Modeling energy refurbishment scenarios for the Hellenic residential building stock towards the 2020 & 2030 targets

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Modeling energy refurbishment scenarios for the Hellenic residential building stock towards the 2020 & 2030 targets Elena G. Dascalaki ∗ , Constantinos A. Balaras, Simon Kontoyiannidis, Kalliopi G. Droutsa Group Energy Conservation, Institute for Environmental Research & Sustainable Development, National Observatory of Athens, I. Metaxa & Vas. Pavlou, GR-15236 Palea Penteli, Greece

a r t i c l e

i n f o

Article history: Received 30 November 2015 Received in revised form 29 March 2016 Accepted 1 June 2016 Available online xxx Keywords: Residential buildings Building stock model Scenario analysis Energy efficiency strategies

a b s t r a c t Residential buildings in Greece account for about 79% of the exclusive-use building stock and consume about a quarter of the total final energy consumption, with space heating and domestic hot water being the main energy end-uses. About 58% of the dwellings were constructed before the 80 s and the adoption of the first thermal insulation regulation. This paper presents the results from the Hellenic pilot action within EPISCOPE. The overall approach and analysis are based on the national TABULA residential building typology for single- and multi-family houses in order to estimate heating energy performance and savings. The work exploits Census and statistical data for defining the Hellenic building stock and empirical adaptation factors to make more realistic estimates from normative calculations. The analysis is supported by a detailed data disaggregation in terms of the number of dwellings and floor areas, based on envelope thermal characteristics, heat production units, energy carriers, use of renewables etc. The calculation results are adapted for the building types and then projected to the building stock. Numerous scenarios for different modernization rates are assessed for identifying the most promising refurbishment strategies in space heating and DHW for reaching the 2020 and 2030 national CO2 emission targets. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Over the past decades, the buildings sector has been at the centre stage of European energy and environmental protection policy actions and regulatory measures. This is well justified since buildings in the European Union Member States (EU-28) consume about 40% of the total final energy consumption and are responsible for 36% of the CO2 emissions in the EU [1]. Specifically, residential buildings dominate the existing building stock, representing about 75% of the 25 billion m2 in the EU [2]. The EU-28 final energy consumption in residential buildings reached 296 million tonnes of oil equivalent (Mtoe) in 2013 [1], decreasing in absolute terms since its historic peak at 311 Mtoe in 2010, although it slightly increased by 0.7% from 2012 to 2013. Space heating is the most important enduse in residential buildings (67%), but its share has been slightly declining since 2000 [2]. Domestic hot water (DHW) ranks second with a stable share at 13% of the total, electrical appliances have climbed to 11%, followed by cooking at 6%, lighting at 2% and cooling at only 0.5%.

∗ Corresponding author. E-mail address: [email protected] (E.G. Dascalaki).

In Greece, the total number of buildings approaches 4.1 million [3] of which 3.78 million are exclusive-use buildings, with 79.2% residential buildings. Mixed-use buildings reach ∼330,000 of which the majority has main use as residential dwellings (77.5%). The evolution of final energy consumption is illustrated in Fig. 1, including the latest officially-reported data for 2013 [1]. The total final energy consumption reached 15.3 Mtoe, relatively close to that of the 1990 levels (i.e. 14.7 Mtoe), following a drop by −11% from 2012 to 2013. Hellenic buildings accounted for 36.6% of the total final energy use and reached 5.6 Mtoe, with a notable decrease by −23% from the 7.3 Mtoe in 2012. Hellenic residential buildings used 3.8 Mtoe in 2013 or 24.8% of the total final energy consumption in Greece [1]. Space heating and DHW are the main energy end-uses, i.e. 63.7% is used for space heating, 17.3% for cooking, 10.2% for appliances and equipment, 5.7% for DHW, 1.7% for lighting and 1.3% for cooling [4]. The annual average thermal energy use averages 10,244 kWh per household, of which 85.9% for space heating and 4.4% for DHW [4]. Heating oil (63.8%) remains the main fuel source for space heating. The annual average electrical energy use per household is 3750 kWh, which is mainly used for cooking (38.4%), white appliances (28.9%), DHW (9.4%), lighting (6.4%), cooling (4.9%) and space heating (3.0%). As shown in Fig. 1, the observed variations of final energy use for the residential sector are partly due to the prevailing winter

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Fig. 1. Evolution of total final energy consumption in Greece and contribution of the residential and commercial sectors (main y-axis). The trend-line corresponds to the average heating degree days (secondary y-axis). The embedded graphic refers to the final energy breakdown for the different sectors in 2013. (Source of data: ELSTAT; Eurostat [28])

conditions, expressed by the heating degree days (HDD). Other driving factors for the dropping trend of energy consumption over the past few years is the deep economic recession and the tax increase on heating oil imposed in 2012. These externalities have a direct impact on occupants’ behaviour forcing them to reduce operational energy costs, even at the expense of proper indoor thermal conditions. The modernization of buildings by implementing energy efficiency measures (EEMs) is a logical path forward in order to extend the useable lifespan and operations of the existing building stock, improve living conditions and lower energy bills for occupants. These efforts can play an important role in meeting the European and national targets to become a highly energy-efficient and low carbon economy, reduce energy import dependency and increase security of supply in accordance to the European 2020 Strategy and the new plan towards 2030 and beyond. The final energy use intensity, i.e. energy per unit floor area (kWh/m2 ) for space heating, an indicator used to assess energy efficiency trends for household heating, has decreased practically throughout the EU-28 since 2000 [2], averaging 2.3% per annum. The current values range from 60 to 90 kWh/m2 in the south (e.g. Malta, Spain, Bulgaria, Greece and Croatia) to 175–235 kWh/m2 in the north (e.g. Estonia, Latvia and Finland). Over the years, several studies have been performed in Greece to assess the potential of EEMs in Hellenic residential buildings [5–8]. They all reach the same conclusion, i.e. there are significant energy savings in the buildings sector that remain untapped. However, it has long been recognized that there may be significant deviations amongst calculated versus actual energy use in the design of new buildings or estimated savings as a result of implementing EEMs. Calculations and even simulation tools may provide different results even for the same building. This may be due to a multitude of reasons including occupants’ behaviour and deviations from the assumptions of normative calculations. Beyond the well prescribed methods on how to validate the accuracy or calibrate software predictions for detailed analysis at building level, the challenge remains on how to adapt the estimations from official calculation tools and facilitate the process of handling the diversities for a large building portfolios or building stocks on a regional and national basis. A multinational effort within EPISCOPE [9] paved the way by developing a conceptual framework for assessing refurbishment processes of European residential buildings in a transparent and effective way. Accordingly, EPISCOPE motivated a number of national pilot actions targeting regional or national residential building stocks, considering different approaches.

The work presented in this paper proceeds as follows. Section 2 outlines the overall methodology. The approach is based on the Hellenic residential building typology that is coupled with Census and statistical data in order to set up and populate a building stock model. Annual calculations are performed using the official national software and the results are adapted to produce more realistic estimates of actual energy use, which are then projected to the national building stock. Section 3 elaborates the results from different modernization scenarios in order to assess the viability of different energy saving strategies towards achieving the national CO2 emission targets for 2020 and 2030. The scenarios first focus on the modernization of building thermal envelopes, next on the heat generation systems and finally consider combined measures. Section 4 elaborates the conclusions from this study and future work for improving the process. 2. Methodology This work presents a coherent approach for transferring the know-how of assessing the energy performance from a single building to the level of handling millions of buildings in a national building stock. The overall method is illustrated in Fig. 2. The starting point is the Hellenic residential typology that sets the stage in terms of analysing the available information, organizing all inputs and data exchange by properly populating the characteristic parameters of the typology. The calculations are performed using the official national software (TEE-KENAK) to estimate the annual space heating and DHW energy demand, primary energy consumption and CO2 emissions per unit floor area. The results from the normative calculations are then adapted using a derived set of empirical factors as multipliers for correcting the calculated values to obtain more realistic estimates of the actual energy use. The inputs to the building stock model are derived from an analysis of Census or statistical data (e.g. number of buildings and floor areas for occupied dwellings) that correspond to the different building types, with the specific construction and system characteristics. The adapted estimates for the various building types are finally projected to the entire building stock. New construction, demolition and refurbishment rates are also taken in to account in order to estimate on an annual basis the number of buildings and floor areas that correspond to the building matrix and estimate the annual final or primary energy use or savings, fuel mix and CO2 emissions. Different scenarios are evaluated by implementing various EEMs on the building envelopes or the systems or both, coupled with different modernization rates for assessing the results towards the national CO2 emission targets for

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Fig. 2. Schematic of the overall process implemented in this study.

