# Exergy performance and optimization potential of refrigeration plants in free cooling operation

Lorenz Brenner<sup>a, b</sup>, Frank Tillenkamp<sup>a, *</sup>, Christian Ghiaus<sup>b</sup>

<sup>a</sup>Zurich University of Applied Sciences (ZHAW), Institute of Energy Systems and Fluid-Engineering (IEFE), Technikumstrasse 9, CH-8401 Winterthur, Switzerland

<sup>b</sup>INSA-Lyon, CETHIL UMR5008, 9 rue de la physique, F-69621 Villeurbanne, France

## Abstract

Exergy analysis has been widely used to assess refrigeration systems by evaluating exergy losses or exergy efficiency. The latter is mostly used as an indicator to determine the system performance, which requires the comparison of the actual system with its idealized reversible version, but not the practical achievable efficiency. Therefore, a practice-oriented evaluation method for refrigeration plants in free cooling operation is proposed, based on exergy analysis and technical standards as baseline. By considering the exergy input of auxiliary devices, the configuration of the hydraulic circuits and the hydraulic integration of the free cooling module in the refrigeration plant can be assessed. The achievable optimization potential compared to the state of the art in technology and the performance is revealed with the introduced optimization potential index (OPI). The application is demonstrated with a case study, where the analysis reveals an adequate operation of the field plant in general. Most cooling locations show potential for improvement, which is indicated by an OPI superior to zero. Moreover, the auxiliary electrical exergy input shows the same magnitude as the thermal exergy input, which emphasizes the importance of reducing the electrical energy usage of auxiliary devices in refrigeration plants to increase the performance.

*Keywords:* optimization potential evaluation method, exergy analysis, vapor compression refrigeration plants, free cooling, optimization potential index, OPI

## Highlights

* The optimization potential index (OPI) for free cooling operation is proposed.

* The performance and optimization potential of subsystems is revealed.

* The evaluation method is presented.

* The application is shown with a case study.

* Simple indicator is realizable for implementation in monitoring systems.

<footnote>*Corresponding author
Email address: frank.tillenkamp@zhaw.ch (Frank Tillenkamp)</footnote>
## Nomenclature

### Abbreviations

<table><tr><td>CL</td><td>subsystem cooling location</td></tr><tr><td>COP</td><td>coefficient of performance</td></tr><tr><td>CST</td><td>subsystem cold storage & transport</td></tr><tr><td>DC</td><td>subsystem dry cooler</td></tr><tr><td>FC</td><td>subsystem free cooling</td></tr><tr><td>HVAC</td><td>heating, ventilation and air-conditioning</td></tr><tr><td>OPI</td><td>optimization potential index</td></tr><tr><td>RM</td><td>subsystem refrigeration machine</td></tr><tr><td>SIA</td><td>Swiss society of engineers and architects</td></tr><tr><td>VDMA</td><td>mechanical engineering industry association</td></tr></table>

### Variables

<table><tr><td>B</td><td>exergy [J]</td></tr><tr><td>dot B</td><td>exergy flow rate [W]</td></tr><tr><td>b</td><td>specific exergy [J/kg]</td></tr><tr><td>f</td><td>amplification factor [-]</td></tr><tr><td>dot m</td><td>mass flow rate [kg/s]</td></tr><tr><td>p</td><td>pressure [Pa]</td></tr><tr><td>Q</td><td>thermal energy [J]</td></tr><tr><td>dot Q</td><td>heat flow rate (thermal power) [W]</td></tr><tr><td>T</td><td>temperature [K]</td></tr><tr><td>t</td><td>time [s]</td></tr><tr><td>V</td><td>volume [m³]</td></tr><tr><td>W</td><td>electrical energy [J]</td></tr><tr><td>dot W</td><td>electrical power [W]</td></tr></table>
Subscripts

0 reference state for exergy analysis

amb ambient

CL cooling location

CP circulating pump

CPR compressor

CST cold storage & transport

D distribution

DC dry cooler

el electrical

ex exergetic

FC free cooling

HE heat exchanger

in component / system input

kin kinetic

L loss / destroyed

m mass

out component / system output

pot potential

rev reversible

th thermal

w work

Superscripts

* reference value according to technical standards

Greek letters

ΔT temperature difference [K]

η efficiency [-]
# 1. Introduction

In order to evaluate and reduce the energy consumption in buildings, e.g. heating, ventilation and air-conditioning (HVAC) systems, different approaches were applied. One suitable method is the concept of exergy. In the last couple of years, several exergy-based investigations were carried out in the field of building technologies, namely heat pumps [1, 2], HVAC [3, 4], photovoltaics [5, 6], building energy systems [7, 8] and refrigeration systems [9, 10].

In a thermodynamic viewpoint, exergy can be seen as the unrestrictedly convertible portion of energy (maximum mechanical energy), which can be obtained from any form of energy by reversible interaction with the environment [11]. Exergy can also be identified as the quality of energy or available energy. In comparison to energy, exergy is destroyed in real (irreversible) thermodynamic processes, such as heat transfer in a heat exchanger. This represents a loss in energy potential to produce work. Such losses are the key for optimization, as their location and magnitude can be identified throughout systems and subsequently countermeasures may be initialized. In the case of thermal energy, the exergy amount of the latter is bound to the temperature level of the investigated system. If there is no work extracted from the system, e.g. in the present case the free cooling operation of the refrigeration plant, the exergy flows and the heat transfer in the hydraulic circuits are of importance. A low amount of thermal exergy transferred in the subsystems, e.g. due to a low temperature difference, implies a higher mass flow rate of the fluid in the distribution networks. This results in an elevated exergy input of the circulating pumps due to the increased frictional losses in the piping. Furthermore, thermal and electrical energy are comparable with the exergy method, as it is always referred to the same quantity. Thus, the relationship between mass flow rate and temperature level can be examined. Exergy analysis allows a deep insight in the different energy flows and the corresponding losses of thermodynamic systems which is not feasible with a purely energetic analysis.

