Predicting energy consumption and savings in the housing stock

Abstract

Research methods The research used several large datasets, about dwellings theoretical energy performance, most of which were related to energy label certificates. All the datasets containing theoretical performance were merged with actual energy data. In addition to that, some were also enriched with socioeconomic and behaviour related data from Statistics Netherlands (CBS) or from surveys which were designed for the purpose of this research. Simple descriptive statistics were used to compare average theoretical and actual consumptions. Advanced statistical tests were used for detecting correlations, followed by several regression analyses. In a separate scenario study, the resulting averages of both theoretical and actual consumptions were extrapolated nation-wide in order to be compared with the existing policy targets. Due to low predictive power of the variables in regression analyses, a sensitivity analysis of the theoretical gas use was performed on six assumptions made in the theoretical calculation to show how an increment in one of the assumptions affects the final theoretical gas consumption and whether this can explain the performance gap. Last but not least, longitudinal data of the social housing dwelling stock between 2010 and 2013 was analysed, focusing on dwellings that had undergone renovation. The goal was to find out whether the theoretical reduction of consumption materialised and to what extent. A comparison of the actual reduction of different renovation measures was made in order to show what renovation practices lower the consumptions most effectively. The discrepancies between actual and theoretical heating energy consumption in Dutch dwellings. Discrepancies between theoretical and actual gas and electricity consumption On average, the total theoretical primary energy use seems to be in accordance with actual primary energy consumption but when looking at more detailed data, one can see that the contribution of gas to the actual primary energy is much lower than in the theoretical primary energy and that the contribution of electricity is opposite – higher in the actual than theoretical primary energy. The two effects cancel each other out so that in terms of total primary energy, the theoretical consumption seems to be well predicted. Furthermore, the analyses showed that the variation in electricity consumption is marginal across label categories. This together with the fact that most Dutch dwellings are heated with gas made us focus exclusively on gas consumption in the rest of the thesis. Whereas it is clear that theoretical electricity consumption is much lower than actual since it does not account for appliances, however, it is much less obvious why gas consumption is on average so much lower in reality than according to theoretical calculation. Performance gap in relation to energy label The discrepancies in gas consumption were the largest in the poorest performing dwelling, where theoretical consumption surpassed the actual almost twice, which we also referred to as overprediction. On the other hand, well performing dwellings consume roughly 20% more gas than predicted. Theoretical electricity consumption was at least twice lower than actual in all label categories, due to the fact that actual consumption takes into account electricity use of appliances and theoretical does not. Actual and theoretical electricity consumptions seemed to be rather constant with regard to the label class. Primary energy consumption is a sum of consumption of gas and electricity in MJ for each label class where the efficiency of the electricity generation and of the network was taken into account as well as the heating value of gas burning. The theoretical primary energy use is dominated by gas consumption, since electricity is a relatively small fraction of primary energy use due to exclusion of the household appliances. The relation between actual and theoretical therefore remains similar as seen in gas consumption. For poor label classes, the theoretical consumption is overpredicted by about 30% and for good label classes it is underpredicted for roughly the same percentage. Electricity consumption does not seem to depend on the energy performance of the dwelling. Moreover, the end uses of electricity included in actual and in theoretical consumption are different to an extent that renders a comparison meaningless (as the theoretical excludes appliances). Therefore the main focus of the thesis was gas consumption, which is also the predominantly used fuel for heating homes in The Netherlands. Performance gap in different samples The performance gap was analysed in four different datasets of varying size. All datasets provided very comparable results regarding average actual and theoretical consumptions across label categories. A closer analyses shows that the actual gas consumption has been dropping steadily within label categories A, E, F and G from 2010 till 2012. Theoretical gas consumption remained roughly the same in these years, which means that the performance gap has increased slightly. Moreover, it was found that the dwellings which had no renovation measures applied and remained unchanged from year 2010 till 2012 still exhibit a 3,5% decrease in gas use between 2010 and 2012, which shows that the decrease detected in the fours studied samples is not due to sampling bias. This decrease could be a consequence of a changing household composition (smaller number of people per household) or a decreased use of gas for cooking, however, both these phenomena's occur at a pace smaller than 3,5%. Other factors which could be responsible for this decrease could be the changing calorific value of gas and/or the method for the calculation of standardized annual consumption. Performance gap in relation to dwelling type, floor area and installation types The analyses showed that floor area does not affect the performance gap strongly. In terms of dwelling type, semi-detached houses have the highest performance gap, followed by flats with a staircase entrance, detached houses and finally, gallery flats. The performance gap differed also in dwellings with different installation types. Dwellings with a local heater in the living room (gas stove) had the highest performance gap, followed by a combined boiler with $η$<83%, and then each higher efficiency boiler had a smaller performance gap. Energy reduction targets for built environment and actual reduction potential of the dwelling stock and of the individual dwelling renovation measures Theoretical and actual achievability of the current targets A scenario analyses was conducted in the third chapter. The baseline scenario was the scenario described in Covenant Energy Savings Housing Associations Sector' (Convenant Energiebesparing Corporatiesector, 2008), which aims is to save 20% gas consumption by 2018 by improving the dwellings to a B label or at least by 2 label classes. The refurbishment scenario of the mentioned agreement was one of the scenarios considered. Another, more radical refurbishment scenario was renovating the whole dwelling stock to label A. The two scenarios were tested on both baseline consumptions, actual and theoretical (Figure 4). It turned out that by using theoretical gas use as baseline, the least radical scenario is enough to ensure the potentials discussed in B.1 are fulfilled. However, if actual gas consumption is used as a baseline, most of these potentials seem unrealistic (exception is the 10% potential as defined by IDEAL project). This points to the fact that analysts as well as policy makers rely on theoretical gas consumption as a basis for future consumption estimates, which ultimately leads to unrealistic reduction targets and renovation plans. Differences between the theoretical and actual reductions in dwellings where different renovation measures were applied Longitudinal data of dwellings energy performance was used to identify renovated dwellings and analyse their energy consumption before and after the renovation. The results showed that most of the renovations are expected to yield larger reduction than what materialises, many times the realised saving is about half of the expected. On average in all renovated dwellings, actual gas reduction is about a third lower than expected, however, there are big differences in the reductions of individual measures. Improvements in efficiency of gas boilers (space heating and hot tap water) yield the biggest energy reduction, followed by deep improvements of window quality. Improving the ventilation system yields a relatively small reduction compared to other measures, however, it is still much larger than theoretically expected. The measures achieving the most reduction are drastic improvements of window quality and an improvement of the efficiency of heating and hot tap water system (not a replacement of a local system). These are averages and the reductions for specific changes vary considerably. Measures that achieve an actual reduction higher that the theoretical seem to mostly be very modest improvements of insulation or window quality. Also notable is the underprediction of the reduction in dwellings where natural ventilation was replaced by mechanical exhaust and it is questionable whether such dwellings still have a sufficient quality of indoor air after the renovation. Causes of the differences between actual and theoretical gas consumption Explaining variation in gas use with dwelling, household and occupant characteristics Regression based on socioeconomic data showed that explaining the actual gas consumption or the difference between the actual and theoretical with the publicly available variables yields a relatively low R2 value (in view of existing literature these R values are not low) of 50,5% and 44,0%, respectively, meaning that 50,5% of the variance could be explained by these factors. Since our dataset contained many records, this relatively l