The assessment methodologies for actual energy consumption can be a useful starting point to carry out diagnostic processes on real estate. In particular, the consumption analysis enables one to identify anomalies and critical issues in building (i.e. in terms of overconsumption in comparison with the average behaviour of the examined sample buildings).
The first step of the diagnostic process is the energy classification of the real estate. From the operative point of view, this means, first of all, defining the correlation between consumption and volume in order to identify any possible cases that do not reflect the statistical trend of the sample.
The frequency distribution of the specific consumption is then expressed as a basis of the energy classification (consumption class A, B, C, etc.) which may lead to planning and developing energy requalification interventions. Obviously, priority will
Figure 3.5 Measured specific useful heat supply versus corrected conventional specific useful heat supply for a sample of buildings used for different purposes
be given to high-consumption buildings (in terms of both absolute and specific values). Therefore, the aim of the analysis is to examine the distribution of both absolute and specific consumption, and to carry out an energy classification in order to identify those subgroups of the sample which present more critical issues in terms of energy.
Figure 3.6 expresses primary energy consumption for heating in a school complex.
As clearly shown in Figure 3.6, the volume of most of the buildings is below 40,000m3. However, higher volume buildings, despite their small number, have a significant impact upon total consumption. Moreover, a large number of buildings fall above the regression line (passing through the origin) representative of the sample consumption. This indicates that a number of specific consumptions are significantly higher than the sample trend.
These results must be integrated with frequency distribution and cumulated frequency of the specific consumption, expressed in kWh/m3, for the examined real estate (see Figure 3.7). About 60 per cent of the values are lower than 40kWh/m3, which is a reference value set slightly below the average specific consumption value of the sample. Moreover, it is evident that in some cases the specific consumption significantly exceeds the average: 11 per cent of the sample show consumption above 80kWh/m3(double the sample average value), and
7 per cent show consumption above 120kWh/m3(triple the sample average value). It is therefore necessary to deepen the diagnostic analysis on the buildings presenting such critical issues in order to identify the causes (which may be related to the building envelope, plant technology, plant management, users’ behaviour, etc.) and propose corrective solutions.
A further in-depth analysis can be carried out by classifying the energy efficiency of the real estate as a function of the specific consumption value, set as an index for characterizing the consumption in existing buildings. The following methodology defining a dimensionless indicator of the actual consumption is adopted:
Ic= CEs / CErif(consumption index) (4) where the value of CErif (kWh/m3) (reference specific energy consumption) is obtained from the statistical analysis of the specific energy consumptions (CEs) of the sample of buildings characterized by the same use (school buildings). In this case, CErifcorresponds to the average value of the examined sample of buildings. On the basis of the Icindex value, four classes are defined (see Table 3.1).
Each of the four classes depicted in Table 3.1 corresponds to an assessment of the Ic index (see Table 3.2).
Figure 3.6 Primary energy consumption for heating as a function of gross heated volume
This approach emphasizes an important aspect: it is evident that intervention priority is given to high-consumption buildings (in comparison with the average consumption of the estimated sample of buildings), although general improving interventions on the building plant system must not be excluded for classes A and B either. Therefore, the proposed diagnostic method defines the guidelines for the assignment of intervention priority within the specific examined sample of buildings. For this reason, the CErifvalue is not aprioristically defined on the basis of literature data, but represents a studied characteristic datum of the real estate.
Figure 3.8 shows the frequency distribution and the cumulated frequency of the specific consumption index calculated for the above-mentioned sample of buildings. The energy efficiency classification described in Table 3.2 is also shown in the diagram.
Figure 3.8 shows that it is possible to define a clear and objective subdivision of the examined real estate into energy efficiency classes. At first, the diagnostic investigation is carried out on high-consumption buildings. In this case, 10 per cent of the buildings fall into class D (= specific consumption index above 2);
therefore, they are assessed as ‘non-classifiable’.
These tools are useful for the energy classification of real estate, which is a preparatory activity for the diagnostic
Other
Figure 3.7 Frequency distribution and cumulated frequency of specific heating consumption
Table 3.1 Variation intervals of the Icindex
Index Variation Class Index
interval assessment
Consumption index ≤ 0.5 A Excellent Ic[ – ] 0.5 < Ic≤ 1 B Good
1 < Ic≤ 1.5 C Mean 1.5 < Ic≤ 2 D Poor Ic> 2
Non-classifiable
Table 3.2 Assessment classes of the Icindex
Ic Assessment
Class A Building consumption far below the average consumption of the reference statistical sample.
No intervention is needed.
Class B Building consumption slightly below the average consumption of the reference statistical sample.
No intervention is needed.
Class C Building consumption above the average consumption of the reference statistical sample.
Intervention aimed at reducing heating consumption is recommended.
Class D Building consumption significantly above the average consumption of the reference statistical sample. Urgent intervention aimed at reducing heating consumption is recommended.
investigation on high-consumption (absolute and specific) buildings. Moreover, these procedures are a particularly effective support tool for planning extraordinary maintenance activities in real estate, which implies the definition of criteria for assigning intervention priorities.