Refrigeration systems in air-conditioning applications are one key component to generate the desired cooling in buildings. With the goal to increase their overall efficiency, different concepts were introduced and applied to assess the energy and exergy utilization. Shan *et al.* proposed an improved chiller sequence control strategy for refrigeration plants with centrifugal chillers [12]. Typically, an optimal sequencing of the refrigeration machine operation can improve the plant efficiency and therefore, reduce the electrical energy consumption. The authors showed an energy saving potential of 3% in comparison to the original control strategy. In another study, free cooling for a data center in a hot summer and warm winter region with a cooling load of approximately 10 MW was evaluated [13]. If the surrounding air temperature is substantially lower than the temperature in the refrigeration system, the use of free cooling (coupling of the consumer and hot water circuits by means of a heat exchanger arranged in parallel to the refrigerating machine) is feasible and the power consumption of the compressors can be economized. The authors found an annual system coefficient of performance (COP) increase from 5.9 to 7.3 and an energy saving rate of 19.2% if free cooling is fully utilized. Sorrentino *et al.* proposed a model-based key performance indicator (KPI), based on a reference energy efficiency index, to assess the performance of telecommunication cooling systems [14]. The authors
mention two possible applications of the KPI. On the one hand, the key figure may be used to assess the cooling efficiency of the system, meaning to determine if the actual cooling strategy is convenient or not. On the other hand, the key figure may be used as a tool for model-based diagnostics. By comparing the measured (actual) cooling system power consumption to a simulated (reference) one, a fault detection can be realized. This reduces the risk of cooling device failure or an increased energy consumption can be avoided. Fan et al. evaluated the performance of an HVAC system in an airport terminal building and determined the influence of different control strategies [4]. Firstly, by means of a simulation model of the building and HVAC system as well as exergy analysis, the exergy efficiencies and exergy loss ratios were determined for every component in the system (cooling tower, chillers and AHU with secondary pump). By investigating the yearly values, it was found that the AHU has the highest optimization priority, followed by the chillers. In order to evaluate the system performance over a certain time period in the setting of different control strategies with respect to an ideal operating level, the control perfect index (CPI) was introduced. In the study, the ideal operating level was determined with a particle swarm optimization (PSO) algorithm and three different control strategies (original, optimal load allocation and optimal supply air temperature reset) were assessed. The highest yearly CPI value of 0.82 was reached with the optimal load allocation strategy in comparison to 0.77 with the original one.

Regarding vapor compression refrigeration plants, the interest extents from the refrigeration machine itself to the neighboring subsystems. In practice, a well-suited hydraulic integration of the chiller or free cooling module is crucial in order to achieve a highly performing plant. By including the auxiliary devices in the exergy analysis, the performance of secondary hydraulic circuits can be assessed likewise [15]. A study investigated the energy savings if variable drives for cooling tower fans are implemented [16]. The system performance was compared to the dual speed mode, where the fan speed automatically switches between a low and a high rotational frequency depending on the needed water temperature leaving the cooling tower. Results showed that with a variable frequency drive, the water consumption was shortened by 13%. For the same cooling load, the overall energy consumption of the refrigeration plant was reduced by 5.8%. Furthermore, it can be beneficial to partition the refrigeration plant into different subsystems. With this method, the exergy analysis reaches an increased level of detail. The key figures, e.g. the exergy efficiency, can be determined for every subsystem and each of them can be assessed individually. The approach to partition the investigated system into subsystems was applied by Harrell et al. to assess the performance of a chilled water system of a campus [9]. The authors found the highest system exergy efficiency of 0.13 at an evaporator cooling load of 70%. By dividing the refrigeration plant into four different subsystems (heat rejection, steam turbine drive, refrigeration machine and chilled water distribution), they were able to determine the exergy loss ratio in each of them. The most significant exergy losses of 42 and 31% were discovered in the stream turbine drive and refrigeration machine, respectively. A detailed exergy analysis of a ground-source heat pump was carried out by Menberg et al. [2]. The system was evaluated with 8 subsystems in heating as well as 6 subsystems in cooling operation. The exergy performance was analyzed by applying 6 different key figures in the form of exergy efficiencies, e.g. the ratio of exergy output to non-natural exergy input, or exergy ratios, e.g. the ratio
of natural exergy input to total exergy input. The investigation examined the exergy flow path from the input to the output and revealed the exergy losses in the different subsystems. The exergy consumption in cooling mode is mentioned to be approximately 2.71 kW compared to 7.62 kW in heating mode at design conditions. The authors state the need of additional research regarding variable boundary and system conditions, the investigation of different reference environment definitions and dynamic exergy evaluation. Another study focused on measuring concepts in order to evaluate the efficiency of refrigeration plants with an exergy-based approach [17]. Typically, an exergy analysis requires an increased amount of measured quantities. Therefore, they suggest using adequate system boundaries for the calculation and to use thermodynamic relations to compute missing variables where possible. Further, they state the need of achievable reference values in order to allow an absolute comparison, as they can vary across different refrigeration plants.

According to the literature search, the investigated refrigeration systems are mostly split into reasonable subsystems with respect to the available measurement data in order to allow a detailed assessment. The performance and optimization potential is then evaluated in terms of key figures. Typically, energy or exergy performance indicators are referred to a thermodynamic ideal, which is not achievable in practice. However, it is relevant for plant operators to identify the realizable improvements and to have reference values for an absolute comparison. Optimization potentials should be revealed, as measures which improve the system effectiveness most likely prevent frequent shortcomings during refrigeration plant operation. Therefore, a practice-oriented assessment method with technical standards as baseline is applied [18]. The aim of the present work is to introduce the method for refrigeration plants in free cooling operation, which, to the best of our knowledge, has never been applied before to such systems. First, the plant is divided into four different subsystems: dry cooler, free cooling, cold storage & transport and cooling location. An exergy analysis is then carried out and the optimization potential index (OPI) proposed for the free cooling configuration. This allows a straightforward determination of the performance and optimization potential of every subsystem in the refrigeration plant. With the OPI, a comparison between different refrigeration systems is possible and the reference can vary depending on the state of the art in technology, which is of great importance in practice. The assessment system is applied and its functionality demonstrated on a field plant as a case study.

