Energy savings evaluation for dry-cooler equipped plants in shopping mall buildings

A rectangular double floor building with a gross floor area of 20000 m² and a height of 4 m were considered. The total volume is 160000 m³. Fig. 1-a shows the internal layout of a building floor.

The longer edge of building is oriented along north-south axis and the entrance glass doors are on two shorter edges.

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Figure 1. Floor plan for the simulated building with using destination (a), and thermal zones (b)

With reference to internal layout, shops take up perimetral and core zones and occupy 60% of the total floor area, leaving 40% of the floor area to a common zone in order to allow a suitable space for the flow of people during the peak time.

Initially, it has been modeled horizontal skylights, but in this way gains of solar radiation were very high; so, a shed roof with 12 vertical skylights, 0.70 x 2.5m, has been chosen.

Taking into account the relevant dimension of building, different thermal zones, that have the same internal load and the same heat losses through wall, were set. For each floor different zones, perimeter zones and one core zone, summarized in Fig. 1-b, were considered.

In this way it is possible to predict the thermal performance of any thermal zone in the building and the total building thermal performance is defined according to an assessment related to its thermal zones.

The model of the building, shown in Fig. 2, was created with TRNBuild module.

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Figure 2. Sketch of the simulated commercial mall

Two different walls and two different slabs were defined:

  ♦ external wall

  ♦ inner wall

  ♦ ground floor

  ♦ middle floor

  ♦ external ceiling

The building elements properties were summarized in Table 1.

Table 1. Building elements construction details

The window glazing value U_w was assumed to be 5,8 W/m²K.

Daily and hourly schedules were adopted to control the infiltration, occupation, internal gains and HVAC system. In commercial malls the main internal loads are those due to people and lights, therefore it is very important to know opening times and people turnout.

In order to carry out more realistic simulations, existing shopping malls with their opening times were considered. Shopping malls, listed in Table 2, are located at the same places chosen for the simulations.

Table 2. Opening times of existing shopping malls

The evaluation of electrical equipment loads was carried out according to ASHRAE Standard guidelines (Table 3) and, assuming a low load, it has been considered a value of 30 W/m² thinking of a shop inside a shopping mall has a higher electrical load than a single shop.

Table 3. Electrical loads – Ashrae

Electrical load was split in a radiative part (30%) and a convective part (70%).

Thermal load of electrical equipment were calculated as product of electrical power, interval time and a coefficient depending on the day of the week; the coefficient was set to 1 during opening hours and to 0,2 during closing hours in order to account for stand-by conditions.

On zones where there are skylights, windows or entrance doors, a infiltration rate equal to 0,5 ACH (Air Changes per Hour) was imposed.

The definition of the number of people inside shopping mall was carried out according to UNI10339-2014 and, for each building, a design value of crowding index equal to 0,2 person/m² was considered both sale zone and common zone. The peak value was scaled down based on daily and weekly schedule of occupant’s presence.

The fraction of the design value is defined as the ratio of the actual load to the peak or maximum load.

Human sensible and latent heat loads from people depend on their activity and, with reference to ISO7730, assuming a light activity for shopping mall, a load of 185 W for each person (90 sensible and 95 latent) was chosen.

4.1 Trnsys model

Dynamic simulation of commercial mall using three different cooling plant configurations is carried out in TRNSYS software on hourly basis.

After drawing the 3D model of the building by means of TRNSYS3D, a plug-in of Sketchup software, and defining internal characteristics and conditions of building in TRNBUILD, all the components of cooling plant are modeled in TRNSYS Studio to run the simulations for three different systems:

  ♦ cooling plant with a vapor compression system

  ♦ cooling plant with a vapor compression system combined with an indirect free cooling system (working all day long); the cooling plant can works with a traditional mode or with a free cooling mode if the external weather conditions are suitable

  ♦ cooling plant with a vapor compression system combined with an indirect free cooling system (working from 7 am to 11 pm)

TRNSYS performs cooling load calculations with transfer function method by using weather and building information data. Simulations were carried out using an ideal air conditioning system, assuming set points for cooling and heating 24 and 20°C respectively.

The TRNSYS model has been implemented using the following type:

  ♦ Building (Type 56)

  ♦ Weather data (Type 15-3)

  ♦ Fan coil (Type 600)

  ♦ Chiller (Type 666)

  ♦ Dry Cooler (Type 511)

Different climatic conditions are investigated considering ten European cities (Fig. 4):

  ♦ Hamburg (Germany)

  ♦ Geneva (Switerland)

  ♦ Madrid (Spain)

  ♦ Messina (Italy)

  ♦ Milan (Italy)

  ♦ Munich (Germany)

  ♦ Paris (France)

  ♦ Prague (Czech Republic)

  ♦ Warsaw (Poland)

  ♦ Wienn (Austria)

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Figure 4. European cities considered in simulations

In order to choose cities with different weather conditions, the Cooling Degree-Hours, Base J₀ (CDH_J₀), has been considered as discriminating factor; the index is proposed by ASHRAE [9] and is defined as:

$C D H_{-} \vartheta_{0}=\sum_{j=1}^{N}\left(\vartheta_{e}-\vartheta_{0}\right)$ for $\vartheta_{e}-\vartheta_{0}>0$

where J_e is the hourly dry bulb temperature, N is the number of hours for entire year and J₀ is the base temperature.

According to the design value of the internal air temperature, suggested by International Standards [10] for the summer period, a base temperature equal to 26°C has been used to evaluate the parameter CDH_26. Fig. 5 shows the CDH_26 for the different cities considered.

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Figure 5. CDH_26 for the different cities considered

4.2 Chiller performance

The chiller has been considered as a high performance centrifugal compressor chiller with condenser cooled by water. It has been modeled by means of TRNSYS Type 666, which allows to take into account the influence of external climatic conditions over the chiller performance. Figure 6 shows the variation of EER values for different chilled water temperatures, varying the cooling water temperature.

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Figure 6. EER trend over cooling water inlet temperature for different outlet temperatures of the chilled water

4.3 Free cooling

Cooling plant have to work in free cooling mode only under suitable conditions, that are:

  ♦ temperature gradient between internal air and external air have to be greater than 10 K;

  ♦ fan-coils have to be switched on.

In particular the first condition takes into account that water have to pass through two heat exchangers and therefore the temperature difference have to be greater than 10 K.

In the present study have been investigated the advantages, in terms of energy saving, achievable by means of the integration of an indirect free cooling system in a traditional cooling plant used for a shopping center cooling.

In particular, the dry-cooler units could be used alternatively to cool down the refrigerant flow, or the water supplied to fan coils, achieving in such a way an indirect free cooling. Under suitable weather conditions, the proposed system allows to turn off the chiller and allows to save electrical energy.

A commercial mall with both a dry-cooler equipped cooling plant and a traditional one has been simulated by means of TRNSYS, and the results have been compared in terms of number of hours in which the chiller could be turned off and amount of energy saving. Different weather data (northern, central and southern European cities) have been considered for the simulations.

Simulations show that among the considered locations the city with the greatest annual energy saving amount (42.4%) is Hamburg, whereas the city with the lowest annual energy saving amount (14.2%) is Messina. As it is reasonable to expect, in cities with a colder climate there is a greater energy saving due to a lower value of the external mean air temperature; for the same reason, during the winter the proposed system is more useful.

Further investigations will be carried out taking in to account different thermal characteristics of the building envelope; a more insulated building requires a lower cooling load, which can be more likely supplied employing the external air. Moreover, it will consider the latent heat that have to be disposed of.