A comparison of projected and actual energy performance of buildings after thermal retrofit measures

Abstract

This article addresses the discrepancies between projected and actual energy performance of thermally retrofitted buildings. Toward this end, we use detailed data and observations pertaining to seven residential buildings in Austria that were thermally retrofitted recently. These include five multifamily residences in Vorarlberg, the upper level of a duplex house in Lower-Austria, and a residential complex for the elderly in Styria. During the heating season 2009–2010 (1st October–30th April), indoor temperature and relative humidity levels were measured and logged in these buildings. For each building, the actual energy use during this period was derived based on bills for gas and electrical power. Additionally, we obtained and examined existing energy calculations (energy certificates) for these buildings. In six cases out of seven, we found a large discrepancy between projected and actual space heating demand. To explore possible reasons for this discrepancy, we generated for each of the buildings an energy certificate and performed detailed thermal simulations. Thereby, we took the main input parameters for energy calculations into consideration (air change rate, indoor air temperature, outside air temperature, and internal gains). If we use standard (default) values as suggested by Austrian standards for these parameters, the above-mentioned discrepancy cannot be explained. Measurements in the buildings, as well as interviews with the building’s inhabitants implied that standard-based input data assumptions were not reliable. A subsequent multi-factor study suggested that specifically the assumptions regarding air change rates might be responsible for the large deviations of the calculated values from the actual heating demand.

The Role of Occupants in Buildings’ Energy Performance Gap: Myth or Reality?

“…The characteristics reported are generally inconsistent across the studies due to differences in research foci and data availability issues. The most reported characteristics are the number of people [9,10,15,26,33,49,59,60,[79][80][81], age [9,10,15,17,21,26,33,59,77,80,81], household composition [6,7,12,14,17,30,59,77,80,82,83], and income [9,10,21,26,29,33,79,80]. Additional characteristics reported were ownership status [9,10,26,79,80,84] and education levels [17,21,…”

“…One study [85] gathered OB data through virtual reality. Similar to the occupant characteristics information, the captured behavioral information is also largely focused on residential contexts, social and student housing, and a few instances of university buildings (e.g., [5,6,9,10,[12][13][14]16,18,49,50,68,77]). The monitored behavioral information primarily relates to the number of occupants, occupancy schedule, and systems control habits concerning, for instance, operational set-points, the use of appliances and (natural or mechanical) ventilation.…”

In the matter of simulation and buildings: some critical reflections

“…Thereby, it was suggested that the frequently observed discrepancy between buildings' predicted and actual energy performance is chiefly due to simplified (typically schedulebased and rule-based) representations of inhabitants' presence and control-oriented behaviour in buildings. The relevant point of discussion here is not so much the question of if this suggestion consistently applies: In fact, a good many -but not all -discrepancies between a priori predictions of buildings' energy demand and their actual energy performance may be at least partially attributable to people's behavioural patterns (Housez, Pont, and Mahdavi 2014). Likewise, we do not wish to enter into a debate here if the principal objective of simulation studies is always the prediction of specific outcomes at specific instances of time in future (as opposed to, for example, comparative assessment of alternative design options).…”

Domestic building fabric performance: Closing the gap between the in situ measured and modelled performance

“…While the UK method of approach for EPC accreditation of RDSAP employs more data, such as structure, dimensions, heating system type, levels of insulation and fenestration/lighting types, it can be expected that the default U-values incorporated within the software, though likely to be more realistic, will still incline towards the pessimistic. Housez et al (2014) are among authors of works which explore the projected and actual energy performance of buildings post-retrofit. Their study looks at seven buildings situated in Austria which have received varying depths of retrofit in an attempt to improve on thermal performance and reduce energy consumption.…”