- In Wallonia (southern, mainly French-speaking part of Belgium): 22.4% of the total 135.4 TWh final energy consumption ;
- In Belgium: 19.9% of the total 39,759 ktoe (around 462 TWh) final energy consumption ;
- In Europe (EU28): 25% of the total 1.1 Gtoe (around 12.9 GWh) final energy consumption .
- An asset rating of the annual primary energy consumption for heating, Domestic Hot Water (DHW), cooling (if present) and auxiliaries consumptions, expressed in kWh/m2 year;
- A scale rating, based on the asset rating result, to sort buildings into efficiency categories (from A++ to G) and to allow easier comparisons between buildings.
- The administration has very little direct contact with end-users, apart from (lengthy) guides released to help users understand their EPC.
- Financial profitability leaves to the assessor few liberties to discuss the method, protocol, his/her assessment or conclusions.
- Real-estate agents are not trained on the certification protocol, so that they generally cannot give better than fragmented information on the results (and they generally focus more on the A-to-G rating than the kWh/m2 year rating level or the improvement advice).
1.2. Behavioral Standardization
- The definition of the set temperature for heating the dwelling;
- The definition of the heated volume, inside the “protected volume”;
- The evaluation of internal loads, whether they could be gained from electricity consumption (equipment, cooking, lighting) or the metabolism of inhabitants;
- The evaluation of heat losses due to ventilation;
- The definition of DHW demands.
2. Materials and Methods
2.2.1. Socio-Demographic Variables
- The household’s characteristics: size of the family, presence of toddlers, presence of children aged 15 or less, presence of people aged 65 or more; and overall income category;
- The description of the responder to the interview (head of house): gender, age category, highest diploma, occupation.
- The age of the building, its typology category, number of exterior facades, position in the block;
- The existence (and use) of an extension (quite commonly built at the back of the building, after the original building and often lower quality);
- The use of the upper floor area (for dwelling or for storage purposes, part of the heated volume or not, etc.);
- The energy improvement investments that have been made since the EPC assessment, in order to upgrade it to better match the reality.
2.2.3. Heating Habits
- Number of “all-day heating” days a week, during which the whole volume or the daytime zones only are fully heated all day (14 h a day by hypothesis);
- Number of “partial heating” hours: average number of hours during which the main spaces are heated on “other days” (not “all-day” heating days);
- Spaces heated during winter nights;
- Set temperatures (when known; default values will have to be used otherwise) for daytime and nighttime (when necessary);
- Heating devices (for the repartition of real consumption data);
- Global temperature management systems (the presence of a regulation system).
2.2.4. Ventilation Habits
2.2.5. Internal Gains
- “Do you use low-energy bulbs?” and “Is the lack of natural light quality in the day zone a problem in your dwelling?” influence the lighting power hypotheses;
- “Do you switch off the lights in unoccupied spaces?” reduces the lit area in brighter homes.
- Light (basic equipment of fridge with freezer, dishwasher or washing machine, microwave and regular ovens, extractor hood, radio, television and decoder, iron and vacuum cleaner);
- Moderate (“light” + dishwasher and washing machine + computer and router, etc.);
- Average (“moderate” + comfortable kitchen equipment + electric dryer, etc.);
- Important (“average” + independent freezer + occasional second fridge + second computer, etc.);
- Heavy (“important” + second television and high-tech media equipment, etc.).
- The number of household members (a part of the consumption for each piece of equipment is fixed; a part varies according to the size of the household, including cooking equipment, small appliances and sleep mode consumptions);
- The number of weekly uses of their dishwasher, washing machine and electric dryer (open questions in the questionnaire);
- The daily use level of their television(s) and computer(s), with 6 possible answers: “NA”, “Less than 2 h a day”, “2 to 4 h a day”, “4 to 6 h a day”, “6 to 8 h a day” and “more than 8 h a day”;
- The evaluation of sleep mode-associated consumptions, approached thanks to the question “Do you switch off or disconnect appliances, instead of letting them be in sleep mode?”
2.2.6. DHW Needs
- “How many baths/showers per week for the entire household?”
- “Do you tend to prefer showers to baths, in order to save time and/or water consumption?” This “rational use of energy” question mainly calibrates the new DHW need evaluation.
