type before implementing a renovation option. In the next step, five energy efficiency solutions related to the improvement of the building envelope and another 10 energy efficiency solutions related to the installation of a non-grid connected heating system were defined (see section “Energy efficiency solutions”). Energy savings were calculated for all building types while implementing different energy efficiency solutions.

From all of these data, the two types of cost curves were generated. 149

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maintenance renovation.

Total energy savings ∆Qj from 2012 to 2030 in the particular building type j was calculated by multiplying the specific energy savings ∆qj , total floor area nj of building type j and cumulated renovation rate from 2012 and 2030 ρj .

∆ci, j = (ici, j − icbase, j )*α + (qi, j − qbase, j )*

pi, j η

∆Qj = ∆qj *nj *ρj 2.4. Deriving the cost curves

The total cumulated renovation rate from 2012 to 2030 was derived from the annual renovation rate, cumulated for the whole period. The annual renovation of the residential building stock for each building type j was calculated following a Weibull distribution with the renovation rate ρj in year t,

β T

ρj (t) =

β

⎛ t ⎟⎞ ⎝T⎠

*

–

Energy savings cost curves provide cumulated energy savings for the considered time period on the x-axis and the cost-effectiveness of the selected renovation options for each building typology on the y-axis. The calculation of both parameters can be carried out by following steps: (1) calculating the cost-effectiveness of all renovation options for each building type using two different indicators, the levelized costs per heated floor area and cost of conserved energy; (2) selecting the leastcost renovation option for each building type or selecting the least-cost options for the total building stock, which are needed to achieve an energy saving target; (3) calculating the total energy savings for each building type and selected renovation option by 2030 while taking into account the building stock changes (renovation); and finally, (4) ranking the investments in energy efficiency solutions implemented for each building type from the cheapest to the most expensive. Two different approaches on how to select the least-cost option are provided. The first approach selects the most-cost effective solution for each building type. In other words, the first approach optimizes the investment for building owners to implement the most cost-effective investment for their buildings and neglect other possible solutions, as shown in Fig. 1. The first approach shows the investors’ perspective. Each bar presents a building type and a selected least-cost renovation option for this particular building type. All building types are ranked from the cheapest to the most expensive. The cost-effectiveness of the investments for each building type are shown on the y-axis, and total energy savings achieved by implanting each selected renovation option are on the x-axis. The selection of the least-cost option for each building type is based on two different indicators, the cost of conserved energy (€/kWh) and the levelized cost (€/m2). By using cost curves to show the building investors‘ perspective, information on the energy saving potential by using energy efficiency solutions with higher energy savings and costs is lost. For this reason, we provide the second approach, which shows the least-cost renovation options to achieve energy savings targets by showing an overall economic perspective. All building types and renovation options are shown on the curve and ranked based on their cost-effectiveness (Fig. 2). The first renovation option for a particular building type is the least-cost option from the investor point of view. The following renovation options for the same building type are shown on the curve, yet the total energy savings are presented as a margin of the first renovation option.

1

⎜

in which β denotes the shape factor and T is the characteristic lifetime of building (lifetime at which a cumulative failure rate of 63.2% occurs). 2.3. Cost-effectiveness of investments For each building type, the cost-effectiveness of investments in an energy efficiency measure was calculated. Different indicators to show the cost-effectiveness of investments were investigated, including the cost of conserved energy, levelized cost per saved energy and levelized cost per heated floor area. Cost of conserved energy shows cost of investments per saved energy. We ordered the measures from the cheapest to the most expensive based on the annualized initial investments per saved energy. However, when considering the perspective of investors, the economically feasible investments are those which cost less than the energy fuel price pE .