2020 and 2030. The entire process for input and output manipulation and analysis is facilitated by a demo tool. The following sections elaborate each one of the main stages. 2.1. Hellenic residential building typology Different experiences with building typologies have emerged in Europe over the past few years to assess the energy performance and EEM of large portfolios and residential building stocks following top-down or bottom-up approaches [10–12]. Amongst the most notable efforts is the TABULA concept [13–18]. The TABULA typologies are also proposed to EU-28 Member States as reference buildings [19] in order to facilitate national work for calculating cost-optimal levels of minimum energy performance requirements for buildings and building elements as mandated by the EPBD recast (2010/31/EC). The use of building typologies is a practical tool for modeling the energy performance of large building portfolios, regional or national building stocks, by overcoming the complexities of an approach at the level of individual buildings. The national TABULA typologies were developed following a common methodical structure consisting of a classification scheme grouping buildings according to their size, age (construction period) and further energy-relevant parameters, and a set of exemplary buildings representing the respective building types. The TABULA concept was enhanced and extended during EPISCOPE [9] to reach a total of 20 European typologies (http://episcope.eu/ building-typology/country), including new buildings meeting the national requirements or more ambitious standards towards the national nearly zero energy buildings (NZEB) definitions. The first harmonized structure of the Hellenic residential typology classified buildings in a total of 24 types [13]. In terms of main building construction practices, one major landmark is the introduction of the first Hellenic building thermal insulation regulation (HBTIR) in 1980. The European Directive on the Energy Performance of Buildings (EPBD 2002/91/EC) was enforced in 2010 by the Hellenic regulation on the energy performance in the building sector – KENAK that replaced HBTIR [20], introducing more stringent U-values for the building’s thermal envelope and minimum effi-

ciency specifications for the technical installations. For example, the U-value for external vertical walls in contact with outdoor air was 0.7 W/m2 K with HBTIR and is reduced with KENAK by 14% to 43% depending on location. For systems, the requirements include, for example, the use of outdoor temperature compensation and zone thermostatic controls. For DHW production, post-2011 buildings should cover 60% of the load with renewables in accordance to KENAK and a national law (N.3851/2010) that transposed the European Renewable Energy Directive (RED 2009/28/EC). The Hellenic building matrix was enhanced during EPISCOPE to include in the typology the most recent constructions (i.e. after the implementation of KENAK), initiating the post-2011 era of ‘new’ buildings with higher energy performance. Accordingly, the Hellenic typology used in this work includes the following classes: 1. Building size, using two categories: single family houses-SFH (low-rise buildings with one or two floors) and multifamily houses-MFH. 2. Building age, using a classification based on the year of building construction, i.e. three age bands: pre-1980 (‘old’ buildings before HBTIR considered without thermal insulation), 1981–2010 (considered thermally insulated according to HBTIR), post-2011 (considered up to KENAK standards). 3. Building location, using the four climate zones (A-D) defined by KENAK on the basis of HDD (Fig. 3). A “typical” building is assigned to each of the 24 classes that has the geometry of a real (existing) example building, with construction and system characteristics calculated as weighted averages of the corresponding data for the existing building stock. Accordingly, they are considered to be representative of all buildings in the particular class. Supplementary sub-typologies regarding building elements and systems were prepared in accordance to the construction and system installation trends in the Hellenic residential building sector, for the three age bands. Data on the “typical” buildings were supplied to the building typology, including general features (i.e. number of storeys, floor areas), geometrical data (i.e. building volumes, envelope areas) and thermal envelope proper-

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Fig. 3. Overview of the main thermal envelope characteristics of the Hellenic typology used in EPISCOPE, with the U-values (W/m2 K) for single-family houses (SFH) and multi-family houses (MFH) at the four national climate zones (A in the south and D in the north of the country) along with the range of heating degree days (HDD) in the corresponding climate zone.

Table 1 Overview of the main system efficiencies of the Hellenic typology used in EPISCOPE. (Empty cells denote non-existing systems or systems with scarce representation in the respective subset of the building stock). Building type (*) Space heating Oil Natural Boiler Gas Boiler Single-Family Houses (SFH) 0.84 A pre-1980 0.84 A 1981-2010 0.89 A post-2011 B pre-1980 0.84 0.89 0.84 0.89 B 1981-2010 0.89 0.89 B post-2011 0.85 0.89 C pre-1980 0.84 0.89 C 1981-2010 0.89 0.89 C post-2011 0.82 D pre-1980 0.83 D 1981-2010 0.89 D post-2011 Multi-Family Houses (MFH) A pre-1980 0.83 A 1981-2010 0.83 0.89 A post-2011 0.82 0.89 B pre-1980 0.83 0.88 B 1981-2010 0.89 0.89 B post-2011 C pre-1980 0.84 0.89 0.85 0.88 C 1981-2010 0.89 0.89 C post-2011 0.83 D pre-1980 0.87 D 1981-2010 0.89 D post-2011

DHW heating Heat Pump

District Heating

1.70 1.70 3.60 1.70 1.70 3.60 1.70 1.70 3.60 0.88 0.88

Direct Electricity

Open fire

Stoves (oil)

Electric Resistance

Electric Resistance & Solar panels

Oil boiler

Oil boiler & Solar panels

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.98

0.84 0.86

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.97

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.97

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.97

0.95 0.97 1 0.95 0.97 1 0.95 0.97 1 0.95 0.97 1

0.84 0.86 0.89 0.82 0.85 0.89 0.85 0.85 0.89 0.82 0.84 0.89

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.98

0.83 0.85

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.97

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.97

0.98 0.98

0.20 0.35

0.80 0.80

0.95 0.97

0.95 0.97 1 0.95 0.97 1 0.95 0.97 1 0.95 0.97 1

3.60 1.70 1.70 3.60 1.70 1.70 3.60 1.70 1.70 3.60 0.88 0.88 3.60

0.82 0.85 0.85 0.85 0.82 0.84

0.82 0.84 0.84 0.86

0.87

0.83 0.85 0.89 0.82 0.84 0.89 0.84 0.86 0.89 0.83 0.87 0.89

Natural Gas

Natural Gas & Solar panels

0.89 0.89

0.89

0.89

0.89 0.89 0.89

0.89 0.88 0.89 0.88

0.89 0.88 0.89 0.89 0.88 0.89

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Table 2 Distribution of the building types in the inhabited Hellenic building stock. Single-Family Houses (SFH)

Multi-Family Houses (MFH)

Building typea

No of buildings

Inhabited floor area (×1000m2 )

Building typea

No of buildings

Inhabited floor area (×1000 m2 )

A pre-1980 A 1981-2010 A post-2011 B pre-1980 B 1981-2010 B post-2011 C pre-1980 C 1981-2010 C post-2011 D pre-1980 D 1981-2010 D post-2011 Total

256,126 183,793 129 589,178 295,165 179 471,650 237,444 142 54,688 35,602 4 2,124,100

20,955 29,732 19 51,685 50,715 33 39,491 39,787 20 4532 5670 0 242,638

A pre1980 A 1981-2010 A post2011 B pre1980 B 1981-2010 B post2011 C pre1980 C 1981-2010 C post2011 D pre1980 D 1981-2010 D post2011 Total

14,815 26,858 33 134,423 118,639 168 42,918 64,985 59 2511 4664 3 410,076

2326 9660 18 40,947 57,572 113 14,404 29,629 32 411 1868 1 156,981

a

Climate zone Construction period.