## 2. Refrigeration plant

Fig. 1 shows schematically a typical refrigeration plant with cold water distribution and free cooling. Usually, multiple refrigeration machines are set up in parallel (e.g. redundancy) and multiple cooling locations are present. The piping & instrumentation diagram is not intended to show the ideal configuration, but to reveal the assignment of the auxiliary devices to the different subsystems. The definition of the latter is based on investigations regarding existing systems but can be chosen differently according to the needed degree of detail. The present study focusses only on the refrigeration system, meaning other building components such as the envelope are not considered.
<figure><img src="image_1.png" /><figcaption>Figure 1: Simplified piping & instrumentation diagram of a typical refrigeration plant with cold water distribution and free cooling divided into different subsystems. The exergy inputs and outputs in free cooling operation are depicted with arrows and measured variables shown in italic (for details see Table 1 and 2).</figcaption></figure>

In refrigeration machine operating mode, the cold is generated by a refrigeration cycle (subsystem refrigeration machine RM), where the cold is distributed over a secondary hydraulic circuit (subsystem cold storage & transport CST) to the cooling locations (subsystem cooling location CL). The heat from the cycle process is discharged over another secondary hydraulic circuit (subsystem dry cooler DC) with the aid of dry coolers. If the surrounding air temperature is substantially lower than the temperature in the refrigeration system, the use of free cooling is feasible. Typically, a free cooling module (subsystem free cooling FC), in the simplest form consisting of a heat exchanger, is arranged in parallel to the chillers. In free cooling operation, the coupling of the subsystem dry cooler (DC) and cold storage & transport (CST) allows an indirect cooling of the cooling location (CL) without the use of the refrigeration machines (RM). Thus, the electrical energy of the compressors can be economized. This free cooling operating mode is mostly present in the colder months over the year and is subject of the present analysis.

Moreover, the exergies of every subsystem in free cooling operation as well as the measured quantities for the computation are depicted in Fig. 1 (for details see Table 1 and 2). The arrows indicate the exergy flows and $B_L$ describes the exergy loss in every subsystem. The cooling location and dry cooler thermal exergy, $B_{CL}$ and $B_{DC}$, are not needed for the assessment but shown for completeness. $T_{amb}$ represents the ambient air temperature.
<table><caption>Table 1: Measured variables in each subsystem for the exergy calculation.</caption><thead><tr><th>Subsystem</th><th>Measured variables</th></tr></thead><tbody><tr><td>DC</td><td>Circulating pump electrical energy W<sub>CP,DC</sub><br>Dry cooler fan electrical energy W<sub>DC</sub></td></tr><tr><td>FC</td><td>Free cooling thermal energy Q<sub>FC</sub><br>Free cooling inlet temperature DC side T<sub>FC,DC,in</sub><br>Free cooling outlet temperature DC side T<sub>FC,DC,out</sub><br>Free cooling inlet temperature CST side T<sub>FC,CST,in</sub><br>Free cooling outlet temperature CST side T<sub>FC,CST,out</sub></td></tr><tr><td>CST</td><td>Circulating pump electrical energy W<sub>CP,CST</sub></td></tr><tr><td>CL</td><td>Cold distribution thermal energy Q<sub>D</sub><br>Cold distribution inlet temperature T<sub>D,in</sub><br>Cold distribution outlet temperature T<sub>D,out</sub></td></tr></tbody></table>

<table><caption>Table 2: Exergy inputs and outputs of each subsystem.</caption><thead><tr><th>Subsystem</th><th>Exergy input</th><th>Exergy output</th></tr></thead><tbody><tr><td>DC</td><td>Circulating pump exergy B<sub>el,CP,DC</sub><br>Dry cooler fan exergy B<sub>el,DC</sub><br>Free cooling exergy DC side B<sub>FC,DC</sub></td><td>Dry cooler exergy B<sub>DC</sub></td></tr><tr><td>FC</td><td>Free cooling exergy CST side B<sub>FC,CST</sub></td><td>Free cooling exergy DC side B<sub>FC,DC</sub></td></tr><tr><td>CST</td><td>Circulating pump exergy B<sub>el,CP,CST</sub><br>Cold distribution exergy B<sub>D</sub></td><td>Free cooling exergy CST side B<sub>FC,CST</sub></td></tr><tr><td>CL</td><td>Cooling location exergy B<sub>CL</sub></td><td>Cold distribution exergy B<sub>D</sub></td></tr></tbody></table>

For the present study, a field plant is examined, from which measurements were collected during the year 2018. The refrigeration plant is located in Winterthur, Switzerland and incorporates five refrigeration machines with a total cooling power of approximately 5 MW and ammonia (R717) as refrigerant. The plant supplies seven buildings with cold, from which three were integrated into the system in April 2018. Additionally, 11 circulating pumps are present, from which two are winter pumps for the free cooling operation, in order to transport the cold water through the distribution network. One free cooling heat exchanger is integrated to the system, while three dry coolers discharge the heat to the environment. As a result, 10 different subsystems are defined to analyze the free cooling operation. No data was registered of the circulating pumps in free cooling operation (winter pumps). As an approach, the electrical energy input is calculated under the assumption that they behave similarly as the circulating pumps in refrigeration machine operation.
### 3. Assessment approach