(ici, j − icbase, j )*α (qbase,

j

− qi, j )

<

p ηi, j

With ici, j Specific initial investment costs per building floor area of renovation option i in building type j (€/m2) icbase, j Specific initial investment costs per building floor area of renovation option base in building type j (€/m2) α Capital recovery factor p p Average energy price during the considered time period (€/kWh) ηi, j Efficiency of the heating system i in building type j qbase, j Final energy demand for space heating and hot water before renovation (kWh/m2/year) in building type j qi, j Final energy demand for space heating and hot water after implementation of renovation package i and building type j (kWh/m2/ year) In order to consider the saved money including the cost of the energy fuel, the cost-effectiveness of investments using the levelized costs was calculated. The investments with negative values are considered to be the most cost-effective measures. However, by using this indicator and by choosing the least-cost option, the problem of negative values occurs. The problem was highlighted in the journal papers by (Levihn, 2016), (Taylor, 2012) who said that the problem occurs when the negative specific cost is achieved either by a greater financial return, which is a desirable objective, or by a reduction in the energy or emission savings, which leads to the more negative cost (meaning better value) when the energy savings are lower. This outcome is not a desired aim, and it leads to the problem of using the cost-effectiveness per saved energy. For this reason, we have used the levelized cost per heated floor area in order to avoid the division of the saved energy, which leads to the potential failure, while selecting and ranking the “best values”. We calculated additional levelized costs per building floor area ∆ci, j (€/m2) for heating energy services in building type j with renovation option i compared to base renovation package, which is a

Fig. 1. Cost curves showing the building investors ‘perspective.

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significant part of the current residential building stock in Lithuania (Fig. 3). The total gross floor area of the residential buildings, including single-family houses and multi-family houses, was approximately 128 mm2, and the number of multi-family houses and single-family houses was 480,000 in 2012. Single-family houses make up 51% on the total residential building floor area, while apartment buildings represent 49%. Buildings built between 1961 and 1990 make up the largest share of the total residential building gross floor area, with 58.4% (Valstybės įmonė registrų centras, 2014), (ENTRANZE, 2016). Of the total gross floor area of the residential buildings, 45% is supplied by district heating. District heating is the main energy source of space heating and domestic hot water, followed by heat boilers with biomass, which supply 43% of the total residential building floor area. Other energy carriers make up only a small proportion, with gas, coal, electricity and oil occupying 6%, 5%, 0.2% and 0.01%, respectively (Valstybės įmonė registrų centras, 2014), (ENTRANZE, 2016). 3.2. Energy efficiency solutions Energy efficiency solutions were defined based on the cost optimality report, the Lithuanian report on energy performance requirements published by the European Commission (European Commission, 2013a). Fifteen renovation options were defined derived using data from this report. The energy demand for space heating, hot water and costs of investments were calculated for each building typology. The renovation options include the improvement of the building envelope and installation of a non-grid connected heating system (heat pump) as well as installation of solar thermal system for hot water. Improving energy efficiency of the building envelope is defined by the respective class of energy performance of the building. The Construction Technical Regulation STR 2.01.09:2012 “Energy Performance of Buildings. Certification of Energy Performance” defines the U-values of the building elements after renovation in order to achieve a particular class of energy performance of the building. Building classes start with class D as the lowest and end with class A++ renovations, which indicate very high energy performance with very low energy consumption. To calculate energy performance of the renovated buildings, the prescriptivebased approach is used. The U-values of building elements before renovation and after renovation are defined. Energy performance of buildings before and after renovation are calculated using monthly energy balance approach as described in Section 2.2 “Energy demand calculation”. Descriptions of the renovation option used in the calculation and associated U-values of the building elements are given in Table 1. The specific investment costs of the renovation options were

Fig. 2. Cost curves showing least cost renovation options to achieve a certain energy saving target (overall economic perspective).

All renovation options which lead to lower energy savings compared to the reference case (the first option) were excluded from the further consideration. The building with the last renovation option was selected because this option is the least-cost option to achieve the energy saving target.

3. Input data 3.1. Residential building stock In Lithuania, as in other European transition countries, multi-family houses built between 1960 and 1990 comprise the largest distribution of total building stock (Martinot, 1997), (Ürge-Vorsatz et al., 2006). These buildings are related to high energy demand for heating and hot water preparation. The lack of basic energy efficiency requirements at the time of construction, which is typical of these cement blocks and concrete panels, is the main reason that these buildings have such low energy performance (Ürge-Vorsatz et al., 2006). After 1950 in the USSR and in other eastern European countries, housing construction rapidly increased in order to improve the standard of living of citizens as well as to rebuild buildings which were destroyed during the Second World War (Smith, 2010). Nowadays these multi-family houses make up a

Fig. 3. Gross floor area of the residential building stock by building periods, building types and supplied energy in 2012 (Valstybės įmonė registrų centras, 2014), (ENTRANZE, 2016).