ties as well as heating system features. The various building types take into account the construction characteristics and differences in the availability of energy carriers and heat supply systems in the four climate zones of Greece (e.g. only zones B and C have a natural gas supply network and district heating is only available in zone D). The main technical characteristics of the 24 building types that were used during this study are summarized in Fig. 3 for the U-values of the building envelope components (note that the post-2011 values are the same for both SFH and MFH, according to the national regulation) and in Table 1 for the system efficiencies (note that thermal efficiencies are based on higher calorific values, following the EPISCOPE notation). Each one of the 24 building types is used in the building stock model for numerous different combinations of space heating & DHW generation systems. The main space heating systems that can be considered depend on the energy carriers, e.g. oil and natural gas boilers, heat pumps, direct electricity units, district heating, open firewood and stoves. The DHW systems may include combinations of simple electric storage heaters, solar, boilers etc. Depending on the modernization scenarios and the implemented EEMs considered in the building stock model, the characteristics of the typical buildings are redefined every year. For example, a new wall Uvalue of the typical building is calculated every year by assigning it the numerical value of the weighted average of the Uwall in the building stock, depending on the building envelope thermal refurbishment rates. Similarly, the system efficiencies of the heat generation units, depending on whether or not a boiler is replaced with a new unit that has a higher thermal efficiency using the same energy carrier (e.g. replacing an old oil-fired boiler with a new oilfired condensing boiler, or change the fuel and install a new natural gas condensing boiler). Finally, to account for new building constructions in the building stock model beyond 2020 and assess different refurbishment scenarios, it was necessary to consider NZEBs. In the absence of an official detailed NZEB definition in Greece at the time of this work (end-2015), apart from the general notion in N.4122/2013 along the lines of the EPBD recast, an envisioned KENAK+ concept was considered for the post-2021 era. The main characteristics are presented in [21,22]. Accordingly, different building modernization levels are defined for each of the 24 building types included in the building stock model. For the building envelope, four possible thermal insulation levels are considered, namely: • Level ‘0’: L0 – No thermal insulation; • Level ‘1’: L1 – Insulation according to HBTIR; • Level ‘2’: L2 – Insulation according to the current regulation standards (KENAK);

• Level ‘3’: L3 – Advanced thermal insulation levels to comply with the envisioned KENAK+ concept. For the main space heat production systems in each climate zone and construction period, the levels are defined according to the different energy carriers existing in the residential building stock. Specifically the oil, natural gas and electricity systems were classified into three levels based on currently available technologies, namely: • Level ‘0’: L0 – Conventional low efficiency systems (e.g. noncondensing boilers, old heat pumps, stoves, open fire, portable heating units); • Level ‘1’: L1 – Modern systems installed in new buildings according to the current market trends (e.g. condensing boilers, high temperature high performance heat pumps); • Level ‘2’: L2 – High performance systems, cutting edge technologies that are envisioned to meet future standards (e.g. high performance oil or natural gas heaters/boilers and low temperature high efficiency heat pumps combined with subfloor systems for space heating). • Level ‘1’ and level ‘2’ systems are considered either independently or coupled with solar panels to cover 100% of the energy demand for DHW and part of the space heating demand, if possible. Finally, for the DHW systems, three levels are considered based on the contribution of renewables in the heat production, namely: • Level ‘0’: L0 – Conventional systems (no solar panels or with 2.5 m2 of solar panels per dwelling); • Level ‘1’: L1 – Solar to cover 60% of DHW demand and the rest covered by high performance systems, with auxiliary energy provided by the Level ‘1’ main space heating system; • Level ‘2’: L2 – Solar to cover 100% of DHW demand and part of the space heating, where possible, with auxiliary energy provided by the Level ‘2’ main space heating system. 2.2. Hellenic residential building stock According to the most recent national Census data [3], the total number of exclusive-use residential buildings is ∼2.99 million buildings and 6.4 million dwellings, of which 4.1 million dwellings are inhabited. The gross floor area is about 480·106 m2 , of which it is estimated that ∼400 × 106 m2 are inhabited (Table 2). Over 70% of the residential buildings are SFH, while ∼55% of the total dwellings are located in SFH and the rest in apartment buildings (MFH). Although the heating degree-days range from 600 HDD in the south to over 2600 HDD in the northern parts of Greece, about half

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of the Hellenic buildings have no kind of thermal protection, since the majority of them (i.e. about 58% from the ‘old’ building stock) were built prior to 1980. In particular, based on the construction periods of the Hellenic building stock 41.2% of the buildings were built before 1970, 17.2% during the 1970s, 17.5% during 1980s, 12.5% during the 1990s and the remaining after 2001 [3]. The ageing building stock constitutes a grim reality and implies that the majority of Hellenic dwellings will need some kind of refurbishment to the thermal envelope and their installations to meet the new energy efficiency standards for buildings. The energy-related characteristics of the building envelope and system installations of the residential building stock are derived from a detailed analysis of the raw data from a recent national survey [4]. The information is then used to populate the different building classes of the typology. Modernization efforts to upgrade the buildings’ thermal envelope of the ‘old’ building stock have been limited. Only 9% of the walls, 22% of the roofs and 33% of the windows of the pre-1980 building stock have been refurbished to upgrade their envelope insulation levels to comply with HBTIR. This translates to a very slow envelope annual modernization trend of less than 1%. Double glazing is a common practice in new construction and the most popular EEM in existing buildings, encountered in about 43% of the dwelling stock, since this is the easiest envelope refurbishment that not only reduces heat loses but also improves sound proofing, safety, and aesthetics. Adding roof insulation is easier and popular in SFH, but it is not common in MFH since it is effective for the last floor apartments and it is difficult to have consensus in the multi-floor-owner buildings. The most demanding action is the installation of wall thermal insulation that is usually implemented only during deep energy renovations. The main fuel source for space heating is heating-oil (63.8%), while 12.4% uses electricity, 12% biomass and 8.7% natural gas [4]. The most common heat supply systems are boilers (69%, liquid fuels), followed by heat pumps (5%). Other heat supply systems include direct electric (7%), stoves (4%) and open fireplaces (4%). District heating is mainly used in the north (climate zone D) and represents 0.73% of the total space heating systems in the country. DHW production is dominated by the use of simple electric storage heaters (62%), followed by the use of solar collectors (37.6%), boilers (30% oil, 4% natural gas), while 25.2% use the central heating system. A total of 59% of the installed oil boilers are old (noncondensing) and 22% of the heat pumps are split units or systems aged over 10 years. The EU efforts to improve the energy efficiency of products, including the heat production systems and equipment, through the Ecodesign and energy labelling, are expected to change the heat generation system characteristics. The use of higher efficiency new heating systems and the switch to other energy carriers (e.g. natural gas or renewables) are rising throughout the EU-28, with an increasing penetration of more efficient heating systems, such as gas condensing boilers and heat pumps [2]. Already, The Netherlands has the highest penetration rate (above 70% of the dwelling stock), while the UK has also experienced a very large penetration from 3% in 2000 to 40% now. For the use of heat pumps, Italy is leading (penetration above 60%), followed by Sweden and Finland (around 20%). The new building activity in the building stock model is set at an average of 0.5% per annum, although the current construction activity has practically stalled due to the deep economic recession. This slowdown in new buildings’ construction activity is also observed throughout the EU-28, thus limiting the relative impact of higher energy performance new dwellings on the total building stock. For example, over the 2000–2012 period, the EU-28 annual new dwelling construction rate averaged about 1.1% of the dwelling stock [2]. In recent years, this has dropped to 0.8% of the dwelling stock and below 0.5% in several EU Member States.

