phi_publications:pb_41:planning_tools_for_the_summer_situation_in_non-residential_buildings
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| phi_publications:pb_41:planning_tools_for_the_summer_situation_in_non-residential_buildings [2018/11/12 12:10] – cblagojevic | phi_publications:pb_41:planning_tools_for_the_summer_situation_in_non-residential_buildings [2019/09/09 13:24] (current) – [3.4 Use for critical rooms] cblagojevic | ||
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| ==== 2.1 Prologue: | ==== 2.1 Prologue: | ||
| - | [{{:picprivate:f1.png? | + | [{{:picopen:41_11.jpg? |
| Dynamic simulations calculate the thermal conditions in the building in time steps which are usually much less than one hour. Heat transfer processes in building components and the room are shown in detail. In contrast with this, there are energy balancing methods such as the annual and monthly method used in the PHPP or the DIN V 18599, which calculates the heating balance | Dynamic simulations calculate the thermal conditions in the building in time steps which are usually much less than one hour. Heat transfer processes in building components and the room are shown in detail. In contrast with this, there are energy balancing methods such as the annual and monthly method used in the PHPP or the DIN V 18599, which calculates the heating balance | ||
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| - | |{{:picprivate:f2.png? | + | [{{:picopen:41_12.jpg? |
| - | + | ||
| - | |**Figure 2: Example of utilisation factor and heat gains plotted against the gains/ | + | |
| The monthly method in the PHPP uses the utilisation factors in accordance with [EN 13790]. Experience with this calculation method for residential buildings has been excellent compared with the dynamic building simulation (for example, see [Feist 1998]), and it also proved successful for inhabited buildings as well as in the direct probation of inhabited buildings. | The monthly method in the PHPP uses the utilisation factors in accordance with [EN 13790]. Experience with this calculation method for residential buildings has been excellent compared with the dynamic building simulation (for example, see [Feist 1998]), and it also proved successful for inhabited buildings as well as in the direct probation of inhabited buildings. | ||
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| Two examples provide more information regarding the scope of application of this method. Figure 3 shows the calculated heating demand for the central room of the simulation model with a window on one side and insulation to the EnEV standard, calculated with consistent indoor conditions with various levels of internal gains and window area ratios. The calculation was carried out using the PHPP as well as the dynamic model in DYNBIL as the comparison standard. For the case without windows, it can be seen that there is excellent correlation between the simulation and energy balance method for all values for internal heat gains. The gradients only diverge noticeably in the case of larger window areas and extra high internal heat gains. | Two examples provide more information regarding the scope of application of this method. Figure 3 shows the calculated heating demand for the central room of the simulation model with a window on one side and insulation to the EnEV standard, calculated with consistent indoor conditions with various levels of internal gains and window area ratios. The calculation was carried out using the PHPP as well as the dynamic model in DYNBIL as the comparison standard. For the case without windows, it can be seen that there is excellent correlation between the simulation and energy balance method for all values for internal heat gains. The gradients only diverge noticeably in the case of larger window areas and extra high internal heat gains. | ||
| - | [{{:picprivate:f3.png? | + | [{{:picopen:41_13.jpg? |
| Principally, | Principally, | ||
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| Altogether, in the energy balance method, the utilisation factor appears to have been calculated a little too low with constantly free heat (i.e. dominating constant IHG), and a little too high with temporally concentrated free heat. Thus, in typical cases both influences balance each other out and the heating demand according to the PHPP correlates with the simulation. | Altogether, in the energy balance method, the utilisation factor appears to have been calculated a little too low with constantly free heat (i.e. dominating constant IHG), and a little too high with temporally concentrated free heat. Thus, in typical cases both influences balance each other out and the heating demand according to the PHPP correlates with the simulation. | ||
| - | |{{:picprivate:f4.png? | + | ---- |
| - | |**Figure 4: Comparison of the calculated heating demand for the corner office in the Passive House standard according to the simulation and the PHPP** | + | |
| + | |{{:picopen:41_010.jpg? | ||
| + | |**Figure 4: Comparison of the calculated heating demand for the corner office in the Passive House standard according to the simulation and the PHPP** | ||
| ====2.2 Useful cooling demand ==== | ====2.2 Useful cooling demand ==== | ||
| - | [{{:picprivate:f6.png? | + | [{{:picopen:41_15.jpg? |
| The principle of energy balancing using a utilisation factor works not only for heating but also for cooling. In the Central European climate, periods requiring cooling, as well as periods without a cooling demand, arise on many days during the summer. Figure 6 illustrates this situation. | The principle of energy balancing using a utilisation factor works not only for heating but also for cooling. In the Central European climate, periods requiring cooling, as well as periods without a cooling demand, arise on many days during the summer. Figure 6 illustrates this situation. | ||