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Table 1 Description of the energy efficiency solutions applied for the Lithuanian residential building sector proposed in the Lithuanian cost optimality report. Renovation options

Description

D, C, A, A+, A++

Improving energy efficiency of the building envelope (D, C, A, A+, A++) and increasing control efficiency of heating system and domestic hot water supply system (U-values of building elements, [W/m2K], D: Uwindow= 1.81, Uwall=0.48, Uroof=0.25; Ufloor= 0.39; C: Uwindow= 1.6, Uwall=0.2, Uroof=0.16; Ufloor= 0.25; A: Uwindow= 1.0, Uwall=0.12, Uroof=0.1; Ufloor= 0.14; A+: Uwindow= 0.85, Uwall=0.11, Uroof=0.09; Ufloor= 0.12; A++: Uwindow= 0.7, Uwall=0.1, Uroof=0.08; Ufloor= 0.1) Improving energy efficiency of the building envelope (D, C, A, A+, A++) and installation of non-grid connected heating system (heat pump, ground, COP=4) Improving energy efficiency of the building envelope (D, C, A, A+, A++), installation of non-grid connected heating system (heat pump, ground, COP=4) and installation of solar thermal system for hot water

D, C, A, A+, A++ in combination with heat pump D, C, A, A+, A++ in combination with heat pump and solar thermal system

calculated using data from above mentioned “cost optimality report” (European Commission, 2013a). This report provides data on the initial investment costs per saved energy while implementing different renovation options and non-grid connected heating systems for 36 reference buildings of different constructions (European Commission, 2013a). To assess the specific investment cost of the renovation options for building types used in this paper, the following calculation steps were carried out:

most expensive energy efficiency solution for this building type is implementing building class A++, changing the heating system to heat pump and installing solar thermal system. The same multi-family houses that is supplied by district heating and gas has a slightly higher cost of conserved energy in energy efficiency solutions compared to buildings with biomass due to the efficiency of the heating system and corresponding lower energy savings. Specific energy savings in the apartment building with biomass that implements the least-cost option (building class C plus heat pump) are 182 kWh/m2, while the savings of implementing building class A++ with a heat pump and solar thermal system are 205 kWh/m2. When it comes to the cost-effectiveness of the investments when calculating levelized costs, the estimation showed different results. In this case, buildings using biomass correspond to the highest cost of investments compared to the buildings supplied by district heating and gas. The energy fuel price has an impact on the cost-effectiveness. The biomass price is low compared to the price of district heating and gas. The highest cost-effectiveness of the investments in energy efficiency solutions can be achieved in the apartment buildings supplied by the district heating. The least-cost option for this type of building would be to invest in building class A. Levelized costs in energy efficiency solutions that achieve energy performance classes A, A+ and A++ were found to be negative, varying from −5.6 €/m2 to −4.3 €/m2. Specific yearly energy demand for space heating and hot water before renovation was found to be 180 KWh/m2 in this apartment building (built between 1941 and 1960, supplied by district heating). Specific energy savings for space heating and hot water by achieving classes A, A+ and A++ were calculated as 115 kWh/m2, 120 kWh/m2 and 125 kWh/m2, respectively. The same building class (multi-family houses, 1941–1960) using gas and biomass fuels showed higher levelized costs compared to the buildings with district heating. This is due to the lower fuel prices of gas and biomass compared to the district heat price in Lithuania. The least-cost option for the apartment building with gas and biomass is building class C. The levelized costs were 0.08 €/m2 and 1.6 €/m2 for buildings with gas and biomass, respectively. The specific final energy savings were found to be 85 kWh/m2 and 108 kWh/m2 for buildings with gas and biomass, respectively. The highest energy savings could be achieved from A++ renovation and installing a non-grid connected heating system, heat pump and solar thermal system. Single-family houses built between 1941 and 1960 and supplied by district heating can be renovated in a cost-effective way to achieve energy performance class C. The levelized costs per saved energy were −0.64 €/m2. Specific energy savings for space heating and hot water by achieving these building classes were measured as 112 kWh/m2. The results show that apartment buildings can be renovated in a more cost-effective way than single-family houses. The main reason for this is the specific initial investment costs which correlate to the size of the building. Consequently, the specific initial investment costs were higher for the single-family houses. It was found that levelized costs are high and energy savings are low in multi-family houses and single-family houses built after 1991. In this way, the newer the buildings are, the higher the levelized costs are due to the low energy savings.