In the Hellenic building stock model, new buildings comply with the requirements of KENAK up to 2020 and thereafter they are constructed according to the KENAK+ concept. Finally, the demolition rate is set at 0.17%, based on the analysis of national building construction activity data for the number of demolitions during the past decade. The base year that defines a coherent building stock model is set at and compared with data for 2012 (i.e. the year that defines the current state). This was the most recent period with available data for all relevant parameters (e.g. for the existing building stock, officially reported energy use and emissions from different sectors) at the time of the study. The evolution of the building stock over the years takes into account constant annual demolition, construction and refurbishment rates, over the entire period of interest. 2.3. Calculations & adaptation factors The calculations are performed using the official national software TEE-KENAK, developed by the National Observatory of Athens for the Technical Chamber of Greece (TEE), to support the implementation of KENAK and issue EPCs in Greece. The calculation engine is in accordance to the European standards with the main calculation procedure of the building energy demand estimated using the quasi-steady state monthly method. The relevant national technical libraries, weather data and other technical specifications are specified in four supporting technical guidelines [20]. The commonly used assumptions and predefined values for the normative calculations in the case of residential buildings include continuous operation (18 h/day, 365 days/year) with specific heating periods in different climate zones (e.g. from November to mid-April in the south and from mid-October to April in the north of the country), operating at a set-point temperature of 20 ◦ C (accounting for thermostatic controls), fixed values for the DHW demand (e.g. 27.38 m3 /bedroom at 45 ◦ C), the occupancy and internal heat gains [6]. For each annual calculation, over 960 input files are generated by combining all 24 building types with the different space heating systems, DHW systems and energy carriers that are fed in the calculation engine (Fig. 2). The technical characteristics of the typical buildings change each year, by redefining the U-values, system efficiency and energy carriers, depending on the different modernization scenarios and EEMs. The outputs include the annual total energy demand, final energy consumption and CO2 emissions per unit floor area for space heating and DHW, along with the energy carriers. The annual calculations are repeated for all building types, on an annual basis over the 2012–2030 period. The next step is to close the gap between calculated and actual energy use, in order to facilitate the process of assessing the energy performance of a building stock. Beyond the well-established procedures for improving the accuracy of normative calculations by calibrating the estimates with data from building energy monitoring, using accurate simulation tools, there may still be significant input uncertainties and output discrepancies. Furthermore, the issue at hand is how to adapt predictions from specific calculation tools, like in the case of TEE-KENAK in Greece, in order to obtain more realistic estimates. This is not an attempt to test the tool’s accuracy, but rather to implement a systematic and reproducible approach for adapting the outputs for more realistic estimates of actual energy use or for assessing energy savings from different EEMs. A two-step approach that exploits available information from EPCs and collects new data through manageable short field surveys is one practical approach [23] that is implemented in this work. The derivation of the first adaptation factors is based on the exploitation of data from energy performance certificates (EPCs). In line with

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the EPBD mandates, over 650,000 EPCs have been issued in Greece, when buildings or building units are sold or rented out for the first time to a new tenant. The available data from the national registry of EPCs (buildingcert) constitutes a valuable resource for gaining an insight on the energy performance of existing buildings. Residential buildings or building units account for ∼85% of the issued EPCs and they are dominated by the lowest energy-class label, e.g. 34% are ranked at an energy-class G, while only 3% are ranked at a Bclass or higher. The average calculated total primary energy use is 261.6 kWh/m2 , while the CO2 emissions reach 70.3 kgCO2 /m2 . The EPCs provide the values of the calculated primary energy use and some of them also include the actual electrical and thermal final energy consumption, since this is optional information. Processing the information from EPCs it was possible to derive empirical adaptation factors f1 (actual/calculated) organized in the 24 building types, using ∼12,000 raw data to derive (f1 *) and ∼8000 filtered data for (f1 **). The detailed methodology and data analysis for deriving the factors is elaborated in [23]. The average ratios based on the raw data (f1 *) range from 0.90 for SFH (i.e. 10% lower energy use than calculated) to 1.42 for MFH (i.e. 42% higher energy consumption than calculated). Using the screened data (f1 **) they range from 0.54 for SFH to 0.57 for MFH (i.e. 46% or 43% lower actual energy consumption than calculated). These factors are used as multipliers for correcting the calculated values (Fig. 2) for each building type. An upper bound is obtained using f1 * and an average bound using f1 ** for approaching the general trend of actual energy consumption. Overall, higher calculated values correspond to lower actual energy use. Results from other European studies report that actual energy use for heating is up to an average of 30% less than calculated [24–26]. The derived average ratios are presented in Table 3 for the 24 building types in the Hellenic building matrix. The empty cells denote missing information for some specific building types in the available database, i.e. no EPCs are currently available that include actual energy consumption. In addition, for some of them (e.g. recent constructions) there is not enough data at this stage, so one would expect that for these specific building types there is low confidence in the derived factors. Moreover, the currently available database is dominated with EPCs from MFH (i.e. 85% in the raw data or 83% in the filtered data) that are the most commonly issued certificates. For the time being, this ratio does not meticulously reflect the national average of MFH in the residential building stock. However, as the database is progressively enriched with EPCs that include actual energy use data from more building types (e.g. SFH and new construction periods), it will be possible to periodically update the corresponding empirical adaptation factors. The second step of the approach provided complementary data from field surveys of homeowners on current behavioural changes and trends in the use and operation of heating systems. The information was used to derive similar adaptation factors (f2 ) for adjusting the calculated values to account for the deviations from the standard conditions used in the normative calculations, e.g. lower hours of operation and indoor temperature settings, heating smaller floor areas of dwellings [23]. Given the limitations of this pilot action that reached out to only 210 dwellings, it was not possible to cover all building types at different climate zones (Table 3). The representative results are presented for two major construction periods (pre- and post-1980) of SFH and MFH. The f2 averages about 0.31 and is considered a lower bound (i.e. a conservative estimate of actual energy use). 2.4. Scenarios The Hellenic building stock model developed within EPISCOPE can be used to investigate the possibility to achieve the national CO2 emission reduction targets in 2020 and 2030. The scenarios

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consider different refurbishment rates and target the buildings’ envelope, systems, or both. The starting point is the trend scenario that follows the current standard (KENAK) till 2030, i.e. complying with the existing regulation on the energy performance of buildings. The envelope scenarios (E1 to E6) target the buildings’ thermal envelope and are more aggressive considering higher refurbishment rates according to KENAK till 2020 and the KENAK+ concept thereafter. The systems scenarios (S1 to S7) target heat generation systems with higher modernization in accordance to KENAK till 2020 and the KENAK+ concept thereafter. Specific characteristics of the various scenarios are elaborated next. The following subsections summarize and elaborate the four groups of scenarios considered during this study. A synoptic description of the scenarios is given in Table 4. 2.4.1. Trend scenario The trend scenario keeps the envelope and system modernization trends that are observed in the 2012 building stock (i.e. the year that defines the current state). An exhaustive search in published data did not reveal any official reports on modernization trends in the residential building stock. Consequently, the model was fed with values, which, for the trend scenario were carefully specified to reflect the prevailing trends in the Hellenic market based on an interpretation of the two recent ELSTAT national surveys on energy consumption in households (i.e. 2001 and 2011 surveys) and in occupants’ priorities regarding building refurbishment over the recent years collected during the EPISCOPE surveys. Accordingly, the annual envelope modernization rate is very low (0.56% per annum), involving lower values for annual wall insulation upgrade rate (0.10% per year) and higher values for annual window replacement with double glazing (1.00%). Similarly, the annual system modernization rates are also very low (0.66%) involving the replacement of old systems with new of the same fuel and the fuel change from oil to natural gas or electricity. Both envelope and system modernization imply an upgrade to KENAK standards (regulation requirements in 2012). 2.4.2. Envelope scenario The ‘envelope’ group includes scenarios that focus on the envelope refurbishment, keeping the system modernization rates at the level of the ‘trend’ scenario. Accordingly, the six scenarios included in the group involve annual envelope modernization of 3%, 4% and 5% of Level ‘0’ and Level ‘1’ components considering an upgrade to KENAK standards until 2020 and to KENAK+ standards thereafter till 2030 (scenarios E1, E3, E5) or to KENAK+ all the way from 2012 to 2030 (scenarios E2, E4, E6). As shown in Fig. 4 an increase in the annual modernization rate of the envelope results in significant improvement of the envelope quality in the building stock. 2.4.3. System scenarios The ‘systems’ group focusses on the modernization of the heat production systems, keeping the envelope refurbishment rates at the level of the ‘trend’ scenario. A total of twenty scenarios are grouped in three subgroups based on the modernization type and level that is considered for each one of them. The first and second subgroups involve system modernization maintaining the same energy carrier. Upgrades are at the level of KENAK standards (Level ‘1’) until 2020 and KENAK+ (Level ‘2’) standards from 2021 till 2030, with solar panels for DHW installed at an annual rate of 1%, 3%, 5% and 10% to cover 60% (scenarios S1-S4) or 100% (scenarios S1 1-S4 1) of the heating needs for DHW. The second subgroup (S1 2-S4 3) differs from the first one in that it considers solar heating as well. In both subgroups an intensive annual modernization rate (2.25%) is considered for the period before 2020 and a slower one (0.64%) thereafter. The average annual modernization rate for the period 2012–2030 is 1.24%. The third subgroup (S5–S7) has the