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| - | | {{: | + | |{{: |
| - | |**Figure 7: Comparison of the calculated useful cooling demand for a centre office to the EnEV standard, according to the simulation and the PHPP** | + | |**Figure 7: Comparison of the calculated useful cooling demand for a centre office to the EnEV standard, according to the simulation and the PHPP** |
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| Based on Figure 9, utilisation as a seminar room was therefore considered in addition. Internal heat loads of 25 W/m² prevail from Monday till Friday afternoon, during the highest outdoor temperatures, | Based on Figure 9, utilisation as a seminar room was therefore considered in addition. Internal heat loads of 25 W/m² prevail from Monday till Friday afternoon, during the highest outdoor temperatures, | ||
| - | |{{: | + | |{{: |
| - | | **Figure 9: Temperature curve for seminar room usage with intensive nighttime ventilation and respective cooling output** | + | | **Figure 9: Temperature curve for seminar room usage with intensive nighttime ventilation and respective cooling output** | **Figure 10: Comparison of the calculated useful cooling demand for a centre office to the Passive House standard with seminar room use according to the simulation |
| As can be seen in Figure 10, the energy balance method functions perfectly well even in this situation. This is astounding, given the fact that information regarding temporal distribution of the internal loads is not available in the PHPP at all. | As can be seen in Figure 10, the energy balance method functions perfectly well even in this situation. This is astounding, given the fact that information regarding temporal distribution of the internal loads is not available in the PHPP at all. | ||
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| According to these results, the cooling load method of the PHPP is suitable for buildings with minimised loads, i.e. a good level of solar protection and internal loads that are either small or uniformly distributed in time. In these cases it provides enough reliability to compensate for some of the temperature fluctuations occurring during the course of the day. If loads are so high that daily buffering is no longer possible, then a method with higher time resolution will have to be used. | According to these results, the cooling load method of the PHPP is suitable for buildings with minimised loads, i.e. a good level of solar protection and internal loads that are either small or uniformly distributed in time. In these cases it provides enough reliability to compensate for some of the temperature fluctuations occurring during the course of the day. If loads are so high that daily buffering is no longer possible, then a method with higher time resolution will have to be used. | ||
| - | |{{: | + | |{{: |
| - | |**Figure 11: Cooling load plotted against the internal heat load according to different calculation methods - without windows** | + | |**Figure 11: Cooling load plotted against the internal heat load according to different calculation methods - without windows** | **Figure 12: Cooling load plotted against the internal heat load according to different calculation methods - ribbon window facade** |
| - | |{{: | + | |{{ : |
| - | | **Figure 13: Cooling load plotted against the internal heat load according to different calculation methods - fully glazed facade**\\ //EnEV, Mitte...=EnEV, | + | | **Figure 13: Cooling load plotted against the internal heat load according to different calculation methods - fully glazed facade**| **Figure 14: Cooling load plotted against the internal heat load according to different calculation methods. Here the daily mean values from Figures 11 to 13 are summarised supplemented with the results of the simulation for the extreme summer** | |
| =====3 Frequency of overheating ===== | =====3 Frequency of overheating ===== | ||
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| Since temperature fluctuations are relevant for calculation of the frequency of overheating, | Since temperature fluctuations are relevant for calculation of the frequency of overheating, | ||
| - | [{{: | + | [{{ : |
| In order to be able to show the influence of individual hot days as well, and to obtain meaningful results for small overheating frequency values, the month of July is additionally divided into several parts: the cooling load day at the end of the month, the four preceding days with slightly lower temperatures and radiation values, another twelve preceding days with lower temperatures and radiation values once more, and the then the rest of the month. In the process, the month is divided in such a way that the monthly average values for the outdoor temperature and solar incidence for July remain unchanged. The average values for the indoor temperature are also determined in the same way for these shorter periods. | In order to be able to show the influence of individual hot days as well, and to obtain meaningful results for small overheating frequency values, the month of July is additionally divided into several parts: the cooling load day at the end of the month, the four preceding days with slightly lower temperatures and radiation values, another twelve preceding days with lower temperatures and radiation values once more, and the then the rest of the month. In the process, the month is divided in such a way that the monthly average values for the outdoor temperature and solar incidence for July remain unchanged. The average values for the indoor temperature are also determined in the same way for these shorter periods. | ||
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| There is a similar tendency for high loads with 9 W/m². However, for air change rates higher than 3 h< | There is a similar tendency for high loads with 9 W/m². However, for air change rates higher than 3 h< | ||
| - | |{{: | + | |{{ : |