• Energy savings for space heating for all renovation options and for all investigated building types were calculated. • Data from “cost optimality report” on the specific energy savings and associated investment costs were collected. • Cost functions were derived which let to identify the specific costs of saved energy after implementing all investigated renovation options for different type of buildings.

3.3. Economic input parameters Energy fuel prices for district heating, gas and biomass in 2012 were 0.09 €/kWh, 0.05 €/kWh and 0.03 €/kWh, respectively (prices include value-added taxes [VAT]) (European Commission, 2013b). These prices were set using the statistics provided by the Lithuanian National Commission for Energy Control and Prices. Energy fuel price development scenarios were taken from the Lithuanian cost-optimality report (European Commission, 2013a). The fuel prices increase from 2012 to 2030 by 54%, 67% and 28% for district heat, gas and biomass, respectively. The trend of the future price development was linked to the energy price trends provided by the European Commission. The discount rate used in this calculation is 3%. 4. Results 4.1. Techno-economics of the energy efficiency solutions The costs of investments were calculated for each building type after implement all possible energy efficiency solutions. Figs. 4 and 5 show the cost of conserved energy and cost-effectiveness of investments in the energy efficiency solutions (y-axis) and specific energy savings for space heating and hot water achieved by these solutions (x-axis) for multi-family houses and single-family houses built between 1941 and 1960 and supplied by district heating, gas and biomass. The costs were calculated using the discount rate of 3% and calculation lifetime of 30 years. The calculation using the cost of conserved energy showed slightly different results compared to the calculation using cost-effectiveness. The calculation shows that using the cost of conserved energy, the cheapest investments can be achieved for multi-family houses which use biomass as energy fuel for space heating. Cost of conserved energy of the investments in this building type vary from 0.05 €/kWh to 0.08 €/kWh. The least-cost option is to implement building class C and change the heating system from a biomass boiler to heat pump. The 152

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Fig. 4. Specific energy savings (x-axis) and cost of conserved energy of investments (yaxis) in different energy efficiency solutions for different types of buildings.

up to 2030 varied from approximately 50% for the buildings built between 1800 and 1940 to 7.5% for the buildings built after 2010 (see Table 2). Figs. 6 and 7 show the cost curves of the energy savings by applying energy efficiency solutions using the first approach (legend description of both figures is given in Table 3). Final energy demand can be reduced by 61% by 2030 if the energy efficiency solutions based on the cost of conserved energy are selected (Fig. 6) and by 56% if the energy efficiency solutions based on the levelized costs are selected (Fig. 7). Fig. 6 shows cumulated energy savings from 2012 to 2030 in all investigated building types (x-axis) and the cost of conserved energy of the investments in the selected renovation option (y-axis). Each bar represents building type and selected least-cost renovation option

4.2. Energy saving cost curves In a further step, we calculated the total energy saving potential to year 2030 for the entire residential building stock using two different cost curves. Firstly, the most cost-effective renovation option for each investigated building type and ranking each building type from the cheapest to the most expensive were selected, and secondly, all building types with all renovation options were ranked from the cheapest to the most expensive. The final energy demand for space heating and hot water in the residential building stock was 7.7 TWh in 2012. The development of the final energy demand by year 2030 is based on the renovation rate and selected renovation options. The calculated cumulated renovation rate

Fig. 5. Specific energy savings (x-axis) and cost-effectiveness (y-axis) of investments in different energy efficiency solutions for different types of buildings (MFH – Multi-family houses, SFH – Single-family houses).

