BIPV/T system – parametric analysis

generation, reported in Table 6.7, are taken into account (according to EU Eurostat - energy price statistics).

Table 6.14. Primary energy savings and avoided CO2 emissions.

Prague Freiburg Bolzano Madrid Naples Athens Almeria [kWh^p/y] REF BIPV/T REF BIPV/T REF BIPV/T REF BIPV/T REF BIPV/T REF BIPV/T REF BIPV/T Floor 1^st 167.8 72.9 102.4 31.9 93.3 14.9 109.8 26.1 78.8 -4.5 118.0 19.5 98.5 -6.3 Floor 2^nd 168.1 73.0 102.5 32.0 93.4 15.1 110.0 26.4 78.8 -4.2 118.2 20.0 98.6 -5.7 Floor 3^rd 167.9 72.8 102.5 32.0 93.4 15.2 109.9 26.6 78.8 -3.9 118.1 20.3 98.5 -5.2 Floor 4^th 167.9 72.7 102.5 32.0 93.4 15.3 109.9 26.8 78.8 -3.6 118.1 20.7 98.5 -4.7 Floor 5^th 167.9 72.6 102.5 32.0 93.4 15.4 109.9 26.9 78.8 -3.4 118.1 21.0 98.5 -4.3 Floor 6^th 167.9 72.5 102.5 32.0 93.4 15.5 109.9 27.1 78.8 -3.1 118.1 21.3 98.5 -4.0 Floor 7^th 167.9 72.5 102.5 32.0 93.4 15.5 109.9 27.2 78.8 -2.9 118.1 21.5 98.5 -3.6 Floor 8^th 167.9 72.4 102.5 32.1 93.4 15.6 109.9 27.3 78.8 -2.8 118.1 21.8 98.5 -3.3 Floor 9^th 167.9 72.4 102.5 32.1 93.3 15.7 109.9 27.4 78.8 -2.6 118.1 22.0 98.5 -3.1 Floor 10^th 168.0 72.4 102.5 32.1 93.4 15.7 109.9 27.5 78.8 -2.4 118.1 22.1 98.5 -2.9

Whole building

[MWh^e/y] 60.5 26.1 36.9 11.5 33.6 5.5 39.6 9.7 28.4 -1.2 42.5 7.6 35.5 -1.5

Δ[t^CO2/y] 10.6 6.9 6.2 5.2 6.6 14.8 6.4

Finally, by a simplified green analysis, the environmental impact of the proposed energy efficiency solution is estimated. Specifically, the average amount of acres necessary to sequestrate the avoided CO2 is calculated by taking into account the carbon dioxide sequestered by average forestry acres (i.e. 0.947 metric ton CO2 acre/year, according to the inventory of greenhouse gas emissions (from 1990 to 2013) of the US Environmental Protection Agency). A swift calculation shows that, thanks to the BIPV/T systems, the avoided CO² emissions (Table 6.14) correspond to average annual sequestrations of carbon ranging from 4.9 (Madrid) to 14.0 (Athens) acres of average forest.

assumptions considered for the ten-floor building and BIPV/T system of the case study reported in Section 6.4. Nevertheless, to increase the level of detail of the parametric study, a thirty-floor high rise building (with the South façade integrating the BIPV/T system) is modelled and simulated. The simulated layouts, defined as a function of the number of active openings, are calculated by dividing the floors number of the considered high-rise building for its integer divisors. Thus, eight BIPV/T system layouts with 1, 2, 3, 5, 6, 10, 15, and 30 openings, (ξ), are obtained. Simulations are carried out for the weather zones of Naples (featuring mild winters and hot summers) and Freiburg (featuring mild rainy winters and temperature summers).

Fig. 6.24 shows the sketch of the configuration layout relative to the typical BIPV/T system (with one opening, Fig. 6.24, left), and the BIPV/T system configuration with multiple openings (Fig. 6.24, right – showing 1 opening for each building floor, for a total of 30 openings).

Fig. 6.24. Sketch of the modelled BIPV/T façade relative to the first and second floors. Sections of the wall integrating the PV/T system with a single opening (left) and multiple openings (right).

The thermal and energy performance of each BIPV/T system layout is compared to that one obtained for the reference case (without BIPV/T). The obtained results are reported in terms of heating and cooling requirements, electricity, and primary energy percentage difference. Such index is calculated by the ratio of the difference between the values of the considered variable, calculated for the reference (XREF) and multi-opening (XPRO) layouts, to the reference one (XREF), as:

REF PRO

100

REF

X X

X X

 = − 

The parametric analysis is carried out by taking into account the same heat pumps/chiller implemented for the reference case. Heat pumps/chiller features are summarized in Table 6.5, whereas the HVAC layouts for the investigated zones and building are reported in Table 6.15.

