COSTAS BALARAS

Costas Balaras is a mechanical engineer and holds a PhD from Georgia Tech. He is a research director at the Institute for Environmental Research & Sustainable Development (IERSD) at NOA in Athens, Greece. He is active in energy conservation, high performing buildings, sustainable cities, thermal and solar applications, building energy audits diagnosis and environmental impact assessments. He has participated in around 50 R&D and demonstration projects and was instrumental in the national adaptation of EPBD in Greece. He has published over 250 articles in journals, books and conference proceedings. He is a chartered engineer in Greece, an ASME Fellow and ASHRAE Fellow.

ELENA DASCALAKI

Elena Dascalaki is a building physicist and holds a PhD from the University of Athens. She is a senior researcher at the Institute for Environmental Research & Sustainable Development (IERSD) at NOA in Athens, Greece. She currently works on building typologies and building stock modelling, lifecycle analysis, building thermal simulations, and computational fluid dynamics. She has participated in over 35 R&D and demonstration projects and published over 130 articles in journals, books and conference proceedings.

Residential buildings in Greece account for 27.5% of the country’s total final energy use (Figure 1), and are responsible for 21.7% of total carbon dioxide emissions^[1]. Space heating (56.2%) and domestic hot water (DHW) (13.5%) are the most important end-uses^[2] . According to the latest national Buildings Census, there are ~3 million exclusive residential use buildings, representing ~79% of the building stock^[3]. The grim reality is that the vast majority lack proper thermal protection and have ageing heating, ventilation and air conditioning (HVAC) installations, failing to meet the new energy efficiency standards according to the national transposition of the EPBD^[4] mandates, KENAK^[5].

A bottom-up building stock model has been developed for Hellenic residential buildings, based on the national TABULA typologies for assessing energy conservation measures and quantifying savings from renovation scenarios6. However, the gap between calculated and actual energy use has long been recognised as a major hurdle for realistic assessments of building performance^[7].

'Residential buildings in Greece account for 27.5% of the country's total final energy use in 2017, and are responsible for 21.7% of the total carbon dioxide emissions'

To make more realistic estimates of actual energy use, heating energy consumption calculated by KENAK can be adapted using empirical factors derived from data included in energy performance certificates (EPC) or collected from simple behavioural occupant surveys.

Data from the Hellenic EPC repository^[8] was used to derive empirical adaptation factors, defined as the ratio of the specific actual (operational) energy use to the normative calculated (asset) final energy consumption from each building. Figure 2 illustrates the final energy use intensities (EUIs) for space heating and DHW derived from 1899 EPCs issued in 2011-2018. The large variations can be attributed in part to unique building characteristics, prevailing weather conditions, occupant behaviour and the deviation of actual operating conditions from the default values used in calculations.

'Moving forward, the big challenge is to improve the energy performance of our buildings while securing proper indoor environmental quality'

The average adaptation factor is 0.584 (i.e. 41.6% lower actual energy use than calculated). In general, higher calculated EUIs correspond to lower actual energy use, known as the ‘prebound’ effect. This is more evident for dwellings with a high calculated EUI (i.e. poor energy performance). This corresponds with published results of actual energy use ranging from 30% to 47% less than calculated space heating^[9].

'On the more important end of indoor comfort conditions, only half of the occupants manage to feel comfortable in their dwellings'

The opposite phenomenon is known as the ‘rebound’ effect, when actual energy use is higher than calculated, most notable in low-EUI dwellings (i.e. good energy performance). The values reported range from 36 % to 51 %. Periodically updated field surveys of homeowners in 278 dwellings reveal additional insights into behavioural changes and trends in the use of heating systems (Figure 3).

According to field data, only about 14.3% of singlefamily houses (SFHs) and 9.3% of multi-family houses (MFHs) have operating hours close to the assumed continuous heating (Fig. 3a). Distribution peaks around 3-4 and 5-6 hours per day in SFHs and MFHs respectively. About 69% of SFHs and 78% of MFHs operate their central heating for less than eight hours. Isolating some rooms is another common practice by homeowners for reducing energy costs (Fig. 3b). Only 38% of SFHs and 44% of MFHs heat their entire dwelling. A notable trend revealing the impact of the recent recession in Greece and of high heating oil prices (through taxes) is that 26% of MFHs have turned off their central heating systems, and over 16% of SFHs. Lowering the temperature is another common way to reduce heating costs, even at the expense of thermal comfort. Only 25% of the occupants of SFHs and 19% in MFHs reported an average temperature setting of 20 oC (Fig. 3c), the indoor set-point used in normative calculations. The derived adaptation factors that address these deviations are 0.40 for heating operating hours, 0.89 for reduced heated floor areas and 0.86 for indoor temperature. These factors can be used as multipliers to obtain more realistic estimates of actual energy use. The unfortunate impact of these behavioural trends is that only half of occupants (52% of SFHs and 45% of MFHs) feel comfortable in their dwellings, while 6% of SFHs and 10% of MFHs are forced to live in severely adverse conditions.