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Table 3 Average empirical factors for adapting the deviations of actual from calculated primary energy use for the different building types. The f1 factors are derived from the EPCs and the f2 from the field studies. The corresponding data population (N) is included in parentheses. Construction period

Climate zone

All Dwellings

f1 b (N)

f2 (N)

f1 a (N)

f1 b (N)

f2 (N)

f1 a (N)

f1 b (N)

f2 (N)

0.62 (1075) 0.57 (66) 0.69 (500) 0.59 (382) 0.48 (127)

0.50 (909) 0.53 (54) 0.52 (422) 0.51 (315) 0.44 (118)

0.28 (24)

0.95 (5196) 0.87 (213) 1.06 (3276) 0.75 (1386) 0.79 (321)

0.52 (4041) 0.55 (154) 0.51 (2482) 0.53 (1136) 0.54 (269)

0.33 (52)

0.89 (6271) 0.80 (279) 1.01 (3776) 0.71 (1768) 0.70 (448)

0.52 (4950) 0.55 (208) 0.51 (2904) 0.52 (1451) 0.51 (387)

0.31 (76)

A B C D

1.34 (700) 1.00 (101) 1.99 (295) 0.84 (227) 0.75 (77)

0.62 (500) 0.57 (135) 0.61 (196) 0.63 (166) 0.64 (70)

0.34 (30)

1.93 (4810) 1.72 (360) 2.49 (2660) 1.14 (1451) 1.09 (339)

0.63 (3067) 0.62 (213) 0.60 (1665) 0.68 (953) 0.62 (236)

0.31 (105)

1.85 (5510) 1.56 (461) 2.44 (2955) 1.10 (1678) 1.03 (416)

0.63 (3567) 0.61 (281) 0.60 (1861) 0.67 (1119) 0.62 (306)

0.32 (135)

A B C D

1.03 (7) 1.55 (3) 0.87 (2)

0.71 (5) 0.52 (2) 0.87 (2)

0.62 (19) 0.71 (6) 0.61 (11) 0.35 (2)

0.40 (2) 0.90 (1782)

0.79 (1) 0.54 (1414)

2.64 (36) 0.66 (9) 3.57 (21) 2.37 (5) 2.38 (1) 1.42 (10042)

2.38 (43) 0.88 (12) 3.33 (23) 2.37 (5) 1.06 (3) 1.35 (11824)

0.64 (24) 0.66 (8) 0.65 (13) 0.35 (2) 0.79 (1) 0.56 (8541)

1981–2010

post-2011 A B C D All data b

Multi-family houses (MFH)

f1 a (N) pre-1980

a

Single-family houses (SFH)

0.32 (54)

0.57 (7127)

0.32 (157)

0.31 (211)

Using the raw data. Using the screened data.

Table 4 Overview of the different scenarios for the envelope, space heating and domestic hot water systems. Envelope Annual refurbishment rate (%)

Space heating Upgrade level (to 2020/2021–2030)

Annual modernization rate (same fuel & fuel change)total (to 2020/2021–2030) (%)

DHW Upgrade level (to 2020/2021–2030)

Solar Heating

Solar panels for DHW

Coverage of DHW demand (%) 60

L2

0.66

L1

No

Annual penetration rate (%) 1

Envelope scenarios (E#) 3.00 E1 3.00 E2 E3 4.00 E4 4.00 E5 5.00 5.00 E6

L2/L3 L3 L2/L3 L3 L2/L3 L3

0.66 0.66 0.66 0.66 0.66 0.66

L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2

No No No No No No

1 1 1 1 1 1

60 60 60 60 60 60

System scenarios (S#) 0.56 S1 S2 0.56 0.56 S3 0.56 S4 0.56 S1 1 0.56 S2 1 S3 1 0.56 0.56 S4 1 0.56 S1 2 0.56 S2 2 0.56 S3 2 0.56 S4 2 0.56 S1 3 0.56 S2 3 0.56 S3 3 0.56 S4 3 0.56 S5 0.56 S6 0.56 S6 1 0.56 S7

L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2 L2

2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 2.25/0.64 1.06a 1.06a 1.06a 1.06a

L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2 L1/L2

No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

1 3 5 10 1 3 5 10 1 3 5 10 1 3 5 10 1 5 5 10

60 60 60 60 100 100 100 100 60 60 60 60 100 100 100 100 60 60 100 100

Combined scenarios (C#) C1 3.09 C2 3.61

L2/L3 L2/L3

2.27/0.47 1.15a

L1/L2 L1/L2

No Yes

10 10

100 100

TREND

a

0.56

Change to other energy carriers (i.e. oil to natural gas or electricity).

same basic characteristics as the second one; however, the main difference is that it considers fuel switch at a fixed annual rate of 1.06%.

Fig. 5a illustrates the final energy use for the trend and selected system scenarios for different landmark years. These representative snap shots may be used to monitor the time evolution trends of dif-

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Fig. 4. Envelope scenarios. (a) Percent of old (pre-1980) building stock refurbished; the percentages indicate the annual envelope modernization rates for the trend and the corresponding envelope scenarios elaborated in Table 4. (b) Old building stock: Breakdown per insulation level for windows in 2030; the base case (2012) is included for reference purposes.

ferent energy carriers. Fig. 5b illustrates the impact of solar systems on the total savings achieved by modernization of the heat production systems. Scenarios with larger exploitation of solar energy, such as the ones where solar heating is adopted, lead to higher energy savings. In the scenarios included in this work the contribution of solar systems to the final energy consumption does not exceed 30% in 2030. 2.4.4. Combined scenarios The ‘combined’ group includes two exemplary scenarios combining the features of the ‘envelope’ and ‘systems’ subgroups at moderate rates for envelope and system upgrade. Scenario C2 considers solar heating and possible changes to other energy carriers (i.e. fuel switch from oil to natural gas in climate zones B and C, where the main distribution network is available and to electricity in climate zone A). The envelope refurbishment rates are slightly

higher in scenario C2 whereas the system modernization rate in the period 2012–2020 considered in scenario C1 is nearly double the corresponding rate considered in scenario C2. As the annual modernization rate in scenario C1 drops down to 0.47% in the period after 2020, the difference in the average annual rate considered by the two scenarios for the period 2012–2030 is only 0.12%. Fig. 6 illustrates the annual evolution of the main energy carriers in the building stock, expressed as a percentage of buildings using a specific energy carrier over the total number of buildings, derived by the two scenarios for the period 2012–2030. As expected, scenario C2 leads to a ‘greener’ fuel mix in the final consumption towards 2030 with a clear increase in the share of natural gas. 2.4.5. Common features The scenarios have some common considerations: (a) Demolition rate: 0.17% per annum; New construction rate: 0.50% per

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Fig. 5. System scenarios. (a) Breakdown of final energy use in 2015, 2020 and 2030 for different energy carriers (i.e. OIL: heating oil, NG: natural gas, DH: district heating, ELE: electricity, WOOD: firewood) for the building stock. The base case (2012) is included for reference purposes; the trend and the corresponding system scenarios (e.g. S4) are elaborated in Table 4. (b) Annual share of final energy covered by solar systems; the base case (2012) is included for reference purposes.