2.2.7. Consumption Data
2.3. Calculation Method
2.3.2. Net Heat Demand
- Qheat,net,m = monthly NHD (MJ);
- QT,heat,m = monthly heat losses due to transmission (MJ);
- QV,heat,m = monthly heat losses due to airtightness and ventilation (MJ);
- ηutil,heat,seci,m = monthly heat gains application rate, a factor that tames the internal and solar gains when they are less needed (depending on the losses/gains monthly ratio); its evaluation is not changed in this method;
- Qi,m = monthly internal gains (MJ); see  for the proposed evaluation method;
- Qs,m = monthly solar gains (MJ). Their evaluation is not changed in this method.
2.3.3. Heat Losses by Transmission
- QT,heat,m = monthly heat losses through the envelope (MJ);
- HT,heat = transmission heat losses coefficient (W/K), sum of the heat losses through the different walls of the envelope. This parameter is mainly ruled by default values that are difficult to change (when there is no more accurate data available) and uninfluenced by inhabitants behavior and habits, so that it will not be questioned here;
- θe,m = monthly average exterior temperature (°C);
- tm = length of the month (106 s).
- ΔTuhs = empirical temperature difference between heated and unheated spaces (K);
- fUm = multiplicative factor, empirically equal to the average thermal transmission coefficient (Um) of the building (-).
- Ti,j = temperature of the “j” portion of the Vp, during the “i” period (K); these data are either given by the respondent or a default value when unknown;
- Vp,j = protected volume of the “j” space (m3);
- Vp = protected volume of the whole dwelling (m3).
2.3.4. Heat Losses by Ventilation
- HV,heat = heat losses coefficient due to air tightness and ventilation (W/K);
- Vin/exfilt,heat = air tightness ventilation air flow for heating calculations (m3/h);
- rpreh,heat = taming factor considering the pre-heating of the ventilation air (when applicable) (-);
- Vhyg,heat = hygienic ventilation air flow for heating calculations (m3/h).
- v50,heat = air flow default value, under 50 Pa pressure, by square meter of the heat loss area, for heating calculations = 12 m3/h m2;
- v50,behave = air flow due to airtightness, under 50 Pa pressure, by square meter of the heat loss area, tamed by inhabitants’ behavior (m3/h m2);
- fv50 = multiplicative factor taming the air flow to consider behavior (-);
- AT,E = total heat losses area of the envelope of the protected volume (m2).
- Vhyg,heat = hygienic ventilation air flow for heating calculations (m3/h);
- mheat = multiplicative factor, depending on the ventilation system quality of execution (taking air leakages into consideration, for example; when no system is present, this parameter is set to 1).
- If the room is declared “non-ventilated”, or “only ventilated through air leakages”, or “punctual window opening” (on occasions, as opposed to regular or daily opening): Vhyg,heat,j = 0 m3/h;
- “Daily window opening”: Vhyg,heat,j = 100% of the Vp,j, the volume of the space in question (m3/h);
- “Obstruction of air vents”: Vhyg,heat,j = 15% of the regulatory air ventilation flow for the space (which is the maximum air flow allowed by the Belgian residential ventilation standard—NBN D50-001—when vents are closed) (m3/h);
- “Use of a kitchen extractor hood”: Vhyg,heat,j = 400 m3/h multiplied by the number of hours during which the hotplates are used (20 min/day + 10 min/day per person ) (m3/h);
- “Use of a bathroom extractor hood”: Vhyg,heat,j = 100 m3/h multiplied by the number of hours during which the bathroom is being used (m3/h);
- “Use of a complete ventilation system”: Vhyg,heat,j = 100% of the regulatory air ventilation flow for the protected volume (m3/h);
2.3.5. Internal Gains
- The presence of inhabitants (depending on the size of the household, the occupation pattern of the building and the loads defined by the ISO 7730:2005 standard):
- Qmet,a = annual internal loads due to metabolism (occupation pattern) (MJ);
- Nocc = number of occupants, size of the household (-);
- Pmet,i = metabolism load of one person present during the period ‘i’ (ISO 7730:2005: 80 W/person at sleep; 100 W/person awake, light activity; 120 W/person awake, daytime);
- Tm,i = length of the period “i” (106 s).
- The equipment, which depends on the description made by the respondent in the questionnaire (“light” to “heavy” levels, number of daily or weekly uses for washing and media appliances).
- QEquip,a = annual internal loads due to equipment and appliances (MJ);
- Qe,a = annual consumption of each equipment of the list defined by the level of equipment and/or the number of uses, and the number of inhabitants; see Section 2.2.5 above (MJ).
