Dealing with heat waves: can I use the PHPP to size cooling equipment?

The issue of correctly sizing cooling equipment is key if we are to maintain thermal comfort, at low power

The article looks at using the PHPP for sizing cooling equipment and compares results with multi-zone calculations using dynamic simulation

Given ever more frequent heat waves and the increasing need for active cooling in Passivhaus residential buildings, the issue of correctly sizing cooling equipment is key if we are to maintain thermal comfort, at low power. Over-sizing of cooling plant adds unnecessary cost and energy consumption, increasing stress on power grids as they try and meet peak loads, especially under heat wave conditions. Under-sizing cooling plant will lead to comfort problems, failed expectations and a performance gap that Passivhaus buildings have been consistently shown to fill. Once the work has gone into creating a working PHPP model, can we safely use the tool to size cooling kit?

The article looks at using the PHPP for sizing cooling equipment and compares results with multi-zone calculations using dynamic simulation, based on a simple worked example of a completed and certified Passivhaus residential building in climate zone 5-Warm. The research was prompted by the (painful) lessons learned some years ago, when using the PHPP to size cooling equipment for a single-family low-energy home with Passivhaus components, without adequate modification of boundary conditions. The home had active cooling but suffered from overheating problems and complaints from occupants.

How does PHPP calculate cooling loads?

PHPP calculates sensible and latent cooling loads as the maximum daily average cooling power required to maintain the operative temperature set point, providing an average cooling load across the whole building, based on maximum daily average outdoor air temperature, dew point, sky temperature and solar radiation. Occupancy gains are typically based on a default setting (e.g., for TFA = 150m², occupancy ratio = 51 m²/p, occupancy = 2.9 people. 

How does a dynamic simulation tool calculate cooling loads?

Dynamic simulation tools allow for a multi-zone calculation based on hourly climate data, occupancy activity, and equipment operation, providing a time-dependent, high-resolution calculation of cooling loads. Typically, solar gains are calculated on an hourly time-step, and occupancy gains are computed dynamically, such that latent gains increase, and sensible gains decrease, as indoor operative temperature increases (people begin to sweat more as indoor temperature increases…). Is this level of accuracy really necessary, or can we use the PHPP to size cooling plant?

Which kind of tool should I use to size cooling equipment?

Finding the right answer to the question involves asking some the following questions: what building typology are we dealing with? What are the local short-term climate conditions, over 24 hours, during the hottest days? What is the occupancy density of the building, what are the internal heat gains and solar gains, and at what time in the day do they occur? Logically, a single zone, quasi-steady state calculation method such as the one found in PHPP, will be pushed to its limits for larger buildings and/or those with short-term peak gains derived from solar radiation, occupancy or equipment use, particularly if they vary greatly from one zone to the other.

Worked example: PHPP vs. dynamic simulation cooling load calculation for single-family home

Table 1 and Figure 2 shows peak cooling load results per zone, for a single-family certified Passivhaus in Mallorca, Spain, with a TFA of 170m², comparing a dynamic multi-zone calculation using DesignBuilder/EnergyPlus, with PHPP single-zone results. The PHPP climate file for the energy balancing calculations is ES0022b-Palma de Mallorca, but the climate file boundary conditions have been adjusted in the PHPP for the conditions shown in Figure 1 (derived from an hourly data set generated by Meteonorm v.7), with an outdoor air temperature of 38.1ºC and a dew point temperature of 27.2ºC (taken from the average 24-hour relative humidity of 54% @ 38.1ºC dry air temperature). The following adjustments were also made in the PHPP: the occupancy was increased to 10 people, the cooling set-point was reduced to 24ºC, and the solar factor of the glazing was increased by 5% (to eliminate the default soiling factor included in the Glazing worksheet), in agreement with the boundary conditions used in the dynamic calculation.

Figure 1: Climate conditions for cooling load calculation

Figure 2: Results of total cooling loads

The results shown in Table 1 and Figure 2 indicate a negligible 1% difference in the total average peak cooling load results at building level, between the dynamic multi-zone calculation and the PHPP results, suggesting that if the PHPP boundary conditions are modified from those used for building certification, the tool can be safely used for sizing cooling equipment for small residential buildings. This approach has been used on many projects of this type for many years with no complaints of overheating from occupants. However, if we look at peak cooling loads on a zone-to-zone basis, they vary by a + 68% (toilet) and -58% (corridor). While this has generally not been found to be a problem in practice in single-family homes, this suggests caution is required with larger buildings or for zones in smaller buildings with higher short-term peak gains (from solar radiation, occupancy or equipment use). Also, cooling distribution must be carefully planned to ensure specific zones don’t suffer from overheating and sufficient heat is removed from each zone.

Finally, the correct sizing of refrigeration equipment is important for the following reasons:

• Oversized cooling equipment leads to higher than necessary energy consumption and therefore increased energy bills.
• If cooling power is much higher than necessary, the setpoint temperature is reached earlier and the equipment shuts down (under orders from a thermostat, which only understands temperature, not humidity). This can lead to comfort problems due to excessively high indoor humidity.

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