annum; (b) Envelope refurbishment is applied to Level ‘0’ (noninsulated) and Level ‘1’ (insufficiently insulated in accordance to HBTIR)envelope components; (c) Floors are not modernized (e.g. floor thermal insulation is not included in the measures); (d) System modernization is applied to Level ‘0’ systems (pre-1980) including aged non-condensing oil boilers, split units and heat

pumps; (e) Only central systems using oil or electricity are modernized, i.e. the system modernization scheme does not include local units (e.g. stoves, direct electric or open firewood systems); (f) Fuel change from oil to natural gas applies only in climate zones B and C, where the main natural gas distribution network is available; (g) District heating is applicable only in climate zone D. The carbon

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Fig. 6. Evolution of the main energy carriers (i.e. OIL: heating oil, NG: natural gas, DH: district heating, ELE: electricity, WOOD: firewood) for the building stock. (a) Combined scenario C1. (b) Combined scenario C2. The base case (2012) is included for reference purposes; the combined scenarios are elaborated in Table 4.

emissions are estimated using the national conversion factors from KENAK, i.e. 0.989 kgCO2 /kWh for electricity, 0.264 kgCO2 /kWh for thermal energy production from oil, 0.196 kgCO2 /kWh from natural gas and 0.347 kgCO2 /kWh from district heating. 2.5. National targets Final energy use in Hellenic residential buildings reached 5.04 Mtoe in 2012 (base year) or 29.4% of the total [1]. According to the national energy efficiency action plan [7], the 2014–2020 cumula-

tive energy savings target is set at 3.33 Mtoe or approximately 19.3% of the total final energy consumption in 2012, with total new annual savings equal to 902.1 ktoe in 2020. The building sector is expected to contribute 58% towards achieving the energy savings targets. For residential buildings, where most policy measures are applied, the accumulated energy savings for the period 2014–2020 are estimated at 1932 ktoe, while the annual final energy savings in 2020 are expected to reach 523 ktoe. The Energy Efficiency Directive (EED 2012/27/EU) was transposed in to national law (N.4342/2015) in early-November 2015. However, its full implementation will prob-

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ably be further delayed, considering the struggle for developing the necessary ministerial decisions, regulations, administrative provisions and supporting tools. The participation of renewables in the final energy consumption for heating and cooling by 2020 is specified at 20% according to the transposition of the European Directive on renewables (RED 2009/28/EC) by national law (N.3851/2010). For 2030, the national targets were not yet defined at the time of this work and were therefore adopted from the EU-28 plan for 2030. Finally, the targets for the abatement of CO2 emissions in the domestic sector for 2020 and 2030 were assumed at 20% and 40% lower than the 1990 emissions (i.e. 6.4 Mt for residential combustion and share of electricity generation for DHW) in line with the EU energy strategies. Accordingly, the national targets for space heating and DHW in the residential sector are set at 5.1 Mt CO2 for 2020 and 3.8 Mt CO2 for 2030, with final heating energy use compared to 2012 set at 3.28 Mtoe for 2020 and 1.49 Mtoe for 2030. 3. Results and discussion The following discussion presents the main results from this study. The first part compares the model predictions against officially reported data for the 2012 base year. As an additional comparison, the recently released official data for the 2013 final energy use is also included; the results build confidence on the relative accuracy of the proposed model to capture the actual trends. The second part elaborates the results obtained from the proposed model using different envelope, system and combined scenarios to estimate the annual heating energy and CO2 savings towards the 2020 and 2030 national targets. 3.1. Validation The approach and the current state of the building stock model were used to generate results for the 2012 base year. This was the year with the latest officially published data at the time of this study. The relevant information is illustrated in Fig. 7. From the national energy balance sheets [28], it is deduced that the final energy use for heating is about 3.4 Mtoe. The building stock model results for occupied dwellings provide an estimate of 7.8 Mtoe using the upper bound (f1 *), 4.6 Mtoe using the average bound (f1 **) and 2.3 Mtoe using the lower bound (f2 ) adaptation factors. The estimated CO2 emissions for the 2012 base year range from 21.9 Mt using the upper bound (f1 *) adaptation, 11.4 Mt using the average bound (f1 **) and 6.3 Mt using the lower bound (f2 ). The officially reported value in 2012 for the emissions from residential combustion is 6.9 Mt CO2 [27], while the additional emissions from the use of electricity for DHW and space heating in the residential sector are estimated at 2.5 Mt CO2 . Accordingly, the reported total emissions for heating amount to about 9.4 Mt CO2 . As shown in Fig. 7, the value is bracketed by the building stock model results for occupied dwellings that have been corrected with the adaptation factors (f1 **) that serve as an average in the general trend of actual energy use and the results using the (f2 ) factors that serve as a conservative estimate. Following the completion of the work, the official Eurostat data for 2013 were published and are also included in Fig. 7. The available data includes the final energy consumption for the different enduses, but the breakdown of the CO2 emissions was not available at the time of this publication. The approach using the lower bound adaptation factors appear to capture the current dropping trend of actual final heating energy use in Hellenic dwellings. The findings give confidence that the overall method and results resemble with relative good accuracy the actual energy use and resulting emissions for 2012 and 2013. The observed differences

between the calculated and officially reported values indicate that the latter lie between the model calculations corrected with the adaptation factors f1 ** and f2 . This is anticipated by the fact that f1 ** reflects the average bound in the general trend of actual energy use, while the f1 * adapted energy consumption values can be considered as an upper bound reflecting a possible future trend as the country moves out of recession. On the other hand, f2 reflects recent behavioural changes under the adverse economic conditions and the recession in Greece; therefore, the estimated actual energy consumption may be considered as a lower bound (using f2 ), providing a conservative estimate of actual energy use in existing dwellings, as a result of occupant’s efforts to cut-down heating energy costs. For practical illustration purposes, the results and analysis in the following sections for the elaboration of different scenarios, are provided using the numerical average of the results obtained from using the f1 ** (average bound) and f2 (lower bound) adaptation factors. This appears to be more representative of the current situation in Greece as well as for the general trend towards 2020 and onwards, as a realistic near term scheme for the evolution of the energy use in Hellenic dwellings. However, at the time that there will be a reactivation of the economy that would drive a notable change in domestic energy use, then the method offers the option of using the upper bound factors to adjust the estimations and reconsider the effectiveness of the scenarios. 3.2. Emissions and energy use in 2020 & 2030 The approach to obtain more realistic estimates is based on multiplying the model predictions for each building type by the average value of the corresponding f1 ** and f2 adaptation factors that capture the combined impact of the different intensities for utilization and user behaviours. Fig. 8 depicts the evolution of the calculated CO2 emissions from the Hellenic residential building stock for the period 2012–2030. From the comparative presentation of the envelope and system scenarios it is observed that the target of 2020 is not met. Further increase of the modernization rates considered in this study could improve the performance of the scenarios. Since the reduction of the heating demand is essential in achieving significant energy savings it is expected that the envelope modernization scenarios show a greater potential for reaching the target of CO2 in 2030. However, even with E6 that is the most promising scenario, the calculated CO2 emissions in 2030 fall short of the target by approximately 8%. Furthermore, the envelope refurbishment rate for this scenario is very high, resulting in a total of 93% of the old building stock that should be refurbished by 2030, which is a rather over ambitious envelope refurbishment rate to be attained in practice. Fig. 9 illustrates the scenario analysis results for scenarios C1 and C2. Both scenarios succeed in meeting the national final energy targets in 2020, but fail to meet the corresponding CO2 emissions target. This can be attributed to the fact that both scenarios consider a moderate envelope refurbishment rates that, by 2020, reduce the heating energy demand and final energy consumption to a much lower level than the target value. However, in order to meet the corresponding CO2 target, emphasis should be towards a fuel change to natural gas combined with solar heating. Scenario C2 incorporates this type of actions. A higher annual system modernization rate in the short-term period would be required for both scenarios to meet the CO2 target in 2020. The moderate annual rate of 1.27% adopted in scenario C1, according to which a total of 62% of the old building stock will be refurbished, is sufficient for meeting the CO2 emissions target in 2030. However, the national final energy target will only be met by scenario C2 that increases the share of solar systems to the total final energy consumption compared to that of scenario C1. Accordingly, by 2030, the total final energy consumption to be covered