#### 3.1. Exergy balance and key figures

The rate of change of exergy $dB/dt$ over a control volume, e.g. over a subsystem in the refrigeration plant, can be written as [19, 20]:

$$ \frac{dB}{dt} = \underbrace{\sum_{i} \left(1 - \frac{T_0}{T_i}\right) \dot{Q}_i}_{\dot{B}_{th}} + \underbrace{\left(\dot{W} - p_0 \frac{dV}{dt}\right)}_{\dot{B}_w} + \underbrace{\sum_{j} \dot{m}_{in,j} b_{in,j} - \sum_{k} \dot{m}_{out,k} b_{out,k}}_{\dot{B}_m} - \dot{B}_L \quad (1) $$

where

* $\dot{Q}_i$ represents a heat flow rate in or out of the control volume,

* $T_i$ is the temperature at which the heat transfer takes place,

* $T_0$ corresponds to the reference temperature,

* $\dot{W}$ represents mechanical or electrical power in or out of the control volume,

* $p_0$ is the reference pressure,

* $dV/dt$ corresponds to the rate of change of the control volume,

* $\dot{m}_{in,j}$ and $\dot{m}_{out,k}$ represent the mass flow rates in and out of the control volume,

* $b_{in,j}$ and $b_{out,k}$ are the incoming and outgoing specific flow exergies, and,

* $\dot{B}_L$ corresponds to the exergy losses in the control volume due to irreversibilities.

By definition, mechanical energy is pure exergy, as it can be fully transformed into any other form of energy (e.g. heat). In contrast, thermal energy contains only a portion of exergy and cannot be fully transformed. By assuming steady-state, incompressible flow (liquid in the hydraulic circuits) and neglecting pressure losses over the system boundaries, Eq. 1 can be expressed as follows [8, 21]:

$$ 0 = \sum_{i} \left(1 - \frac{T_0}{T_i}\right) \dot{Q}_i + \dot{W} + \sum_{l} \left(1 - \frac{T_0}{\bar{T}_l}\right) \dot{Q}_l - \dot{B}_L \quad (2) $$

where the exergy transfer by mass flow is now expressed by the net heat $\dot{Q}_l$ transported over the system boundary with the incoming and outgoing mass flow and the logarithmic mean temperature $\bar{T}_l$ defined as:

$$ \bar{T}_l = \frac{T_{in,l} - T_{out,l}}{\ln\left(\frac{T_{in,l}}{T_{out,l}}\right)} \quad (3) $$

with $T_{in,l}$ the temperature of the incoming and $T_{out,l}$ the temperature of the outgoing mass flow, respectively. The exergy efficiency $\eta_{ex}$ is mostly used to assess the exergy performance of thermodynamic systems. The key figure can be evaluated by balancing the total exergy output $\dot{B}_{out}$ to the input $\dot{B}_{in}$ [22]:

$$ \eta_{ex} = \frac{\dot{B}_{out}}{\dot{B}_{in}} = 1 - \frac{\dot{B}_{L}}{\dot{B}_{in}} \quad (4) $$

which indicates how much exergy leaves the system compared to the input. The key figure reaches a value of 0 if the energy is completely degraded (only losses present) and 1 if a thermodynamic ideal process (no exergy losses) is considered. Since every real process is irreversible, exergy losses are to be expected and the need
to know the best process possible is appearing. This indicator allows a relative comparison between different processes with regard to the thermodynamic ideal, but there are no reference values available stating which exergy efficiency should be achieved with a certain process. Thus, the quantification of the performance and possible optimization potentials according to the state of the art in technology is problematic, which is of great importance in practice. For this reason, the optimization potential index (OPI) is applied which has the following general form [18]:

$$OPI = 1 - \frac{\eta_{ex}}{\eta_{ex}^*} = 1 - \frac{\frac{\dot{B}_{out}}{\dot{B}_{in}}}{\frac{\dot{B}_{out}}{\dot{B}_{in}^*}} = 1 - \frac{\dot{B}_{in}^*}{\dot{B}_{in}} \quad (5)$$

The OPI balances the effective exergy efficiency $\eta_{ex}$ according to measurement data with a reference efficiency $\eta_{ex}^*$ based on technical standards. The key figure describes the behavior of the real system in comparison with a reference system under identical operation conditions while the same exergy output $\dot{B}_{out}$ is achieved. Thus, the evaluation of a subsystem is carried out with the assumption that the adjacent subsystems perform identically. $\dot{B}_{in}$ and $\dot{B}_{in}^*$ describes the actual exergy input according to measurements and the reference exergy input according to technical standards, respectively. The interpretation of the results becomes straightforward when evaluating the OPI (see Fig. 2). If the actual exergy input of the subsystem is larger than the reference (meaning an increased input is required to achieve the same output), the OPI is larger than 0 and points out improvement potential. For example, assuming the circulation pump in the subsystem CST consumes an increased amount of electrical energy due to an unfavorable design of the hydraulic circuit. The total exergy input of the subsystem will be larger compared to the reference and the OPI reveals the issue with a value superior to 0. Conversely, the OPI delivers a value inferior to 0 if the actual exergy input is lower than the reference. Thus, no optimization potential according to the state of the art in technology is present. An OPI of 0 indicates that the technical requirements are met.

As for technical reasons, typically no physical data is available in real systems for the calculation of $B_{CL}$ (see Fig. 1) of the subsystem CL. Therefore, an alternative approach is applied for the latter in free cooling operation. Namely, the exergy input is set to be the same in the actual and in the reference condition, while the exergy output varies according to the technical standards. The latter is plausible from a thermodynamic viewpoint, as it is favorable for the subsystem, if more exergy is extracted compared to the reference operating condition. Thus, the interpretation of the OPI remains the same for the subsystem CL.