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Table 2 Cumulated renovation rate in 2030 compared to 2012 and yearly renovation rate for different type of buildings built in different building periods. Single-family houses 1800 − 1940 Share by 2030, % 52% Renovation rate (yearly), % 3.1%

Multi-family houses

1941 − 1960

1961 − 1990

1991 − 2009

2010 − 2012

1800 − 1940

1941 − 1960

1961 − 1990

1991 − 2009

2010 − 2012

43% 2.5%

31% 1.8%

12% 0.7%

7% 0.4%

49% 2.9%

36% 2.1%

31% 1.8%

12% 0.7%

7% 0.4%

Fig. 6. Energy saving cost curve showing the building investors ‘perspective using cost of conserved energy.

Fig. 7. Energy saving cost curve showing the building investors ‘perspective using levelized cost per heated floor area.

reason, from the investors’ point of view, these investments do not save costs. Fig. 7 shows the selected energy efficiency measures that use the levelized costs and thus show the investors’ perspective. The results show that the most cost-effective options are investing in multi-family houses (built in years 1800–1940, 1941–1960 and 1961–1990) that are supplied by district heating to implement energy efficiency class A. The costs per heated area vary from −12.3 €/m2 to −4.4 €/kWh for these building types. The results show that 24% of the total energy savings by 2030 can be achieved in a cost-effective way. The cost curve approach using the least-cost option neglects many energy efficiency solutions which would result in higher energy savings and additional investments. Moreover, by using this type of cost curve, we encourage lock-in effects by neglecting energy efficiency solutions

(legend description is given in Appendices, Table 3). The results show that investments in multi-family houses (built during years 1800–1940, 1941–1960 and 1961–1990) that are supplied by biomass (three first bars), implement efficiency class C and change the heating system would be most cost-effective, leading to a total final energy savings of 9%. The highest energy savings can be achieved by renovating multifamily houses that were built between 1961 and 1990 and are supplied by district heating (8th bar, Fig. 6). The total final energy savings were calculated as 685 GWh or 9% by 2030 with the selected renovation option of energy efficiency class C and with the replacement of the heating system. However, the three cheapest investments have initial investments that are higher than energy costs because of the biomass price. For this 154

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Fig. 8. Energy saving cost curve showing least cost renovation options to achieve a certain energy saving target (overall economic perspective) (MFH – Multifamily houses, SFH – Single-family houses).

or per heated floor area. The use of the cost of conserved energy (annualized investments per saved energy) showed that energy efficiency class C and installation of a heat pump in the apartment buildings built between 1800–1940, 1941–1960 and 1961–1990 and supplied by biomass would be the cheapest option. However, when the levelized costs were used to assess the least-cost options, the results differed strongly from the abovementioned approach. Energy efficiency class A implemented for the multi-family houses built in the periods of 1800–1940, 1941–1960 and 1961–1990 and supplied by district heating was the most cost-effective measure. By using the first indicator and selecting these energy efficiency options with the lowest costs, 61% of the energy savings for space heating and hot water can be achieved from 2012 to 2030. Meanwhile, using the second indicator would result in a savings of 56%. The use of the cost of conserved energy for selecting the least-cost options led to higher energy savings compared to the use of the levelized costs. However, the cost of conserved energy did not show the least-cost option from the investor point of view. Both approaches showed that by selecting only the least-cost option for each building type, the lock-in effect might occur by neglecting energy efficiency solutions, which can lead to higher energy savings and small additional costs for investors compared to the least-cost option. For this reason, we used the second approach, which ranks all renovation and implementation options for all building types. This approach shows the least-cost options for the total building stock to achieve the target energy savings. To achieve energy savings of 30% from 2012 to 2030, the following investments were found to be the most cost effective: energy efficiency class A++ for multi-family houses (1941–1960 and 1961–1990) that are supplied by district heating, followed by efficiency class A for single-family houses (1800–1940 and 1961–1990) that are supplied by district heating. The second approach shows that to achieve the energy savings targets, attention should be paid to the refurbishment of old multi-family houses built before 1990 and supplied by district heat because these buildings provide the highest energy savings; by renovating these houses, the most money can be saved. Moreover, implementation of energy efficiency solutions which lead to high energy savings (energy performance class A+ and A++) should be promoted because these solutions are correlated with high additional energy savings and relatively low additional investments compared to energy performance class C and A, which were selected as the least-cost option from the investors’ point of view. This is important in order to avoid the lock-in effect.

