Energy, cost, and environmental analysis of individuals and district cooling systems for a new residential city

Journal Pre-proof Life-cycle-cost analysis of District Cooling for high energy demand of Low-Rise Buildings Ali Alajmi, Mohamed Zedan

PII:

S2210-6707(19)31404-0

DOI:

https://doi.org/10.1016/j.scs.2019.101976

Reference:

SCS 101976

To appear in:

Sustainable Cities and Society

Received Date:

17 May 2019

Revised Date:

8 October 2019

Accepted Date:

18 November 2019

Please cite this article as: Alajmi A, Zedan M, Life-cycle-cost analysis of District Cooling for high energy demand of Low-Rise Buildings, Sustainable Cities and Society (2019), doi: https://doi.org/10.1016/j.scs.2019.101976

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LIFE-CYCLE-COST ANALYSIS OF DISTRICT COOLING FOR HIGH ENERGY DEMAND OF LOW-RISE BUILDINGS Ali Alajmi1*, Mohamed Zedan1 1

Mechanical Engineering Dept., College of Technological Studies, PAAET, Kuwait

*

Corresponding author, [email protected]

Highlights DC system reduces the residential house peak electric power demand by 50%.

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The annual electrical energy consumption of the DC is 55% and 18% lower than RTU

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and VRF.

The life cycle cost of DC is 30% and 20% less than the RTU and VRF.

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The DC number of cooling units is 624, while RTU and VRF are 660,200 and 220,800.

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The risk of refrigerant leakages for DC is much less than RTU and VRF.

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A significant reduction (53%) in CO2 emission is achieved using DC cooling system.

ABSTRACT

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In severe hot climates, the cooling system is the main cause of high power demand and energy consumption in buildings. District cooling (DC) system, have the potential to decrease such demands. A comparison of energy performance of the DC versus individual units, roof top unit (RTU) and variable refrigerant flow (VRF), has been conducted. The DC shows a less peak

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demand than by around 49.6% and less consumption by 55% and 18.4% of RTU and VRF respectively. However, the main concern that refrains spreading of using the DC system in lowrise buildings is the capital cost investment. Thus, a life-cycle-cost analysis (LCC) has been implemented on a new design city “Almutlaa” in Kuwait. The LCC analysis, which includes all aspects related to the capital and running cost, indicated that the DC system is the most cost-effective system over the studied life span (24

years). The LCC of the three systems (RTU, VRF, and DC) for the new city is 22.67, 20.83, and 17.39 Billion dollars, respectively, saving 5.28 and 3.44 Billon dollars compared to RTU and VRF. Moreover, the amount of avoided CO₂ emission achieved by using DC compared to RTU and VRF is 35,000 and 11,000 metric Ton, respectively.

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Keywords: District Cooling (DC), Rooftop unit (RTU), Variable Refrigerant Flow (VRF), Life-cycle Cost Analysis (LCC).

1. INTRODUCTION Worldwide, buildings account for about 40% of the primary energy consumption. In the Middle East, buildings consume an even higher fraction of primary energy consumption [1]. In such harsh hot climates, the cooling system claims to be responsible of 70% of the power demand and 60% of the energy consumption [2,3] mainly servicing residential buildings. District cooling (DC) systems, have the potential to decrease air conditioning peak power and energy demands due to its high energy performance. DC systems were established in Hartford

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(USA) in 1962, Hamburg in 1967, and the La Defense district outside Paris in 1967. However, early precursors were the ‘pipeline refrigeration’ systems introduced in New York and other US cities in the 1890s [4]. Nowadays district energy (DE) involves multi-building heating and

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cooling, in which heat and/or cool are achieved by circulating either hot water or low-pressure steam (District Heating systems (DH)) or cold water (District Cooling system (DC)) through

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underground piping [5-8]. Major district cooling systems appear in cities such as Singapore,

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Tokyo, Stockholm, Paris, Dubai, Chicago, Toronto, Courbevoie outside Paris, Helsinki, Barcelona, Vienna, Berlin, etc. District energy (cooling and/or heating) can provide efficiency, environmental and economic benefits to communities and energy consumers [9]. In tropical

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climates, individual systems usually achieve a coefficient of performance (COP) in the range of 2.5–3.25, electric chillers with dry air cooling tower achieve a COP in the range of 3.5–5 and electric chillers with wet cooling tower achieve a COP in the range of 6–10 [10]. Difs et al. [11]

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state that DE systems usually exhibit lower environmental impacts compared to conventional systems. A district cooling system was developed for the South East Kowloon, Hong Kong and achieved energy savings of 20–35% compared to the air conditioning split systems and decentralized chillers saving of 85 GWh, equivalent to the CO2 reduction of 59.5 ktons [12]. However, the volume of cold district deliveries in the world is currently much smaller than district heat deliveries [13]. In the Middle East, district cooling systems provide about 7% of all cooling demands [14].