<figure><img src="image_2.png" /><figcaption>Figure 2: OPI scale with the corresponding operating conditions.</figcaption></figure>
## 3.2. Reference environment

Exergy describes the energy potential with respect to an environmental reference. Therefore, exergy evaluations require a proper definition of the latter. Torío et al. investigated different reference states for the building environment, where they recommend using the surrounding ambient air as reference [23]. The variable outdoor temperature was applied in other studies [24, 25]. However, other research stated to use a fixed and constant reference in order to carry out a consistent and reliable exergy analysis [26, 27]. Therefore, as a first approach, a constant reference temperature $T_0$ of 5 °C is used in the present study, which represents the averaged outdoor temperature of the months January to April and November to December 2018, according to measurements from the investigated field plant. While the definition of the reference environment may influence the absolute values of the exergy, the effect on the OPI is small, as the same reference temperature is used for the actual and reference exergy.

## 3.3. Subsystem evaluation

With the goal to achieve a daily assessment of refrigeration plants in free cooling operation, as the cooling load in air-conditioning applications typically exhibits a daily rhythm, a quasi-stationary approach is chosen. The exergy flow rates are determined and balanced over each subsystem. The needed quantities are calculated from measurement data, obtained with reference values from technical standards or determined with an exergy balance (see Eq. 2). Subsequently, the exergy flow rates are numerically integrated with the trapezoidal rule

<table><caption>Table 3: Proposed OPI definitions of every subsystem in free cooling operation of the refrigeration plant.</caption><thead><tr><th>Subsystem</th><th>Optimization potential index</th></tr></thead><tbody><tr><td>DC</td><td>OPI<sub>DC</sub> = 1 - <div style="display: inline-block; vertical-align: middle; text-align: center;"><div style="border-bottom: 1px solid black; padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> [B<sup>*</sup><sub>FC,DC</sub> + &sum;<sub>i</sub>B<sup>*</sup><sub>el,CP,DC,i</sub> + &sum;<sub>j</sub>B<sup>*</sup><sub>el,DC,j</sub>]</div><div style="padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> [B<sub>FC,DC</sub> + &sum;<sub>i</sub>B<sub>el,CP,DC,i</sub> + &sum;<sub>j</sub>B<sub>el,DC,j</sub>]</div></div> (6)</td></tr><tr><td>FC</td><td>OPI<sub>FC</sub> = 1 - <div style="display: inline-block; vertical-align: middle; text-align: center;"><div style="border-bottom: 1px solid black; padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> B<sup>*</sup><sub>FC,CST</sub></div><div style="padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> B<sub>FC,CST</sub></div></div> (7)</td></tr><tr><td>CST</td><td>OPI<sub>CST</sub> = 1 - <div style="display: inline-block; vertical-align: middle; text-align: center;"><div style="border-bottom: 1px solid black; padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> [&sum;<sub>i</sub>B<sup>*</sup><sub>D,i</sub> + &sum;<sub>j</sub>B<sup>*</sup><sub>el,CP,CST,j</sub>]</div><div style="padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> [&sum;<sub>i</sub>B<sub>D,i</sub> + &sum;<sub>j</sub>B<sub>el,CP,CST,j</sub>]</div></div> (8)</td></tr><tr><td>CL</td><td>OPI<sub>CL</sub> = 1 - <div style="display: inline-block; vertical-align: middle; text-align: center;"><div style="border-bottom: 1px solid black; padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> B<sub>D</sub></div><div style="padding: 0 5px;">&sum;<sub>t=0 h</sub><sup>24 h</sup> B<sup>*</sup><sub>D</sub></div></div> (9)</td></tr></tbody></table>
over the present measurement interval of 5 minutes. The corresponding exergies of each interval are then summed up over 24 h and the optimization potential index is evaluated on a daily basis.

Each subsystem of the field plant in free cooling operation is assessed separately with the described pro- cedure. Table 3 lists the proposed definitions of the optimization potential index of each subsystem under consideration, with the exergies according to Table 2. The exergies marked with an asterisk represent reference values computed with technical standards. The detailed approach is introduced below using the subsystem dry cooler (DC) as an example, whereby the OPI for the other subsystems is determined similarly using the corresponding measured variables from Table 1.

The $OPI_{DC}$ is proposed according to Eq. 6 (see Table 3), where the electrical exergy input of each present circulating pump and dry cooler fan is summed up. The free cooling exergy on the DC side $B_{FC,DC}$ is defined as:

$$B_{FC,DC} = Q_{FC} \left( 1 - \frac{T_0}{\bar{T}_{FC,DC}} \right) \qquad (10)$$

where $Q_{FC}$ represents the free cooling thermal energy, $T_0$ the reference temperature and $\bar{T}_{FC,DC}$ the logarith- mic mean temperature of the secondary circuit of the heat exchanger according to:

$$\bar{T}_{FC,DC} = \frac{T_{FC,DC,in} - T_{FC,DC,out}}{\ln\left(\frac{T_{FC,DC,in}}{T_{FC,DC,out}}\right)} \qquad (11)$$

with the inlet and outlet temperature $T_{FC,DC,in}$ and $T_{FC,DC,out}$ of the heat exchanger on the dry cooler side. By definition, electrical energy is pure exergy, and thus, the exergy of the dry cooler fans $B_{el,DC}$ is given by:

$$B_{el,DC} = W_{DC} \qquad (12)$$

with the dry cooler fan electrical energy $W_{DC}$. Correspondingly, the exergy of circulating pumps $B_{el,CP,DC}$ is defined by:

$$B_{el,CP,DC} = W_{CP,DC} \qquad (13)$$

with $W_{CP,DC}$, the respective electrical energy input of the circulating pumps. The reference exergy of the free cooling on the DC side $B_{FC,DC}^*$ is given with:

$$B_{FC,DC}^* = Q_{FC} \left( 1 - \frac{T_0}{T_{FC,DC}^*} \right) \qquad (14)$$

where $T_{FC,DC}^*$ represents the reference temperature of the free cooling module. As no reference temperatures for the inlet and outlet of the free cooling module according to technical standards are available, a definition similarly to Eq. 11 is not possible. Therefore, a calculation with the ambient air temperature as a basis and temperature differences according to technical standards as well as available measurements is proposed as a first approach:

$$T_{FC,DC}^* = T_{amb} + \Delta T_{HE} + \frac{T_{FC,DC,out} - T_{FC,DC,in}}{2} \qquad (15)$$

where $T_{amb}$ is the ambient air temperature and $\Delta T_{HE}$ the temperature difference between the secondary hydraulic circuit medium and the ambient air in the dry cooler heat exchanger. According to the technical
standard VDMA 24247-8 [28], a desirable temperature difference $\Delta T_{HE}$ of 6 K is defined. The reference exergy of the dry cooler fans $B_{el,DC}^*$ is proposed as follows:

$$B_{el,DC}^* = \frac{1}{f_{el,th,DC}} Q_{FC} \qquad (16)$$

with the electro-thermo amplification factor for dry cooler fans $f_{el,th,DC}$ (see Table 4). This factor determines the desirable amount of electrical energy consumed by auxiliary devices with respect to the transferred thermal energy. Similarly, the reference exergy of the circulating pumps $B_{el,CP,DC}^*$ is given by:

$$B_{el,CP,DC}^* = \frac{1}{f_{el,th,CP,DC}} Q_{FC} \qquad (17)$$

where $f_{el,th,CP,DC}$ represents the electro-thermo amplification factor for circulating pumps (see Table 4). The amplification factors are defined in the technical standard SIA 382/1 [29] with respect to the thermal energy of the condenser and evaporator of the integrated refrigeration machine. As an approach, the thermal energy of the free cooling module is used for the computation of the reference exergies of the auxiliary devices, as the refrigeration machines are turned off in free cooling operation.

<table><caption>Table 4: Amplification factors for auxiliary devices according to the technical standard SIA 382/1 [29].</caption><thead><tr><th>Subsystem</th><th>Electro-thermo amplification factor</th><th></th><th>Threshold value</th></tr></thead><tbody><tr><td rowspan="2">DC</td><td>Dry cooler fan</td><td>$f_{el,th,DC}$</td><td>≥ 28</td></tr><tr><td>Circulating pump</td><td>$f_{el,th,CP,DC}$</td><td>≥ 85</td></tr><tr><td>CST</td><td>Circulating pump</td><td>$f_{el,th,CP,CST}$</td><td>≥ 65</td></tr></tbody></table>

Concerning the other subsystems, the reference exergy of the circulating pumps $B_{el,CP,CST}^*$ in the subsystem CST is computed similarly to Eq. 17 with the electro-thermo amplification factor $f_{el,th,CP,CST}$ according to Table 4. The reference exergy of the free cooling module $B_{FC,CST}^*$ on the CST side is determined by an exergy balance of the reference exergies in the subsystem CST. The cold distribution reference exergy $B_D^*$ of the subsystem CL is calculated according to Eq. 14, but with the cold distribution thermal energy $Q_D$. The cold distribution reference temperature $T_D^*$ is determined similarly to Eq. 11 with temperatures of the secondary side hydraulic circuit according to the technical standard SIA 382/1 [29]. A cold distribution reference inlet temperature $T_{D,in}^*$ of 10 °C and a cold distribution reference outlet temperature $T_{D,out}^*$ of 16 °C is specified, representing the temperature level for an air-conditioning application with partial dehumidification.

## 4. Results and discussion

The investigated field plant exhibits free cooling operation if the measured compressor electrical energy $W_{CPR}$ is equal to and the free cooling thermal energy $Q_{FC}$ larger than 0 J, respectively. This is the case from January to mid-March as well as from end of October to December 2018. Mixed operation of the refrigeration machines and the free cooling module, e.g. precooling overnight, is not considered in the present work. The daily OPI (y-axis) of every subsystem in the refrigeration plant in function of the date (x-axis) is depicted in Fig. 3.
<figure><img src="image_3.png" /><figcaption>Figure 3: Optimization potential index (OPI) of the subsystem DC, FC and CST (a) as well as subsystems CL,1 to CL,7 (b).</figcaption></figure>

## 4.1. Subsystem FC

To begin with, the subsystem FC shows an average $OPI_{FC}$ of -0.30 and exhibits almost a steady-state behavior over the investigated time period (see Fig. 3a). The minimum of -0.45 is achieved on December 25th and the maximum of -0.21 on November 21st. The key figure is 100% of the time lower than 0 and thus, the technical requirements according to the applied technical standards are exceeded. This leads to the assumption, that the implemented heat exchanger is well designed according to the specifications, which results in an adequate operation and performance.

## 4.2. Subsystem CST

The subsystem CST reveals a similar behavior, where the technical requirements are fulfilled. The $OPI_{CST}$ is 100% of the investigated time period lower than 0 and shows an average value of -0.30 (see Fig. 3a). The hydraulic circuit is apparently well designed and the circulating pumps correctly operated, resulting in a low electrical power consumption and a low exergy input compared to the reference, respectively. Interestingly,
the performance indicator reveals an increase of approximately 0.2 from mid-March to end of October. A
possible reason are the three additional cooling locations which were integrated at the end of April, and thus,
the actual exergy input of the subsystem is increased. Most likely, the circulating pumps exhibit an increased
electrical energy usage, due to the additional piping installed in the hydraulic circuit.