Table 6.15. HVAC system layouts.

Naples Freiburg

Peak load Heating [kW] 43.2 91.4

Cooling [kW] 49.4 29.5

Number of selected heat pumps/chillers

Mod 41 [-] 2 2

Mod 51 [-] 1 2

Mod 61 [-] 1 2

Mod 71 [-] 1 2

Heating and cooling requirements

The impact of the number of openings (ξ) on the heating and cooling requirements is analysed hereinafter. In particular, Fig. 6.25 shows the heating requirements percentage variation (ΔQh) as a function of ξ, calculated by comparing the eight multiple openings BIPV/T layouts versus the reference (without BIPV/T) one, for both the investigated weather zones.

Fig. 6.25. ΔQ^h vs. number of openings (ξ).

As expected, by increasing the number of openings, a remarkable reduction of ΔQ^h is obtained, due to the reduction of the air channel temperature (also due to the reduced stack effect). For both the investigated weather zones, the higher is ξ, the lower is the impact of the BIPV/T on the heating loads.

Thus, since passive effects are mitigated, an increase of the heating requirements is achieved. In Naples, the percentage variation of heating requirements, ΔQh, ranges from 23.0% (at ξ = 30) to 25.4%

(at ξ = 1). In Freiburg, ΔQh ranges from 12.3% (at ξ = 30) to 13.3% (at ξ = 1). Note that, the differences between the ΔQh calculated for the investigated zones are ascribed to the higher influence of the BIPV/T system (i.e. energy savings or energy recovery potentials) in case of lower heating energy requirements.

The percentage variation of cooling requirements (ΔQ^c) as a function of ξ, is shown in Fig. 6.26.

Fig. 6.26. ΔQ^c vs. number of openings (ξ).

Hare, as expected, increasing the number of openings, ξ, helps preventing the impact of passive effects (e.g. overheating) at the higher floors (according to the findings about the inversion point reported in Section 5.1). This leads to the increase of ΔQ^c, which ranges from -3.8% (at ξ = 1) to 2.7%

(at ξ = 30) for the weather zone of Naples, and from -7.2% (at ξ = 1) to 1.2% (at ξ = 30) in Freiburg.

Note that negative ΔQc values indicate that the BIPV/T system negative passive effects (i.e.

overheating), occurring at the higher floors, overtake the positive passive effects (i.e. cooling), taking place at the lower floors. By Fig. 6.26, according to the outcomes of Fig. 6.18, it is possible to note that the use of multiple openings for the weather zone of Naples produces a reduction of the building cooling requirements, and that by using six openings (one each five floors) the overheating effects are counterbalanced by the cooling ones. Increasing the number of openings, an additional slight advantage in terms of cooling requirement reduction is observed (up to 2.7% at ξ = 30). In Freiburg, according to Fig. 6.18, during summer the use of multiple openings only allows reducing the overheating effects (no cooling effects are observed).

PV Electricity production

The number of openings on the BIPV/T façade also influences the PV electricity production. Fig.

6.27 shows the percentage variation of electricity production (ΔEel,PV) versus the number openings, ξ.

Note that for the calculation of this index, the reference value (XREF in eq.(6.23)) is the electricity production obtained in case of the BIPV/T layout with a single opening. By increasing the number of openings, ξ, on the BIPV/T system, the PV panels operate at lower temperatures with respect to those observed in case of the typical BIPV/T system configuration (with single opening).

Fig. 6.27. ΔE^el,PV vs. number of openings (ξ).

In fact, by increasing ξ, the air flowing through the channel has a lower average temperature with higher heat extraction potentials, leading to higher PV efficiencies as discussed regarding Fig. 6.21. A percentage increase of PV electricity production ranging from 0.2% (at ξ = 2) to 1.1% (at ξ = 30) is calculated for the weather zone of Naples. In Freiburg, a minor ΔE^el,PV increase is observed, reaching a maximum of 0.6% (at ξ = 30).

Electrical requirements

By taking into account the electrical needs due to the operation of the HVAC system (for heating and cooling) and the operation of the air channel fans, the percentage electricity variation ΔE^el versus ξ is show in Fig. 6.28.

Fig. 6.28. ΔE^el vs. number of openings (ξ).