| - | |**Figure 16: Example with frequency of overheating plotted against air change rate in summer for low internal heat loads** | + | |**Figure 16: Example with frequency of overheating plotted against air change rate in summer for low internal heat loads** |
| ==== 3.2 Conversion to usage period? ==== | ==== 3.2 Conversion to usage period? ==== | ||
| - | [{{: | + | [{{: |
| In non-residential buildings, the question of whether all hours with overheating fall within the usage period arises on account of the intermittent usage. If that was the case, then the frequency of overheating | In non-residential buildings, the question of whether all hours with overheating fall within the usage period arises on account of the intermittent usage. If that was the case, then the frequency of overheating | ||
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| Based on the entire year and the usage period, the overheating frequencies can differ considerably depending on the air change rates which are possible in summer. Conversion with the ratio of usage period to the entire year would also give pessimistic results, but the difference is no longer as great. The reason for this can be seen in the upper chart in Figure 19, where the temperature curve for high summer air change rate is shown. The excessive temperatures actually occur almost exclusively during the usage period. | Based on the entire year and the usage period, the overheating frequencies can differ considerably depending on the air change rates which are possible in summer. Conversion with the ratio of usage period to the entire year would also give pessimistic results, but the difference is no longer as great. The reason for this can be seen in the upper chart in Figure 19, where the temperature curve for high summer air change rate is shown. The excessive temperatures actually occur almost exclusively during the usage period. | ||
| - | |{{ : | + | |{{ : |
| |**Figure 19: Example with frequency of overheating plotted against air change rate in summer for high internal heat loads and seminar room usage. The simulation results are also shown with reference to the operating times, the PHPP results were converted using the factor tYear/tUse | |**Figure 19: Example with frequency of overheating plotted against air change rate in summer for high internal heat loads and seminar room usage. The simulation results are also shown with reference to the operating times, the PHPP results were converted using the factor tYear/tUse | ||
| - | The chart above shows the temperature curve in summer and the usage period for high air change rates in May.** | + | The chart above shows the temperature curve in summer and the usage period for high air change rates in May.** | |
| ==== 3.3 Accuracy limits for calculating the frequency of overheating ==== | ==== 3.3 Accuracy limits for calculating the frequency of overheating ==== | ||
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| These examples demonstrate that it is generally not possible to make statements regarding thermal comfort in summer which are more precise than those derived from the categories in Table 1. It is difficult to predict even the summer air change rate, because according to the system, it depends more or less on user behaviour. The outside temperatures and wind speeds which are influenced by the microclimate also affect the removal of heat through night-time ventilation. The year-to-year fluctuations in weather are not subject to any influence in any case. | These examples demonstrate that it is generally not possible to make statements regarding thermal comfort in summer which are more precise than those derived from the categories in Table 1. It is difficult to predict even the summer air change rate, because according to the system, it depends more or less on user behaviour. The outside temperatures and wind speeds which are influenced by the microclimate also affect the removal of heat through night-time ventilation. The year-to-year fluctuations in weather are not subject to any influence in any case. | ||
| - | |{{: | + | |{{ : |
| - | |{{: | + | |{{ : |
| - | |{{: | + | |{{ : |
| |**Figure 20: Temperature curve in an example room according to weather and air change rate**| | |**Figure 20: Temperature curve in an example room according to weather and air change rate**| | ||
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| In the opposite case, individually considering a room is just as inadequate (Figure 22). Taken alone, summer thermal comfort in the room under consideration is excellent. However, if the adjacent rooms are intensely uncomfortable on account of full glazing and high internal heat loads, then this will also affect the centre room being examined; the frequency of overheating is now 13%. | In the opposite case, individually considering a room is just as inadequate (Figure 22). Taken alone, summer thermal comfort in the room under consideration is excellent. However, if the adjacent rooms are intensely uncomfortable on account of full glazing and high internal heat loads, then this will also affect the centre room being examined; the frequency of overheating is now 13%. | ||
| - | |{{: | + | |{{: |
| - | |{{ : | + | |{{: |
| - | frequency of overheating 4%, maximum temperature 28 °C** \\ // Außentemperatur=outdoor temperature, | + | frequency of overheating 4%, maximum temperature 28 °C**| |
| |**Figure 21: Temperature curve as a function of adjacent rooms, part 1**| | |**Figure 21: Temperature curve as a function of adjacent rooms, part 1**| | ||
| - | |{{: | + | |{{: |
| - | |{{: | + | |{{: |
| |**Figure 22: Temperature curve as a function of adjacent rooms, part 2**| | |**Figure 22: Temperature curve as a function of adjacent rooms, part 2**| | ||
phi_publications/pb_41/planning_tools_for_the_summer_situation_in_non-residential_buildings.1542021043.txt.gz · Last modified: 2018/11/12 12:10 by cblagojevic