4.3. Subsystem CL

The cooling locations CL reveal a differentiated behavior (see Fig. 3b). Cooling location 1 performs best, has an averaged $OPI_{CL,1}$ of approximately -0.04 and is 92% of the time lower than 0. Cooling location 2, 4, 5 and 7 operate close to the technical requirements with an average OPI of 0.19, 0.16, 0.13 and 0.12, respectively. Accordingly, these cooling locations should be observed closely during further operation. An increase of the key figure would indicate a possible malfunction. In contrast, the cooling location 3 performs worst with an average $OPI_{CL,3}$ of 0.36 and cooling location 6 reveals an averaged $OPI_{CL,6}$ of 0.25. Therefore, both cooling locations show an increased potential for improvement. A possible reason can be a fouled or suboptimal heat exchanger, which results in a decreased cold distribution temperature to achieve the needed heat transfer, compared to the chosen reference (see subsection 3.3). Also, a different dimensioning might be present in the refrigeration plant. Meaning that the cooling locations supply an air-conditioning application with a different temperature level as assumed in the reference conditions, e.g. an air-conditioning application without dehumidification. As a consequence, the mentioned cooling locations should be inspected to determine eventual issues and to initiate countermeasures in order to achieve an increased performance.

4.4. Subsystem DC

The subsystem DC operates according to the technical requirements, similarly to the subsystems FC and CST, and exhibits an average $OPI_{DC}$ of -0.87. Three outliers with a value superior to 0 are present on November 15th as well as December 8th and 21st. However, such outliers should not be overly considered, as only a constantly high or rising key figure is a possible indication of a faulty operation. By investigating the daily exergy sums, the reason for the adequate performance of the subsystem DC is revealed (see Fig. 4).

The exergy input of the circulating pumps (see Fig. 4b) is all the time lower than the reference. Also, the exergy input of the dry cooler fans (see Fig. 4c) is substantially, around factor 2, lower than the reference. This is favorable for the refrigeration plant operation. The actual dry cooler fan input is increased by approximately a factor of 6 the same days the OPI reveals a potential for improvement, and thus, the behaviour of the dry cooler fans determines the outcome. The thermal exergy input of the free cooling module (see Fig. 4a) exhibits values according to the technical standards. It is revealed, that a decreased electrical exergy input is more favorable for the subsystem than an adequate temperature level. The reference electrical exergy is roughly factor 2 higher than the reference thermal exergy and, interestingly, the actual electrical exergy inputs of the auxiliary devices exhibit a similar magnitude as the actual thermal exergy input. In energetic considerations, their input would account only for roughly 4.7% of the thermal load according to technical standards. This outcome emphasizes to reduce the auxiliary electrical energy input where possible, e.g. with an adaptive speed control of the circulating pumps and dry cooler fans, in order to achieve a highly performing refrigeration plant.
<figure><img src="image_4.png" /><figcaption>Figure 4: Daily exergy sum of the subsystem DC input from the free cooling module (a), circulating pumps (b) and dry cooler fans (c).</figcaption></figure>

5. Conclusions and outlook

The introduced optimization potential indices for free cooling operation of refrigeration plants allows an assessment of the performance and the corresponding optimization potential in every subsystem at a glance. The identification of possible optimization potentials is relevant, as measures which improve the system effectiveness most likely prevent frequent shortcomings during refrigeration plant operation. The functionality of the methodology was shown by applying it with experimental data from an existing field plant as a case study. With defined reference values according to the state of the art in technology, an absolute comparison between different refrigeration plants is feasible. The interpretation of the results is straightforward, which is of great importance in practice. Laypersons can easily determine the system operating state and initiate countermeasures by specialist if needed. A simple red/green indicator could be realized to facilitate the monitoring of the plant operation. Furthermore, the exergy-based assessment system helps to sensitize all involved actors, e.g. plant operators, regarding an efficient operation of refrigeration plants. The presented method finds possibly
also application in other building energy systems, such as heat pumps.

The investigated field plant reveals a performance according to the technical requirements in general, whereby it can be concluded that the hydraulic circuits are adequately designed and the auxiliary devices properly controlled. Two out of seven cooling locations show significant potential for improvement. The latter could be realized by e.g. ameliorating the heat transfer or including another hydraulic circuit for the cold distribution on the desired temperature level according to the air-conditioning application. Moreover, the analysis shows the importance of reducing the energy usage of auxiliary devices to achieve an adequate performance of the plant.

Further investigations are needed regarding the determination of the cooling location exergy. As no measurements were available for the present study, an alternative approach was used for the subsystem cooling location to determine the optimization potential index. To allow a consistent definition of the latter, the temperature of the cooling locations and the corresponding air humidity needs to be measured in the future. This includes the determination of the exergy of humid air, which is typically present in air-conditioning applications or evaporative coolers, e.g. cooling towers. Furthermore, the exergetic assessment system should be applied to other field plants, preferably with a different cooling power and other subsystems such as heat utilization. This helps to identify interrelationships between various refrigeration systems and to use them for future evaluations. Likewise, further technical reference values should be determined, as it is currently not possible to estimate which values of the optimization potential index close to the limit of 0 still represent a permissible operation. In addition, future investigations should analyze the influence of the reference environment on the optimization potential index.

# 6. Acknowledgements

This study was partially funded by the Swiss Federal Office of Energy (SFOE).

# References

[1] D. Wu, B. Hu, R. Wang, Performance simulation and exergy analysis of a hybrid source heat pump system with low GWP refrigerants, Renewable Energy 116 (2018) 775-785. doi:10.1016/J.RENENE.2017.10.024.

[2] K. Menberg, Y. Heo, W. Choi, R. Ooka, R. Choudhary, M. Shukuya, Exergy analysis of a hybrid ground-source heat pump system, Applied Energy 204 (2017) 31-46. doi:10.1016/J.APENERGY.2017.06.076.

[3] M. Razmara, M. Maasoumy, M. Shahbakhti, R. Robinett, Optimal exergy control of building HVAC system, Applied Energy 156 (2015) 555-565. doi:10.1016/J.APENERGY.2015.07.051.

[4] B. Fan, X. Jin, X. Fang, Z. Du, The method of evaluating operation performance of HVAC system based on exergy analysis, Energy and Buildings 77 (2014) 332-342. doi:10.1016/j.enbuild.2014.03.059.
[5] A. Fudholi, M. Zohri, G. L. Jin, A. Ibrahim, C. H. Yen, M. Y. Othman, M. H. Ruslan, K. Sopian, Energy and exergy analyses of photovoltaic thermal collector with ∇-groove, Solar Energy 159 (2018) 742–750.
doi:10.1016/J.SOLENER.2017.11.056.