- The lighting of the dwelling, which depends on the lighting time, the power installed and the lit area (approached via the heated floor area and taming factors).
- Qlight,a = annual internal loads due to lighting (MJ);
- Nh,light,a = average annual number of hours when lights are on = 1300 h/year, considering ephemeris in Belgium , 8 h of sleep a night and 3 annual weeks of absence.
- fqual,L = multiplicative factor (-) = 0.8 to 1.6, depending on the answer to the “quality of natural lighting in day zone” question;
- PL = lighting power = 4 to 8 W/m2, depending on the answer to the “do you use low-energy light bulbs” question;
- Ach = heated floor area (m2), reduced by the 0.8 factor to exclude walls and circulation areas;
- fL = empirical taming factor (-) = 0.5 to 0.9 depending on the answer to the “do you switch off the lights in unoccupied rooms” habit.
- Qi,a = annual internal loads (MJ);
- ta = length of the year (106 s).
2.3.6. DHW Demand
- Qwater,bathi,net,m, Qwater,sinki,net,m: net DHW energy demand for a bath or a kitchen sink (MJ);
- fbathi, fsinki: the part of the bath or kitchen sink in the total DHW net energy demand (-).
- Qwater,net,m: the net energy demand for domestic hot water production (MJ);
- Nlt: the number of liters to be heated (L);
- Nd,m: the number of days in the month (-);
- 4.1855: the energy needed to raise by 1 °C the temperature of 1 cm3 of water (J);
- θwater,out: the temperature of the heated water = 50 °C;
- θwater,in: the temperature of the supplied water = 10 °C.
- Regulatory results include consumptions from ventilation and heating systems auxiliaries. As EPCs do not consider local mobile heating systems, there is no electrical heating considered in these assessments. Only Case 5 also includes electric DHW production, which explains its higher scores.
- Revaluated results (for both climates) include electrical consumption for electr(on)ic equipment, lighting, auxiliaries, cooking, when indicated thus by the respondents, local heating (mostly bathrooms, but also “other” bedrooms in Case 2) and DHW production (Case 5).
- Higher average thermal transmission coefficients (Um; see Table 1) and total heat loss by transmission coefficient (HT,heat; see Table 1). There are several levels of precision in available engineering estimates for envelope description: the thermal conductivity of all (identified) materials is imposed by default values. The very existence of the insulation layer can be unknown, which leads to the lowest level of certainty on envelope description; the thermal resistance of this hypothetical layer is therefore given a default value based on the age of the wall’s construction or renovation. When the existence of this layer is acceptably proven, its thermal resistance can still present different values, when its thickness and/or the type of insulation material is described, or when the thermal resistance of the layer is given by trustworthy proofs. Higher Um and HT,heat values could witness greater imprecision in input data.
- Lower DHW systems’ efficiencies. This is interesting, because the intermediary results (Table 5) clearly show that revaluated DHW demands are quite higher than the demands from the EPC intermediary results, which is quite surprising considering the opposite tendency in the estimation of heating demands. With higher DHW demands, therefore, detrimental DHW system efficiencies’ default values exercise higher influence on the final energy consumption. It all happens as though the regulatory method compensates underestimated DHW demands by even more underestimated system efficiencies.Major obstacles to a more refined evaluation are: (1) the real data from inhabitants, indivisible between cold and hot water consumptions; (2) the determination of efficiency values closer to reality by the assessor; and (3) the difficulty to estimate real DHW demands, based on inconstant DHW use behavior (from the interviews, Case 5: “It depends when [my daughter] is here or at her mother’s”; Case 3: “I do not bathe every day, sometimes I just rinse myself, sometimes I draw long and bubbly baths…” or Case 1: “we used to shower, but the kid arrived mid-year, and now baths are more common”). It must be admitted that inconstant behavior would normally also be witnessed in heating habits or use of appliances; these different reactions to DHW use might hide some privacy issues on the respondents’ side (for example, the healthiness interpretation of data).