The most recent growth in district cooling has been in Asia and the Middle East. The largest projects on district cooling in terms of capacity took place in Qatar, Kuwait, and the United Arab Emirates. In Qatar, the district cooling plant at The Pearl-Qatar has the combined cooling power of 450 MW, and it seems to be the world’s largest integrated district cooling plant so far [15]. In Kuwait, the Shadadiyah University’s campus will be cooled with 36 electric chillers with the combined cooling power of 252 MW [16]. All the above mention projects are designed for high-rise residential buildings, institutional buildings, and shopping malls. However, the district energy system for low-density residential areas which involves higher distribution costs

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as stated by Reihav and Werner [17] and Nilsson et al. [18] are not covered in the literature.

In the current research, the feasibility of DC systems in comparison to other residential cooling

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systems, i.e., rooftop unit (RTU) and variable refrigerant flow (VRF) systems, for low-rise buildings with high energy demand in a hot-summer climate is studied. Al Mutlaa city is

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selected as a case study that has an area of 7700 hectares comprising 87% residential

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neighborhoods and 13% of other building such as commercial and light industrial zones. 2. RESIDENTIAL COOLING SYSTEMS TYPES

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The widespread use of cooling system type in the Arabian Gulf Countries (AGC) is the Roof Top Unit (RTU) ducted system and mini-split units. Recently the Variable Refrigerant Flow (VRF) is introduced as a more efficient cooling system to be alternative to the existing common used system (RTU). On the other hand, the water-cooled cooling system is the most used for

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large buildings.

Roof Top Unit (RTU)

The rooftop unit (RTU) system is the most common type used in the low-rise buildings and in particular for the residential buildings. It is a unitary system that uses the vapor compression cycle to provide cooling to the supplied air and reject the absorbed heat by the refrigerant through an air-cooled condenser. Its performance on a hot climate tends to be inefficient due to

many factors such as compressor type, fan performance, duct leakage, etc. In this research, detail performance curves are used which represent the best available units in the market with an overall coefficient of performance (COP) of 2.5. Variable Refrigerant Flow (VRF) The variable refrigerant flow (VRF) increasingly becomes popular for medium to low-rise buildings and recently introduced to residential buildings. It is a two-part unit system (outdoor and indoor) that uses the vapor compression cycle to provide cooling to the supplied air and

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reject the absorbed heat through an air-cooled condenser. Its performance on a hot climate tends to be a better efficiency due to the use of inverter compressor which leads to reduce the consumption in part load situations. In this research, detail performance curves are used which represent the best available units in the market with an overall coefficient of performance (COP)

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of 3.3.

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Water-cooled Chiller

The water-cooled chiller is the most efficient and stable technology as cooling systems. It is the

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main component of a district cooling (DC) system. It is usually come in large size capacity using a centrifugal compressor as the main driver for a large quantity of refrigerant. Besides the

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compressor, such system type is integrated with a cooling tower to reject the absorbed heat. Its performance on a hot and arid climate tends to be the best in the peak demand. However, it has a noticeably less performance in the part load situations. In this research, detail performance

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curves are used which represent a coefficient of performance (COP) of 5.5. Performance Curves

In order to make the comparison between all selected cooling system types; the performance curve of each system that represents the full and part load behaviors are prepared. The energy simulation software (EnergyPlus) requires several performance curves to be used to calculate the energy peak demand and consumption. The used performance curves in this study are: 1. Delivered Cooling Modifier Curve as a Function of Temperature.

2. Energy Input Ratio (EIR) Modifier Curve as a Function of Temperature. 3. Energy Input Ratio (EIR) Modifier Curve as a Function of Part-Load Ratio.

3. METHOD AND MATERIAL In the presence of the building simulation software the calculation of the cooling demand on a scale of individual premises or a whole district can be done properly. The calculation of the cooling load of a newly district design is need to be calculated carefully. It tends to use a rule of thumb of an individual unit cooling load such as house and replicate it to the total number of

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the same unit in a district. This approach is not only inaccurately sizing the mechanical system but also it has a high uncertainty of calculating the corresponding energy consumption.

In this research, the cooling load of the individual unit is calculated using a building simulation

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program (EnergyPlus) using an interface by the DesignBuilder software [x]. In addition, the

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orientation and position of the house were considered, therefore, a multiple number of houses (16) were allocated in different positions i.e. at the middle of a line of houses, at the edge, etc.

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as well as the orientation i.e. east, west, south, and north to represent the all possible cooling demand of each unit location and orientation. Then the average cooling load of these selected

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representative houses can be used to size the air-conditioning unit and also to calculate the energy consumption. A diversity factor has been selected for each type of air-conditioning system to size the required maximum capacity of each air-conditioning (A/C) system. The methodology used in this research is shown in Figure 1 and its implementation is described in

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the following sections.