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Fig. 7. Estimated (a) final energy consumption for heating and (b) CO2 emissions of the Hellenic residential building stock and the officially reported values for the base year 2012 and for 2013, when available.

by solar systems is estimated at 27% and 40% for scenarios C1 and C2, respectively. It is evident that for both CO2 and final energy national targets to be met appropriate building refurbishment and system modernization rates should be combined with the introduction of ‘green’ technologies among which solar systems will be a key player. A software tool was also developed to facilitate the manipulation of input and output data. A navigator allows the user to select specific building types or make global changes to the entire building stock model, for updating the input data. A multi-parametric visualization tool has also been prepared to support the overview and screening process of the results during the decision making process. The application facilitates the analysis and exploitation of the results for identifying the most effective strategies and moni-

toring progress at regional and national level. The tool will also be adapted to handle different annual refurbishment rates over the calculation periods. To further strengthen the flexibility and future updates of the tool, it will be interesting to investigate the option of incorporating an automated process for periodically updating the adaptation factors. For example, as more data becomes available on the national registry of EPCs that include actual energy consumption, they could be used to update the derived empirical adaptation factors (e.g. f1 **) as elaborated in [23]. New data from the EPCs would also be necessary for populating building types that are currently based on a limited number of cases (e.g. corresponding to new construction periods). Similarly, the periodic derivation of updated values for the lower bound adaptation factors (f2 ) that capture current

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Fig. 8. Individual scenario analysis results. Evolution of CO2 emissions for (a) envelope scenarios (E1–E6), and (b) system scenarios (S1–S7). The scenarios are elaborated in Table 4. The bullets denote the base case (2012) value (grey) as officially reported in Eurostat and the targets (red) for 2020 and 2030. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

behavioural changes and trends in the use and operation of heating systems would also be necessary. This data would reflect new trends in the actual use of heating systems and deviations from the

standard conditions assumed in the normative calculations (e.g. operating hours of heating systems, heated floor area and indoor temperature settings) and extended to cover all building types.

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Fig. 9. Combined scenario analysis results. Evolution of (a) CO2 emissions, and (b) final energy consumption, calculated for the trend and the two combined scenarios (C1 and C2). The scenarios are elaborated in Table 4. The bullets denote the base case (2012) value (grey) and the targets (red) for 2020 and 2030. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

This effort could become part of the annual surveys conducted by ELSTAT (e.g. “Household Budget Survey” or “Statistics of Income and Living Conditions”), by integrating a few relevant short items (questions) in the official survey structure. Finally, the most important item to consider is addressing the financial issues and the capital required for different EEMs and

scenarios. As a first step in this direction, currently available is a relevant study of case studies for representative buildings that include a first estimate of the refurbishment costs for different scenarios or alternative (higher performance) new constructions [22]. Financing such a large scale effort is a critical parameter for owners and pol-

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icy makers that will need to consider diverse and flexible financing tools.

4. Conclusions The conceptual framework of this work was based on the national TABULA residential building typology that was tied to Census and statistical data to set up the Hellenic residential buildings stock model. The implemented conceptual approach provides realistic estimates of actual heating energy use by the residential building stock and allows a practical assessment of energy savings from different EEMs and scenarios. Based on the results from this pilot study, the 2030 targets for CO2 emissions and final energy consumption are reached by applying the scenario C2 that has a refurbishment rate of 3.6% for thermal improvement of the envelope and 1.15% for improvement of the systems’ efficiency to minimize heat demand and promotes the use of solar energy systems for DHW and solar heating together with a gradual fuel change from oil to natural gas. As a result, at the end of the period 2012–2030 solar systems cover 40% of the final energy in 2030 and the share of natural gas in the mix of energy carriers covering the remaining heating energy demand is twice as high as the corresponding current value. Key to the future success is the minimization of heating demand, use of high efficiency equipment and systems, coupled with central solar assisted systems and potentially solar thermal assisted cooling or PV driven heat pumps. To lower the CO2 emissions it is necessary to switch from oil burning heat production technologies towards natural gas boilers and electrical heat pumps. However, turning to electricity for heating, needs to advance with caution in order to minimize a negative impact on power capacity of the grid, especially in the islands served by limited autonomous power plants. Given the fact that this study did not look into decarbonisation of central power generation, on-site or nearby building green power generation (e.g. PV or CHP) additional savings could be achieved as a result of lower emissions for electricity use. Reaching the 2020 target while securing proper indoor environmental quality, will need aggressive refurbishment rates that may be difficult to implement, given the unprecedented economic crisis and continuing recession in Greece. The current dropping trend of energy use is evident but as a result of the efforts by people to cut-down heating energy costs. Higher energy prices (e.g. imposing a fuel tax on heating oil in 2012) significantly decreased oil consumption in the residential sector by 70%. Side effects resulted to poor indoor thermal conditions and unprecedented environmental impacts in major urban cities as a result of using open fireplaces and burning improper solid fuels. However, given the recent trends and staggering drop in use of conventional energy carriers for space heating due to family budget constraints, it may be possible to actually surpass the 2020 target as the economy continues to stumble. The Hellenic residential building stock model requires input data regarding the modernization trend and rates of refurbishment for different envelope components and heating systems at various modernization levels. The structure of the developed model permits easy future updates of the current input data. It can also be used for sensitivity analysis in order to assess a sufficiently large number of scenarios to derive the optimum combination of modernization rates that must be included in a realistic energy efficiency action plan to meet the national targets related to CO2 reduction. The beta version of the application program has managed to overcome some of the computational complexities and facilitates the user in handling the vast amount of generated outputs. Variable inputs will be used to reflect the state and trends for each of the different building types that are included in the model. The cost

of refurbishment scenarios will also have to be taken into consideration, for a more holistic assessment of the alternatives. Finally, an automated sensitivity analysis will be incorporated in the tool for handling the computational complexities resulting from the study of numerous scenarios, using variable steps for each parameter. Selecting proper EEMs and assessing their effectiveness with accurate estimates of the anticipated energy savings will play a critical role in short- and long-term projections. Certain rebound in energy use can be expected in the near future as the Hellenic economy recovers and building occupants start again to be more concerned with maintaining a comfortable indoor environment in their dwellings. Accordingly, the derived empirical adaptation factors will have to be periodically updated. For example, at the time when the EPC registry is populated with new certificates that include actual energy use information for some building types that are currently missing or the available data population is low (e.g. especially for SFH). Additional insight is expected to be gained once the inspections of heating and air-conditioning systems finally move to full-scale implementation. According to N.4122/2013, the initial round of inspections should be completed by early 2017, although this may be too optimistic. In any event, this kind of detailed information that will progressively become available, could be used to improve the assumptions and the breakdown of the statistical data that do not have the desirable accuracy for the different building types; i.e. good for national averages but not recommended for different construction periods around the different climate zones. Although this building stock model and overall process was performed based on data from Greece, the streamline approach and the specific stages can also be adapted in other European countries. The building typologies are already available for 20 EU member states, while the derivation of the empirical adaptation factors from national EPC registries can become a straight-forward process.

Acknowledgments The national EPC registry (www.buildingcert.gr) has been developed and is maintained by the Hellenic Ministry of Environment, Energy and Climate Change – YPEKA (currently Hellenic Ministry of Environment & Energy) in collaboration with the Centre for Renewable Energy Sources (CRES). YPEKA is thankfully acknowledged for allowing access to the national EPC database. The analysis performed using the EPC data does not necessarily reflect the opinion of the Ministry. The European project EPISCOPE – Energy Performance Indicator Tracking Schemes for the Continuous Optimisation of Refurbishment Processes in European Housing Stocks (http:// episcope.eu) was partly financed by the European Commission (Executive Agency for Competitiveness and Innovation – EACI, EE/12/695/SI2.644739). The EPISCOPE project was a collaborative effort of 17 European organizations and was coordinated by Ms Britta Stein, IWU – Institut Wohnen und Umwelt GmbH, Germany. The content of this publication does not necessarily reflect the opinion of the European Union. Neither the EASME nor the European Commission is responsible for any use that may be made of the information contained herein.