- Case 2 is the biggest of the five studied houses (higher protected volume, five occupants) and presents several additions to the original volume that were initially uninsulated (roofs have been insulated thereafter). The upper level was not inhabited nor inhabitable during the period covered by the consumption data and separated from the protected volume by a simple wooden door and uninsulated walls and ceiling. All of this could explain the high total heat loss by transmission coefficient (HT,heat = 951.2 W/K), around 3.2-times the coefficient of the Case 4 house, which shares the same typology category, but is located in a row.The very important heat losses area (slightly less than 600 m2, more than twice the heat losses areas from every other cases) increases significantly the heat losses by (lack of) air tightness, which obliges us to acknowledge that this parameter is still influential in this method (and there are no real ways to refine it during an EPC assessment). Lastly, this house is equipped with PV panels, which were not considered in this study, as it focuses on consumptions rather than productions. Nevertheless, this encourages the owners to prefer local mobile electric systems to heat their children’s bedrooms and use central heating as an eventual additional system. Such particular behaviors are difficult to model in a steady-state, single-volume method.
- During the interview of Case 3, several things had been noted by the interviewer: first, the particular configuration of the house, in a sloping street, with the garden at the first-floor level (the ground floor being partially buried, a significant part of the heat loss area is protected from severe air leakages); secondly, the presence of humidity (and mold smell) in the kitchen and cigarette smoke in the living room seem to confirm the low ventilation rate revaluation. This case being the only one with a ‘stay-at-home’ parent, conscious and unconscious variations in heating habits, uncovered by this study or non-verbalized by respondents, could have an important influence on the results that do not appear here. This is probably a limitation of this exercise.
- Case 4 is probably the more “precise” EPC to begin with, with little default values to be replaced (the ones still used are not alterable). Both electricity and natural consumptions (obtained with the modified method using “real climate” data) are fairly close to the real consumption data.
- Case 5 is more questionable. The addition of electricity and natural gas consumptions, obtained with the modified method under the “real climate” data, is quite close to the addition of real consumptions data from respondents. In detail, however, the electricity consumption is about 600 kWh above reality, and natural gas is about 1000 kWh under reality. This case being the only one where DHW is produced with electricity, instead of natural gas, the discussion above on DHW results could explain the discrepancy in electricity consumptions, but not natural gas consumptions. Three important characteristics of the household could bring some explanation. Firstly, the income is relatively high for this type of house, which generally shelters more precarious households. Generally, higher incomes influences higher energy consumptions [17,22,24,26,36]. Secondly, this house is a temporary home; it is owned by the occupants, but they are currently renovating what will become their permanent home. This implies inconstant occupancy and a feeling of “not really home” that could be comparable to tenants’ attitudes and representations (generally less careful about energy consumption [22,23,24,25]). Lastly, the owners confessed: “The one who feels coldest, wins. Will turn the valve to its maximum. That’s the problem when you live with a lizard.” Humor aside, this implies that thermal comfort requires higher temperatures, the management of which is probably inconstant (and the lack of a regulation system reinforces this feeling).
- This study has as the ultimate motive to try and predict the energy consumption of a household in a house that they do not (yet) live in. The prediction of energy bills is, by essence, uncertain. The uncertainty on future climate obviously influences the results, and the average EPB Belgian climate could be as good as any in a predictive model. There is a gap, in the results above, between revaluation results obtained using the EPB average climate on the one hand or the “real” climate data on the other; that gap is part of a permanent uncertainty margin that has to be considered in the analysis of the results (and the study of annual climatic variations could result in wider margins).
- Exact correspondence between theoretical and real consumption data is limited by the high number of uncertainty parameters in the method to control, particularities and special occasions in energy consumption. Furthermore, the respondents to the survey cannot or will not always give the needed information, as some are subconscious, others considered private by those who have a more emotional link to energy or a more secretive approach to their life at home.
- The questionnaire media in itself is a limitation: the attention, interest and understanding of the respondent is important for the reliability of his/her answers, so that the number of questions should be controlled. Therefore, the number of added parameters will be restrained. Interviews allowed detecting unmentioned behaviors and improving the progressing questionnaire. There was, however, no psychological side to this study, while it must be acknowledged that this is also a crucial way to understand consumption behavior or attitude/behavior gaps [11,17,36].
- Lastly, one must acknowledge that this questionnaire somehow replaces default values by others, some of which are chosen empirically (see above). Perhaps more precisely, default values have been multiplied, in the belief that a sum of little uncertainties on more accurate default values would be less damaging to the final results than one big uncertainty on one default value. A sensitivity analysis will follow to validate them.
- The steady-state calculation method, as it is implemented in Wallonia, is probably accurate enough to allow final energy consumption predictions, if improved on several behavioral parameters.