[6] S. Agrawal, G. Tiwari, Energy and exergy analysis of hybrid micro-channel photovoltaic thermal module, Solar Energy 85 (2) (2011) 356–370. doi:10.1016/J.SOLENER.2010.11.013.

[7] R. Sangi, D. Müller, Exergy-based approaches for performance evaluation of building energy systems, Sustainable Cities and Society 25 (2016) 25–32. doi:10.1016/J.SCS.2016.04.002.

[8] E. Saloux, A. Teyssedou, M. Sorin, Development of an exergy-electrical analogy for visualizing and modeling building integrated energy systems, Energy Conversion and Management 89 (2015) 907–918.
doi:10.1016/J.ENCONMAN.2014.10.056.

[9] J. Harrell, J. Mathias, Improving Efficiency in a Campus Chilled Water System Using Exergy Analysis, ASHRAE Transactions 115 (1) (2009) 507–522.

[10] M.-H. Yang, R.-H. Yeh, Performance and exergy destruction analyses of optimal subcooling for vapor-compression refrigeration systems, International Journal of Heat and Mass Transfer 87 (2015) 1–10. doi: 10.1016/J.IJHEATMASSTRANSFER.2015.03.085.

[11] W. Fratzscher, V. M. Brodjanskij, K. Michalek, Exergie - Theorie und Anwendung, Deutscher Verlag für Grundstoffindustrie, Leipzig, 1986.

[12] K. Shan, S. Wang, D. C. Gao, F. Xiao, Development and validation of an effective and robust chiller sequence control strategy using data-driven models, Automation in Construction 65 (2016) 78–85. doi: 10.1016/j.autcon.2016.01.005.

[13] K. Dong, P. Li, Z. Huang, L. Su, Q. Sun, Research on free cooling of data centers by using indirect cooling of open cooling tower, Procedia Engineering 205 (2017) 2831–2838. doi:10.1016/J.PROENG.2017.09. 902.

[14] M. Sorrentino, G. Rizzo, A. Trifiro, F. Bedogni, A Model-Based Key Performance Index for Energy Assessment and Monitoring of Telecommunication Cooling Systems, IEEE Transactions on Sustainable Energy 5 (4) (2014) 1126–1136. doi:10.1109/TSTE.2014.2334365.

[15] O. B. Kazanci, M. Shukuya, B. W. Olesen, Theoretical analysis of the performance of different cooling strategies with the concept of cool exergy, Building and Environment 100 (2016) 102–113. doi:10.1016/
J.BUILDENV.2016.02.013.

[16] E. Al-Bassam, R. Alasseri, Measurable energy savings of installing variable frequency drives for cooling towers' fans, compared to dual speed motors, Energy and Buildings 67 (2013) 261–266. doi:10.1016/j. enbuild.2013.07.081.
[17] S. Eisenhauer, T. Hauck, M. Arnemann, Systematische Erstellung und Anwendung messtechnischer Konzepte zur energetischen Untersuchung von Kälteanlagen, in: DKV-Tagung, Dresden, 2015.

[18] L. Brenner, F. Tillenkamp, M. Krütli, C. Ghiaus, Optimization potential index (OPI): An evaluation method for performance assessment and optimization potential of chillers in HVAC plants, Applied Energy 259. doi:10.1016/j.apenergy.2019.114111.

[19] M. J. Moran, H. N. Shapiro, D. D. Boettner, M. B. Bailey, Fundamentals of engineering thermodynamics: SI version, John Wiley, New York, 2010.

[20] A. Bejan, G. G. Tsatsaronis, M. J. Moran, Thermal design and optimization, Wiley, 1996.

[21] M. Ducoulombier, M. Sorin, A. Teyssedou, Thermodynamic bounds for food deep chilling tray tunnel operation, International Journal of Thermal Sciences 46 (2) (2007) 172–179. doi:10.1016/J.IJTHERMALSCI. 2006.05.001.

[22] Y. A. Çengel, M. A. Boles, Thermodynamics: an engineering approach, McGraw-Hill, Boston, 2005.

[23] H. Torío, D. Schmidt, Annex 49 final report: Energy Conservation in Buildings and Community Systems (ECBCS) - Low exergy systems for high-performance buildings and communities, Tech. rep., Fraunhofer IBP, Stuttgart (2011).

[24] V. Martinaitis, J. Bielskus, K. Januševičius, P. Bareika, Exergy efficiency of a ventilation heat recovery exchanger at a variable reference temperature, Mechanics 23 (1) (2017) 70–77. doi:10.5755/j01.mech. 23.1.17678.

[25] Y. Zhou, G. Gong, Exergy analysis of the building heating and cooling system from the power plant to the building envelop with hourly variable reference state, Energy and Buildings 56 (2013) 94–99. doi:10.1016/J.ENBUILD.2012.09.041.

[26] V. Bonetti, Dynamic exergy analysis for the built environment: fixed or variable reference?, in: Proceedings of the 9th Exergy, Energy and Environment Symposium, FESB, University of Split, Split, Croatia, 2017, pp. 924–939.

[27] M. Pons, On the Reference State for Exergy when Ambient Temperature Fluctuates, International Journal of Thermodynamics 12 (3) (2009) 113–121. doi:10.5541/IJOT.1034000246.

[28] Mechanical Engineering Industry Association (VDMA), Energieeffizienz von Klimakälteanlagen. Teil 8: Komponenten - Wärmeübertrager (VDMA 24247-8), 2011.

[29] Swiss Society of Engineers and Architects (SIA), Lüftungs- und Klimaanlagen - Allgemeine Grundlagen und Anforderungen (SIA 382/1), 2014.