References [1] EU Energy in Figures – Statistical Pocketbook 2015 edition, Brussels: European Commission. Available online: https://ec.europa.eu/energy/en/ statistics/energy-statistical-pocketbook. [2] L. Gynther, B. Lapillonne, K. Pollier, Energy Efficiency Trends and Policies in the Household and Tertiary Sectors – An Analysis Based on the ODYSSEE and MURE Databases, June 2015. Available online: http://www.odyssee-mure.eu/ publications/br/energy-efficiency-trends-policies-buildings.pdf.

Please cite this article in press as: E.G. Dascalaki, et al., Modeling energy refurbishment scenarios for the Hellenic residential building stock towards the 2020 & 2030 targets, Energy Buildings (2016), http://dx.doi.org/10.1016/j.enbuild.2016.06.003

G Model ENB-6738; No. of Pages 17

ARTICLE IN PRESS E.G. Dascalaki et al. / Energy and Buildings xxx (2016) xxx–xxx

[3] ELSTAT, Buildings Census, Athens: Hellenic Statistical Authority, 2015, 2011, Available on line: http://www.statistics.gr/census-buildings-2011. [4] ELSTAT, Survey on Energy Consumption in Households 2011–2012, 2013, Available on line: http://www.statistics.gr/statistics/-/publication/SFA40/. [5] C.A. Balaras, A.G. Gaglia, E. Georgopoulou, S. Mirasgedis, Y. Sarafidis, D.P. Lalas, European residential buildings and empirical assessment of the hellenic building stock, energy consumption emissions & potential energy savings, Build. Environ. 42 (2007) 1298–1314. [6] K.G. Droutsa, S. Kontoyiannidis, E.G. Dascalaki, C.A. Balaras, Ranking cost effective energy conservation measures for heating in hellenic residential buildings, Energy Build. 65 (2014) 318–332. [7] YPEKA (2014) Long Term Strategy Report mobilizing investments in the renovation of residential and commercial buildings, public and private, of the national building stock, Pursuant to Article 4 of Directive 2012/27/EU, Athens: Hellenic Ministry of Environment, Energy and Climatic Change, December 2014. Available online (in Greek): http://ec.europa.eu/energy/en/topics/ energy-efficiency/energy-efficiency-directive/national-energy-efficiencyaction-plans. [8] YPEKA (2014) Long Term Strategy Report mobilizing investments in the renovation of residential and commercial buildings, public and private, of the national building stock, Pursuant to Article 4 of Directive 2012/27/EU, Athens: Hellenic Ministry of Environment, Energy and Climatic Change, December 2014. Available online (in Greek): http://www.ypeka.gr/LinkClick. aspx?fileticket=vDjk62bRxSI%3d&tabid=282&language=el-GR. [9] T. Loga, N. Diefenbach, Monitor progress towards climate targets in European housing stocks-Main results of the EPISCOPE project, EPISCOPE Final project report D1.2, March 2016. Available online: http://episcope.eu/fileadmin/ episcope/public/docs/reports/EPISCOPE FinalReport.pdf. [10] G.V. Fracastoro, M. Serraino, A methodology for assessing the energy performance of large scale building stocks and possible applications, Energy Build. 43 (2011) 844–852. [11] U. Eicker, E. Demir, D. Gürlich, Strategies for cost efficient refurbishment and solar energy integration in European Case Study buildings, Energy Build. 102 (2015) 237–249. [12] G.M. Mauro, M. Hamdy, G.P. Vanoli, N. Bianco, J.L.M. Hensen, A new methodology for investigating the cost-optimality of energy retrofitting a building category, Energy Build. 107 (2015) 456–478. [13] E.G. Dascalaki, K.G. Droutsa, C.A. Balaras, S. Kontoyiannidis, Building typologies as a tool for assessing the energy performance of residential buildings – a case study for the hellenic building stock, Energy Build. 43 (2011) 3400–3409. [14] S. Hrabovszky-Horváth, T. Pálvölgyi, T. Csoknyai, A. Talamon, Generalized residential building typology for urban climate change mitigation and adaptation strategies: the case of Hungary, Energy Build. 62 (2013) 475–485. [15] I. Ballarini, S.P. Corgnati, V. Corrado, Use of reference buildings to assess the energy saving potentials of the residential building stock: the experience of TABULA project, Energy Policy 68 (2014) 273–284. [16] J. Kragh, K.B. Wittchen, Development of two Danish building typologies for residential buildings, Energy Build. 68 (2014) 79–86.

17

[17] F. Vásquez, A.N. Løvik, N.H. Sandberg, D.B. Müller, Dynamic type-cohort-time approach for the analysis of energy reductions strategies in the building stock, Energy Build. 111 (2016) 37–55. [18] T. Loga, N. Diefenbach, B. Stein, Typology approach for building stock energy assessment—main results of the TABULA project, TABULA Final Report, D2, October 2012. Available online: http://episcope.eu/fileadmin/tabula/public/ docs/report/TABULA FinalReport.pdf. [19] Guidelines accompanying Commission Delegated Regulation (EU), No 244/2012 of 16 January 2012 supplementing Directive 2010/31/EU of the European Parliament and of the Council on the Energy Performance of Buildings by Establishing a Comparative Methodology Framework for Calculating Cost-optimal Levels of Minimum Energy Performance Requirements for Buildings and Building Elements (2012/C 115/01), European Commission, 2012, Brussels, 2012, Available online http://eur-lex.europa.eu/ LexUriServ/LexUriServ.do?uri=OJ:L:2012:081:0018:0036:EN:PDF. [20] E.G. Dascalaki, C.A. Balaras, A.G. Gaglia, K.G. Droutsa, S. Kontoyiannidis, Energy performance of buildings – EPBD in Greece, Energy Policy 45 (2012) 469–477. [21] B. Stein, T. Loga, N. Diefenbach, Inclusion of New Buildings in Residential Building Typologies, EPISCOPE, project, D2.4 Synthesis Report SR1: Integration of Nearly Zero-Energy Building Standards in National Residential Building Typologies, October 2014. Available online: http://episcope.eu/fileadmin/ episcope/public/docs/reports/EPISCOPE SR1 NewBuildingsInTypologies.pdf. [22] E.G. Dascalaki, K.G., Droutsa, C.A., Balaras, S. Kontoyiannidis, Typology of Hellenic Residential Buildings – Energy conservation potential, EPISCOPE, project, D2.3b National Typology Brochures, March 2016. Available online (in Greek): http://episcope.eu/fileadmin/tabula/public/docs/brochure/GR TABULA TypologyBrochure NOA.pdf. [23] C.A. Balaras, E.G. Dascalaki, K.G. Droutsa, S. Kontoyiannidis, Empirical assessment of calculated and actual heating energy use in hellenic residential buildings, Appl. Energ. 164 (2016) 115–132. [24] M. Sunikka-Blank, R. Galvin, Introducing the prebound effect: the gap between performance and actual energy consumption, Build. Res. Inf. 40 (2012) 260–273, http://dx.doi.org/10.1080/09613218.2012.690952. [25] S.M.C. Magalhães, V.M.S. Leal, Characterization of thermal performance and nominal heating gap of the residential building stock using the EPBD-derived databases: the case of Portugal mainland, Energy Build. 70 (2014) 167–179. [26] G. Dall’O’, L. Sarto, N. Sanna, V. Tonetti, M. Ventura, On the use of an energy certification database to create indicators for energy planning purposes: application in northern Italy, Energy Policy 85 (2015) 207–217. [27] Country Factsheets, version 3.0, DG Energy, European Commission, Brussels, 2014, Available online: https://ec.europa.eu/energy/sites/ener/files/ documents/2014-country-factsheets.pdf. [28] Eurostat, Supply, Transformation, Consumption – Electricity – Annual Data, Online statistics database, Statistical office of the European Union, Luxembourg, 2015, Available online: http://ec.europa.eu/eurostat/data/ database.

Please cite this article in press as: E.G. Dascalaki, et al., Modeling energy refurbishment scenarios for the Hellenic residential building stock towards the 2020 & 2030 targets, Energy Buildings (2016), http://dx.doi.org/10.1016/j.enbuild.2016.06.003