- The additional data gathered with the questionnaire is already quite extensive and requires about an hour of interview with respondents (around half of it for the data needed in this study; the rest of the interview was used to explore the households’ understandings and views on the certification scheme, their real-estate investments decisions and obstacles and incentives for their renovation decisions). The number of questions has to be limited to ensure sufficient understanding and attention of respondents, as well as the reliability in their answers.
- An indication on the level of accuracy of input data (envelope and systems’ descriptions) is strongly needed to analyze these results, but requires more thorough monitoring and investigations on the building, which would completely change the certification protocol, the time needed for full assessment and perhaps the financial profitability of the “job”.
- There could be further study on the existing Walloon dwelling stock in order to refine the regulatory calculation method on envelope description. The introduction of typologies in addition to the age of the building, for example, could lead to a matrix of more accurate default values, to replace the actual list of values that characterize the whole building stock.
- A sensitivity analysis on the accuracy of behavioral parameters that are input is needed as a further step in this study; there are still several (some of them empirical) parameters that influence the final result that are still to be analyzed and validated.
Conflicts of Interest
- ICEDD ASBL. 2011 Energy Assessment of Wallonia; ICEDD asbl for the Public Service of Wallonia: Namur, Belgium, 2012; p. 80. [Google Scholar]
- International Energy Agency Website—Belgium Page. Available online: https://www.iea.org/countries/membercountries/belgium/ (accessed on 19 September 2016).
- Eurostat Website. Available online: http://ec.europa.eu/eurostat/web/energy/data/energy-balances (accessed on 19 September 2016).
- Intergovernmental Panel on Climate Change (IPCC). Climate Change 2007: Synthesis Report; Core Writing Team, Pachauri, R.K., Reisinger, A., Eds.; IPCC: Geneva, Switzerland, 2007; p. 104. [Google Scholar]
- Housing Division, DGATLP, Ministry of the Walloon Region. Enquête sur la Qualité de L'habitat en Région Wallonne 2006–2007; Walloon Region: Namur, Belgium, 2007. [Google Scholar]
- European Parliament and Council. Directive 2002/91/CE Approved the 16th of December 2002, about Energy Performance of Buildings. 2002. Available online: http://eur-lex.europa.eu/eli/dir/2002/91/oj (accessed on 9 November 2016).
- Laine, L. As Easy as EPC? Consumer Views on the Content and Format of the Energy Performance Certificate; Consumer Focus: London, UK, 2011. [Google Scholar]
- O’Sullivan, A. Urban Economics; McGraw-Hill: Boston, MA, USA; London, UK, 2007. [Google Scholar]
- Amecke, H. The Impact of Energy Performance Certificate: A Survey of German Home Owners. Energy Policy 2012, 46, 4–14. [Google Scholar] [CrossRef]
- Rogoff, B. Observing sociocultural activities on three planes: Participatory appropriation, guided appropriation and apprenticeship. In Sociocultural Studies of the Mind; Wertsch, J.V., Del Rio, P., Alverez, A., Eds.; Cambridge University Press: Cambridge, UK, 1995; pp. 139–164. [Google Scholar]
- Billett, S.R. Situation, social systems and learning. J. Educ. Work 1998, 11, 255–274. [Google Scholar] [CrossRef]
- Serfaty-Garzon, P. L’Appropriation. In Dictionnaire Critique de L’habitat et du Logement; Segaud, M., Brun, J., Driant, J.-C., Eds.; Editions Armand Colin: Paris, France, 2003; pp. 27–30. [Google Scholar]
- Guy, S.; Shove, E. The Sociology of Energy, Buildings and the Environment: Constructing Knowledge, Designing Practice (Routledge Research Global Environmental Change Series, 5); Routledge: London, UK, 2000; p. 164. [Google Scholar]
- Public Service of Wallonia. Arrêté du Gouvernement Wallon du 30 Juillet 2014 Portant Exécution du Décret du 28 Novembre 2013 Relatif à la Performance Énergétique des Bâtiments; Belgian Monitor: Namur, Belgium, 2014; pp. 56172–56294. [Google Scholar]
- Public Service of Wallonia. Annexe D: Méthode de Détermination de la Consommation Spécifique des Bâtiments Résidentiels dans le Cadre de la Certification PEB; Belgian Monitor: Namur, Belgium, 2014; pp. 61636–61767. [Google Scholar]
- EPBD—Concerted Action. Implementing the Energy Performance of Buildings Directive 2010 (EPBD), Featuring Country Reports; EU Publications Office: Brussels, Belgium, 2011. [Google Scholar]
- Fanger, P.O. Human Comfort and Energy Consumption in Residential Buildings. In Proceedings of the International Energy Use Management Conference, Tucson, AZ, USA, 24–28 October 1977.