which lead to higher energy savings. Therefore, to avoid these effects, we utilized the adapted cost curve to show a societal and overall economic perspective. All building types and implemented measures were ordered based on their cost-effectiveness and the last renovation option for the corresponding building type was selected, which is still the leastcost option but also considers the energy savings targets. This cost curve might show the most feasible solutions to implement for particular building types to achieve energy savings targets. Fig. 8 shows the cost curve of the energy savings by applying energy efficiency solutions, which are the most cost-effective to achieve 30% of energy savings. The results show that energy efficiency class A++ implemented in apartment buildings (built in years 1941–1960 and 1961–1990) and supplied by district hearing are the most cost-effective measures and can save 620 GWh from 2012 to 2030. Energy efficiency class A in the singlefamily houses (1800–1940 and 1961–1990) supplied by district heating are the most cost-effective energy efficiency improvements. To consider one selected building type, it can be seen that the investments in a more efficient renovation option are still cost-effective and lead to higher energy savings. The least-cost option from the investor point of view for apartment buildings built between 1961 and 1990 and supplied by district heating was selected as energy performance class A. The leastcost option from the total building stock to achieve 30% of the target energy savings for the same building is energy performance class A+. The levelized costs of investments in renovation to achieve A and A++ energy performance classes was −4.3 €/m2 and −3.1 €/m2, respectively, and the total energy savings for space heating and hot water from 2012 to 2030 was 530 GWh and 572 GWh respectively. 5. Discussions In this paper, total energy saving potential by year 2030 for space heating and hot water and associated costs of investments in energy efficiency solutions were calculated in the Lithuanian residential building stock. Two different approaches of deriving cost curves and two different indicators to assess the least-cost energy efficiency options were used and both led to different findings. The final energy demand for space heating and hot water in the residential building stock was 7.7 TWh in 2012. Cost-effectiveness of different energy efficiency options were assessed for different building types, and the least-cost option for each building type was selected. This selection was made in order to calculate energy savings potential by 2030 and identify which options have the lowest costs per saved energy 155

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6. Conclusions and policy recommendations

for building thermal renovations could be provided to address low-income homeowners and residential buildings with low energy performances. Possible examples of how to select the buildings to receive financial support from the state for the thermal renovation are as follows:

This paper shows energy savings potential for space heating and hot water by year 2030 in the Lithuanian residential building stock, which can be achieved by investing in energy efficiency solutions in the most economical feasible way from the building investors’ point of view and from the overall economic point of view. Firstly, we demonstrated two approaches of cost curves, their applications and the interpretation of the results. Secondly, we showed the most cost-feasible investments for different building types. Finally, we identified the most cost-effective way to achieve energy saving targets and the necessary total investments. Policy recommendations were derived based on the calculation results. The calculation was carried out for the Lithuanian residential building sector and policy recommendations address this country specifically. However, policy recommendations can be directly applied for other European transitions economies, due to their similarities in building stock, policies and costs. Moreover, the methodology can be applied for other European countries using country specific input data on the building stock and costs. The results show that renovating the old multi-family houses that are supplied by district heating is clearly the most cost-effective option due to very low energy performance of the buildings, the size of the buildings and their accordingly relatively low specific investment costs as well as high district heating prices. It seems that an investment in energy efficiency solutions is a very good option for homeowners to save money. However, there are several barriers stopping the renovation activities. One of the barriers is the compensation for the fuel prices. Many homeowners in Lithuania get heating price compensation from the government. These calculations were made by using the standard district heating price. By having a lower district heating price, investments in energy efficiency measures are not cost-effective. This instrument is a barrier for the implementation of energy efficiency measures. Therefore, the implementation of energy efficiency measures would be very difficult (or virtually impossible) given the current nation-wide policy. Instead of using subsidies for heating costs, subsidies

• Buildings of a minimum EPC with G and lower, • Buildings whose total cost of heating is 25% or more of its value • Buildings whose total cost of heating makes up a high share of the

