4. BASELINE MODELS FOR CHARACTERIZATION, FORECASTING AND DECISION-MAKING IN DISTRICTS
4.3. Validation of the model
In this section, the proposed baseline models will be validated in two ways: first, a theoretical validation will be carried out through simulation, and then an experimental validation will be done by using temperature and air-conditioning consumption measurements obtained from the monitoring of a household.
4.3.1. Theoretical validation
4.3.1.1. Case study
A dwelling located in a social housing district in Seville (Spain) will be considered for the validation of the proposed models. This dwelling is located on the third floor of one of the building blocks of the district (see Figure 54).
Figure 54: Location of the dwelling under study.
In order to carry out a detailed analysis of the thermal behavior of the dwelling, it is necessary to know the distribution of the different spaces, so a HULC multi-zone model was created to reflect the reality. In addition, it is necessary to include the shading effects due to the surrounding buildings, since these could have a great influence on the energetic behavior of the dwelling due to reduced solar access, particularly in the building under study. The building where the dwelling is located was built in 1983. The main facade is oriented to the South-West, and the quality of construction of its walls and windows is rather poor.
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Figure 55: HULC model of the dwelling (left) and real image (right).
4.3.1.2. Results of the theoretical validation
The main objective of this theoretical validation is to show the details of the application of the proposed baseline models. In order to do that, the first step is to simulate the HULC building model that was created, considering the real weather conditions. This is done by creating a weather file following the procedure explained in Annex A. The first simulation is performed without air-conditioning. That means that the full free-floating temperatures can be obtained, giving way to the primary baseline. An example of the temperatures that are reached inside the dwelling during the heating season is shown in the next figure.
Figure 56: Illustration of the evolution of the indoor and outdoor temperatures.
If the whole year is shown (see Figure 57), the effect of the internal and solar gains can be observed. In average, the indoor temperature is higher than the outdoor temperature. Then, once the effect of the gains has been demonstrated they should be characterized. In order to do so, another simulation is performed in such a way that the thermal load due to solar and internal gains can be disaggregated.
Finally, the proposed model for obtaining energy baselines will be obtained. To do so, first the primary baseline is identified, and then the secondary baseline with 6 numerators and 1 denominator. The primary baseline allows to estimate the full free-floating temperature, which combined with the secondary baseline model allows to estimate the thermal loads of the space when the air-conditioning equipment is activated, or the air temperature when the air-conditioning is not working. The following graph shows a comparison between the air-conditioning consumptions obtained by the simulation and the ones estimated through the proposed baselines, as well as a comparison between the temperatures obtained by the simulation and the ones estimated. The validity of the proposed procedure is demonstrated, as well as the goodness of fit offered by the physical sense that was forced in the identification of the coefficients of the proposed transfer functions.
Figure 58: Comparison between simulated and estimated temperature and consumption measurements. To illustrate the way the baselines work, we can see for example what happens at the end of March. Since the indoor air temperatures are over 20 °C and below 25 °C, there is no need for air-conditioning. As it can be seen in the figure below, although the indoor temperatures and the ones estimated by the primary baseline (full free-floating temperature) were very different during days when the air-conditioning system was working, after turning off the air-conditioning for some days they are very similar.
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4.3.2. Experimental validation
4.3.2.1. Required monitoring
The first requirement in order to evaluate the real thermal performance of a district is to have temperature measurements of its representative buildings. This could be done by installing temperature sensors, preferably in the spaces that use the air-conditioning systems, but also in those which do not use them. More information about these sensors is given in Annex C.
On the other hand, an accurate assessment of a district would require data of the HVAC energy consumption of its representative buildings, which could be possible by installing a Smart Plug on the air-conditioning systems. However, if this were not possible, disaggregating these consumptions in residential buildings is an intricate task. The main reason is that even when there is access to the total electricity consumptions, they are very volatile and depend on the number of occupants, their behavior, income, size of the dwelling or climatic zone. Nevertheless, there are some ways in which this disaggregation of the air-conditioning consumption could be estimated: using the total electricity consumption combined with measurements of temperature, or using standard profiles. These alternatives are presented in Annex B in more detail and will be applied in Chapter 5.
4.3.2.2. Estimation of the matching climate
The energy consumption and thermal comfort of the dwellings in a district may be inferred by using data from a monitoring campaign, but the real weather conditions are also necessary for an accurate assessment. Ideally, a weather station should be installed in the district. However, if this were not possible (mainly due to budgetary constraints) there are other alternatives. Annex A describes the procedure developed in the present work to obtain a weather file at any location, modified through real measurements of outdoor temperatures, humidity and solar radiation that are typically obtained from weather stations that are located nearby. Once this new weather file is created, it can be used to perform simulations under real climatic conditions, or it can be applied for the baseline models developed in this chapter.
4.3.2.3. Case study
The same dwelling that was used in the previous section for the theoretical validation will be considered here. In this case, a temperature sensor was installed in the living room of the dwelling under study, and a Smart Plug was installed on the air-conditioning unit to measure its electricity consumption. A Smart Meter was also installed to check the total electricity consumption of the dwelling. The devices were operative from the 25th of July to the 15th of September 2017. The measurements obtained during this period can be seen in Figure 61.
Figure 60: Installation of the temperature sensor (left) and smart plug on the air-conditioning system (right).
Figure 61: Measurements obtained from the monitoring campaign.
4.3.2.4. Results of the experimental validation
In order to show the results obtained by using the proposed methodology of energy baselines, we will focus on 3 weeks in August 2017. Since the real air-conditioning consumptions were available (as well as the total household electricity consumptions), in this case there was no need to disaggregate the consumptions during this period. Once all the process for obtaining the baselines was carried out, it was possible to establish a correlation between the real air-conditioning consumption and the temperatures that were reached in this dwelling. The following figure shows the measured indoor temperature of the living room of the dwelling compared to the correlated values that were obtained, demonstrating the validity of the procedure.
Figure 62: Comparison between the measured and estimated indoor temperatures.
In addition, the full free-floating temperature that the space would have had if the air conditioning system had not been used at all (obtained by using the primary baseline), as well as the total electricity consumption and the air conditioning consumption (measured and the one estimated in the previous section) can be seen in Figure 63.
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