- Hauglustaine, J.-M. Incidences du Comportement Humain sur la Consommation D’énergie dans les Habitations Sociales. Master’s Thesis, University of Liege, Liege, Belgium, 1979. [Google Scholar]
- Lutzenheiser, L. Social and behavioral aspects of energy use. Annu. Rev. Energy Environ. 1993, 18, 247–289. [Google Scholar] [CrossRef]
- Wilhite, H.; Nakagami, H.; Masuda, T.; Yamaga, Y.; Haneda, H. A cross-cultural analysis of household energy-use behaviour in Japan and Norway. Energy Policy 1996, 24, 795–803. [Google Scholar] [CrossRef]
- Wilhite, H.; Lutzenhiser, L. Social loading and sustainable consumption. Adv. Consum. Res. 1998, 26, 281–287. [Google Scholar]
- Wilhite, H.; Shove, E.; Lutzenhiser, L.; Kempton, W. The legacy of twenty years of energy demand management: We know more about individual behaviour but next to nothing about demand. In Society, Behaviour, and Climate Change Mitigation; Jochem, E., Sathaye, J., Bouille, D., Eds.; Springer: Dordrecht, The Netherlands, 2000; pp. 109–126. [Google Scholar]
- Lindén, A.L.; Carlsson-Kanyama, A.; Eriksson, B. Efficient and inefficient aspects of residential energy behaviour: What are the policy instruments for change? Energy Policy 2005, 34, 1918–1927. [Google Scholar] [CrossRef]
- Wallenborn, G.; Rousseau, C.; Thollier, K.; Aupaix, H. Politique d’Appui Scientifique à une Politique de Développement Durable PADDII: Détermination de Profils de Ménages Pour une Utilisation Plus Rationnelle de L’énergie, Partie 1: Modes de Production et de Consommation Durables; Federal Scientific Policy: Brussels, Belgium, 2006; p. 106. [Google Scholar]
- De Groot, E.; Spiekman, M.; Opstelten, I. Dutch research into user behaviour in relation to energy use of residence. In Proceedings of the PLEA 2008—25th Conference on Passive and Low Energy Architecture, Dublin, Ireland, 22–24 October 2008.
- Santin, O.G. Actual Energy Consumption in Dwellings, the Effect of Energy Performance Regulations and Occupant Behavior; Sustainable Areas Series; TU Delft: Delft, The Netherlands, 2010; p. 242. [Google Scholar]
- Allibe, B. Modélisation des Consommations D’énergie du Secteur Résidentiel Français à Long Terme, Amélioration du Réalisme Comportemental et Scenarios Volontaristes. Ph.D. Thesis, Ecole des Hautes Etudes en Sciences Sociales, Paris, France, 2012. [Google Scholar]
- Hens, H.; Parijs, W.; Deurinck, M. Energy consumption for heating and rebound effects. Energy Build. 2010, 42, 105–110. [Google Scholar] [CrossRef]
- Vanparys, R.; Niclaes, E.; Lesage, O. Certificat Énergie, la Base d’un Véritable Audit? Association des Consommateurs Test-Achats SCRL: Brussels, Belgium, 2012; pp. 10–16. [Google Scholar]
- Monfils, S.; Hauglustaine, J.-M. Etude Énergétique—Typologique du parc Résidentiel Wallon en Vue D’en Dégager des Pistes de Rénovation Prioritaires, Rapport Final; University of Liege: Liege, Belgium, 2009; p. 73. [Google Scholar]
- Gram-Hanssen, K. Residential heat comfort practices: understanding users. Build. Res. Inf. 2010, 38, 175–186. [Google Scholar] [CrossRef]
- Official Website of the Walloon Commission for Energy. Available online: http://www.cwape.be/ (accessed on 26 September 2016).
- Website of the Belgian Association for the Promotion of Renewable Energies. Available online: http://www.apere.org (accessed on 26 September 2016).
- Official National Weather Forecast and Database Website. Available online: http://www.meteobelgique.be/ (accessed on 15 June 2016).