•

• •

income of the residents. The second outcome shows that there is a need to promote building owners’ investments in deep renovation measures (energy performance class A+ and A++) in order to lock out the full energy saving potentials and ensure the transition of the Lithuanian building stock towards nZEBs. This outcome would serve to use the potential of the environmental, social and economic benefits of these investments. Although investments in A+, A++ renovation are cost-effective for different types of buildings, the up-front investments are often disliked by investors. For this reason, to trigger the uptake of deep renovations, the following recommendations are presented, including legislative, economic and communications suggestions: Provide building owners and investors with tailored advice. The EPCs aim at providing information on the energy performance of a building for its owners. At present, EPCs are required for buildings that are being renovated and new buildings in Lithuania. These EPCs could be implemented for all buildings in order to provide information and tailored advice about the full range of renovation options and their benefits. Provide financial products that address deep renovation (A++ or nZEB renovation). Provide low-interest loans to housing associations or provide grants with the grant rates that vary depending on the expected energy savings. Promote market uptake of deep renovation with information campaigns and demonstration projects to address the investors and housing associations.

Appendices See Table 3 here.

Table 3 Building types and selected renovation options (MFH – Multi-family houses, SFH – Single-family houses). Index

Cost of conserved energy (Fig. 6)

Cost-effectiveness (Fig. 7)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

MFH(1800 − 1940,Biomass)-C, HP MFH(1941 − 1960,Biomass)-C, HP MFH(1961 − 1990,Biomass)-C MFH(1800 − 1940,District heat)-C MFH(1800 − 1940,Gas)-C MFH(1941 − 1960,District heat)-C, HP MFH(1941 − 1960,Gas)-C, HP MFH(1961 − 1990,District heat)-C, HP MFH(1961 − 1990,Gas)-C, HP SFH(1800 − 1940,Biomass)-C MFH(1991 − 2009,Biomass)-A SFH(1961 − 1990,Biomass)-C SFH(1941 − 1960,Biomass)-C MFH(1991 − 2009,District heat)-A MFH(2010 − 2012,Biomass)-A SFH(1800 − 1940,District heat)-C MFH(1991 − 2009,Gas)-A SFH(1800 − 1940,Gas)-C SFH(1961 − 1990,District heat)-C SFH(1961 − 1990,Gas)-C SFH(1941 − 1960,District heat)-C SFH(1941 − 1960,Gas)-C MFH(2010 − 2012,District heat)-A, HP

MFH(1800 − 1940,District heat)-A MFH(1941 − 1960,District heat)-A MFH(1961 − 1990,District heat)-A SFH(1800 − 1940,District heat)-C MFH(1800 − 1940,Gas)-C SFH(1961 − 1990,District heat)-C MFH(1991 − 2009,District heat)-A SFH(1941 − 1960,District heat)-C MFH(1941 − 1960,Gas)-C MFH(1961 − 1990,Gas)-C MFH(2010 − 2012,District heat)-A MFH(1800 − 1940,Biomass)-C MFH(1961 − 1990,Biomass)-C MFH(1991 − 2009,Gas)-A MFH(1941 − 1960,Biomass)-C MFH(2010 − 2012,Gas)-A SFH(1991 − 2009,District heat)-A MFH(2010 − 2012,Biomass)-A MFH(1991 − 2009,Biomass)-A SFH(2010 − 2012,District heat)-A SFH(2010 − 2012,Gas)-A SFH(2010 − 2012,Biomass)-Maintenance SFH(1941 − 1960,Gas)-C (continued on next page)

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Table 3 (continued) Index

Cost of conserved energy (Fig. 6)

Cost-effectiveness (Fig. 7)

24 25 26 27 28 29 30

SFH(1991 − 2009,Biomass)-A MFH(2010 − 2012,Gas)-A, HP SFH(1991 − 2009,District heat)-A SFH(1991 − 2009,Gas)-A SFH(2010 − 2012,Biomass)-A SFH(2010 − 2012,District heat)-A SFH(2010 − 2012,Gas)-A

SFH(1991 SFH(1961 SFH(1991 SFH(1941 SFH(1800 SFH(1961 SFH(1800

− − − − − − −

2009,Gas)-A 1990,Gas)-C 2009,Biomass)-Maintenance 1960,Biomass)-C 1940,Gas)-C 1990,Biomass)-C 1940,Biomass)-C

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