Here, it is possible to note that the trend of ΔEel versus ξ shows a maximum value. This behaviour is caused by different significant aspects, playing opposite roles on the electrical needs. In particular, the increase of the number of openings implies:

i) the variation of the heat pump, COP^h, which depends on conditions of the air from the PV/T cavity channelled to the heat pump evaporator. Such conditions are characterized by the total air channel mass flor rate and by its average temperature, calculated at the outlet sections of the obtained parallel air channels. Note that by using multiple openings, the modular PV/T panels can be considered in parallel and series operation, thus, the total air channel mass flor rate increases as ξ increases, whereas the average air channel temperature decreases as ξ increases;

ii) the increase of the final electricity use due to fans, caused by the reduced stack effect inside the channel.

It is worth noting that as the number of ξ increases, the air flowing through the BIPV/T cavity is channelled to the HVAC system (heat recovery mode) with lower temperature and higher flow rate.

Nevertheless, as well known, the contribution of the BIPV/T system to the increase of the heat pumps COP^h (i.e. active effect) is limited to the operating flow rate and to the maximum temperature at the evaporator (i.e. 20°C as provided by manufacturers). Therefore, by taking into account a multiple openings strategy, the optimal number of openings depends on the trade-off between the increase of the COP (achieved with a suitable combination of outlet air temperature and flow rate) and the increase of electricity needs due to the multiple openings fans. As shown in Fig. 6.28, the maximum obtained ΔE^el is equal to 6.3% (at ξ = 15) in Naples and to 14.2% (at ξ = 6) in Freiburg.

Primary energy saving

Finally, it is interesting to assess the percentage variation of the primary energy saving (ΔPES) as a function of the number of multiple openings. The slight trend of ΔPES versus ξ is shown in Fig. 6.29.

Fig. 6.29. PES vs. number of openings (ξ).

This minor variation is mainly due to the primary energy linked to the PV electricity production and electrical loads, which smooth the influence due to the passive and active BIPV/T effects. The ΔPES

ranges from 100% (at ξ = 1) to 102.5% (at ξ = 30) in Naples (where the positive net ZEB goal is achieved), and from 72.8% (at ξ = 1) to 73.7% (at ξ = 30) in Freiburg.

Estimated trends of ΔQ, ΔEel,PV, ΔEel, and ΔPES versus ξ

The results obtained from the parametric analysis can be useful for designers and benchmark purposes, in case of the implementation of air open loop BIPV/T systems on the façade of new or refurbished buildings. To this aim, several equations, defined by the trends of ΔQ,ΔE^el,PV, ΔE^el, and ΔPES versus ξ, are estimated. Despite of the limitation of such approach, restricted to the case study building use and to the investigated BIPV/T system, such easy to use correlations can be taken into account as swift tools for the assessment of the percentage variation of heating and cooling requirements, PV electricity production, electrical needs, and primary energy savings, as a function of the number of openings on the BIPV/T façade.

In particular, for both the considered weather locations, by taking into account the trends of ΔQ^c andΔQ^h (see Fig. 6.25 and Fig. 6.26), and the one of ΔE^el,PV (see Fig. 6.27) versus ξ, a logarithmic profile is detected. In addition, very high root means square errors, R², are calculated, ranging from 94 to 99%. The obtained trends can be characterized by the logarithmic equation reported in Table 6.16. The table also provides the values of the coefficients a and b, to be selected as a function of the investigated parameter.

Similarly, the trends of ΔEel (see Fig. 6.28) and ΔPES (see Fig. 6.29) as a function of ξ show a parabolic profile, also detected with satisfactory R², ranging from 0.71 to 0.88%. The obtained trends can be estimated through the parabolic equation reported in Table 6.16. Also, in this case, the coefficients a, b, and c, are provided in the table as a function of the investigated parameter.

Table 6.16. Estimated equations and coefficients.

Equations Heating and cooling requirements PV electricity production

Electrical

needs Primary energy logarithmic trend: a∙ln(ξ) + b parabolic trend: a∙ξ²+b∙ξ+c Parameters Heating - ΔQh Cooling – ΔQc PV – ΔEel,PV HVAC – ΔEel,HVAC Building - ΔPES

Naples Freiburg Naples Freiburg Naples Freiburg Naples Freiburg Naples Freiburg

a -0.67 -0.34 25.2 2.52 0.42 0.24 -0.011 -0.015 -0.005 -0.004

b 1.97 13.3 3.80 9.50 -0.25 -0.04 0.45 0.28 0.22 0.13

c - - - - - - 2.22 12.5 100 72.8