- Davin, E.; André, P. Rapport Smart Micro Cogen WP2: Identification des Profils Caractéristiques de Consommations (Chauffage, Consommations Électriques) dans les Bâtiments; University of Liege: Arlon, Belgium, 2014; p. 25. [Google Scholar]
- Brisepierre, G. Analyse Sociologique de la Consommation D’énergie dans les Bâtiments Résidentiels et Tertiaires: Bilan et Perspectives; ADEME: Paris, France, 2013; p. 51. [Google Scholar]
|Building period (-)||2007||[1946–1960]||[1919–1945]||[1946–1960]||[1919–1945]|
|Typology||First floor||Urb. extension||Modest||Urb. extension||Blue-collar|
|Vp (protected volume) (m3)||487||841.8||443.2||505.5||323.1|
|Heated Floor Area (m2)||160.7||254.9||138.1||162.6||101.3|
|AT (Total heat loss area) (m2)||228.2||598.9||225.5||257.2||179.4|
|Average U-value (W/m2·K)||0.79||1.59||1.76||1.16||1.21|
|Heating system efficiency (EPC) (-)||0.670||0.693||0.601||0.774||0.626|
|DHW system efficiency (EPC) (-)||0.510||0.383||0.332||0.488||0.712|
|Number of exterior facades (-)||2||3||2||2||2|
|Presence of an extension?||No||Yes||Yes||No||Yes|
|Use of the upper floor?||Bedrooms||Attic (off Vp)||Bedrooms||Storage (in Vp)||Storage (in Vp)|
|Kitchen open on living room?||Yes||Yes||No||Yes||Yes|
|Annual electricity consumption (kWh/year)|
|(1) Real data (respondent’s)||3989||9436||3774||4691||4609|
|(2) EPC regulatory calculation||614||841||377||430||1599|
|Annual final energy consumption for heating and DHW, excluding electricity (kWh/year)|
|(3) Real data (respondent’s)||8300||25,297||12,743||14,493||10,091|
|(4) EPC regulatory calculation||24,806||103,780||52,304||32,163||26,390|
|Number of inhabitants (-)||4||5||4||4||3|
|Presence of toddlers?||Yes||No||Yes||Yes||No|
|Presence of children between 3 and 15?||No||Yes (3)||Yes (2)||Yes (2)||Yes (1, half-time)|
|Presence of elderly?||No||No||No||No||No|
|Monthly total income category||[2000; 2999]||[4000; 4999]||[2000; 2999]||[4000; 4999]||[4000; 4999]|
|Respondent age category||[25; 34]||[35; 44]||[25; 34]||[25; 34]||[35; 44]|
|Respondent highest diploma||University||University||Sup non univ.||University||Sup non univ.|
|Respondent daily occupation||Independent||Executive||Employed||Executive||Employed|
|Metabolism loads due to occupation (Qmet,a) (kWh/year)||2626||3158||2321||2521||1857|
|Switch off appliances instead of sleep mode?||+||+||+/−||+/−||+/−|
|Estimated sleep mode annual consumption (kWh/year)||135||150||160||160||140|
|Equipment electricity consumption (Qequip,a) (kWh/year)||3088||4088||3055||3239||2091|
|Switch off the lights in unoccupied spaces?||+/-||+||++||+||+|
|Area-reducing factor (fL) (-)||0.7||0.6||0.5||0.6||0.6|
|Do you use low-energy bulbs?||+/-||+||+||++||++|
|Lighting power (PL) (W/m²)||6||5||5||4||4|
|Natural lighting quality in day zone?||++||+||-||+/-||-|
|Quality factor (fqual,L) (-)||0.8||1||1.4||1.2||1.4|
|Lighting electricity consumption (Qlight,a) (kWh/year)||562||795||503||487||354|
|Energy vector for cooking (hobs)?||Electricity||Electricity||Electricity||Electricity||Electricity|
|Cooking electricity consumption (Qcook,a) (kWh/year)||420||420||490||420||280|
|Total annual internal gains (Qi,a) (kWh/year)|
|From EPC regulatory method||4785.5||6869.1||4527.3||4897.0||3823.0|
|Revaluation from behavior||6696||8461||6369||6667||4582|
|Revaluation / EPC (%)||139.9%||123.2%||140.7%||136.1%||119.9%|
|Out of the 7 days of a normal (work or school) winter week, how many all-day heating of…|
|… the whole home (day AND night zones)?||0||2||2||2||0|
|… the day-time zone only?||5||0||5||0||5|
|On “other” days (not “all-day” heating days), on average, how many hours do you heat…|
|… the living room (LR)?||4||8||0||8||4|
|… the kitchen (K)?||4||8||10||8||4|
|… the main bedroom (MBDR)?||0||0||0||0||0|
|… the other bedrooms (OBDR)?||0||6||6||6||0|
|… the bathroom (BTR)?||2||2.5||2||6||1.25|
|Spaces heated during winter nights?||LR, K, OBDR||LR, K||LR||OBDR||LR, K|
|% of winter time without heating?||11.9%||17.9%||8.3%||17.9%||20.2%|
|Temperature regulation device?||Yes||Yes||Yes||Yes||No|
|Set temperatures during day-time in…|
|… the living room (LR)?||21||21||22||21||24|
|… the kitchen (K)?||21||21||22||21||24|
|… the bedroom(s) (BDR)?||-||21||20||21||-|
|… the bathroom(s) (BTR)?||21||21||22||21||24|
|Set temperature during night time?||18||16||18||16||16|
|Do you close doors separating heated and unheated spaces?||+/−||++||++||++||++|
|Ventilation of the living-room (LR)?||occasional||occasional||occasional||no||daily|
|Ventilation of the kitchen (K)?||hood||occas. + hood||daily||daily + hood||no|
|Ventilation of the bedrooms (BDR)?||daily||daily||daily||occasional||daily|
|Ventilation of the bathroom (BTR)?||timed||occasional||occasional||daily||timed|
|Average ventilation rates (m3/h)|
|From EPC regulatory method||284.8||369.8||269.9||289.6||223.9|
|Revaluation from behavior||46.6||28.95||10.6||23.1||12.6|
|Do you weather-strip the doors and windows in winter?||++||+||+||+/-||+|
|air-flow reducing factor fv50 (-)||0.8||0.85||0.85||0.9||0.85|
|Empirical ΔT (ΔTuhs × fUm)||2.37 °C||6.35 °C||7.04 °C||4.63 °C||4.85 °C|
|Heating periods: average set temperature of heated zones?||19.58 °C||18.46°C||20.55 °C||18.46 °C||19.49 °C|
|Heating periods: estimated average temperature of the whole building?||17.99 °C||15.5 °C||15.5 °C||14.57 °C||15.94 °C|
|How many baths/showers a week?||7/14||10/20||7/7||10/10||4/14|
|Tendency to prefer showers?||+/-||+/-||-||+/-||+|
|Consumption level||Average||Rather heavy||Rather light||Rather heavy||Rather heavy|
|Annual Net Heat Demand (Qheat,net,a) (kWh/year)|
|(1) From EPC regulatory method||14,817.2||67,652.4||28,843.4||22,574.2||17,600.8|
|(2) Revaluation-EPB climate||5430.4||29,708.6||11,734.3||7191.8||7385.6|
|Annual DHW net demand (Qwater,net,a) (kWh/year)|
|(3) From EPC regulatory method||1411.5||2266.7||1305.5||1457.2||1016.4|
|(4) Revaluation from behavior||2552.2||3589.4||2233.6||2870.8||1794.4|
|Bathroom heated by electricity?||Yes||Yes||No||Yes||Yes|
|Estimated annual electricity consumption for (local) bathroom heating (kWh/year)|
|Bedrooms heated by electricity?||No||Yes (children)||No||No||No|
|Estimated annual electricity consumption for (local) bedrooms heating (kWh/year)|
|Annual electricity consumption (kWh/year)|
|(1) Real data (respondent’s)||3989||9436||3774||4691||4609|
|(2) EPC regulatory calculation||614||841||377||430||1599|
|(3) Revaluation-EPB climate||5150||11,683||4425||5062||5239|
|(4) Revaluation-real climate||4417||10,349||4048||4593||5218|
|Annual final energy consumption for heating and DHW, excluding electricity (kWh/year)|
|(5) Real data (respondent’s)||8300||25,297||12,743||14,493||10,091|
|(6) EPC regulatory calculation||24,806||103,780||52,304||32,163||26,390|
|(7) Revaluation-EPB climate||11,615||38,753||26,244||14,046||9804|
|(8) Revaluation-real climate||9887||34,291||20,094||13,095||9017|
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).