Select a District Area

Analyze the Building Typology

Select a Representative number of building Set a Diversity Factor for each A/C system Set Energy Performance Curves of A/C system

Calculate the Energy Yes Consumption for the District

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Compare the Energy Consumption

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Size the Required Cooling Capacity System

For each A/C type

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Study the Cost Effectiveness of all A/C types

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Figure 1: Methodology flowchart.

3. A NEWLY DESIGNED PLAN OF CITY OF RESIDENTIAL BUILDINGS

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In this study, a new design plan of a city in the State of Kuwait is used to make a tangible comparison between the compared cooling systems. It is worth noting that the weather in the State of Kuwait is extremely hot over a long summer period, see Fig 1. As shown in this figure

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that the temperature from April to October is beyond the comfort zone. The highest recorded temperature as seen is during August with the temperature reaches above 50°C. Five months of the year, from May to September, the highest recorded temperature ranges from 47°C to 52°C. For this reason, active cooling is required most of the year to ensure comfort to the occupants.

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Dry-bulb temperature °C

Figure 2: The temperature profile for the State of Kuwait

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The City’s Buildings Typology

The considered neighborhood layout of this study compromises several building types such as

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villa, retail, public office, etc. However, the main building type is the villa which occupies the main share around 87%, see Fig 2. In this study only, the residential area is considered,

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diversity factor.

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although, mixing the other building types improve the DC performance by increasing the

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Figure 3: Building types of the studied new plan residential area.

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The City’s Neighbourhood Layout

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The layout of the neighborhood of the city of “Almutlas” is shown in Fig. 3. The neighborhood split into quarters; a chilled water plant facility will serve each quarter.

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1. Each quarter has 575 houses in mirror design.

2. The simulation was set to simulate 2300 houses.

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3. The city has 12 neighborhoods.

(a)

(b)

Figure 4: Layout of the neighborhood served by chilled water plant facilities: (a) the four facilities chilled water plants (b) a single facility.

Design Capacity It is so common in practice to over-size the air-conditioning system to avoid possible customers’ complaints of insufficient cooling. Also, there is a lack of simple and cost-effective tools that can be used to estimate the cooling load adequately for such type of building (residential) in which the HVAC system capacity is selected. Usually, a simple hand calculation by the A/C equipment supplier is done to size the house requirement of A/C capacity. Similarly, the relatively new A/C equipment, i.e., variable-refrigerant-flow (VRF) are designed using the same method. However, in the case of using a district cooling (DC), a proper cooling load

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calculation will be done by a consultant firm using a proper cooling load tool to ensure a right capacity of the cooling system.

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In this study, a sample of 16 villas has been selected (donated by letters A-P) to represent the served area shown in Fig. 4. The selected houses have been carefully chosen to represent all

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orientation and location of the houses, i.e., take into consideration possible adjacencies, see

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Fig.4.

(a) (b) Figure 5: Sample of 16 houses of different orientations (a) perspective view (b) model used in the simulation program (DesignBuilder).

The typical villa is encompassed of a basement and three floors, which becomes the trend nowadays among the residents. The total floor area (conditioned) is 1225 m². The cooling demand of these houses (minimum, average, and maximum) are calculated using building simulation program (DesignBuilder, [19]), illustrated in Fig. 5. Average cooling demand of 159

kW per house is considered. Based on this selection, the design margin of each cooling system type has been selected differently. The design margins for rooftop unit (RTU), variable refrigerant flow (VRF), and district cooling (DC) are 1.15, 0.9, 0.8, respectively. The total design capacity of the 2300 houses is shown in

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Fig. 6.

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Figure 6: Total cooling demand for each of the represented 16 houses

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Figure 7: The design capacity of a neighborhood (2300 houses).

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Peak Power Demand

The peak power spikes during the summer period which mainly comes from the buildings’

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demand, in particular from the air-conditioning system. Therefore, reducing the peak building

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demand will reduce the maximum power capacity requirement of the power plant. Consequently, reducing the need for constructing a higher number of power plants for the future

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growth of residential buildings. The peak demand for the three selected cooling systems for one neighborhood is illustrated in Figure 7. As shown in this figure that the district cooling peak

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demand is the lowest and it is 49.5% less than the other two systems.

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Figure 8: Peak demand of each system type (RTU, VRF, and DC) for a neighbourhood.

Energy Use Intensity (EUI) of Each Cooling System (CS) Type

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The energy use intensity for each cooling system type (EUI-CS) is measured by dividing the

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total annual energy consumption of each cooling system (RTU, VRF, and DC) by the total floor area of a house. A noticeable difference value of EUI for each cooling system type is shown in Fig. 8. The EUI value of the RTU, VRF, and DC systems are 144, 110, 93 (kWh/m².year),

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respectively.

Energy Consumption of each Cooling System Types A typical value of a house energy demand is used to represent the energy demand of 2300 units

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in a single neighborhood. As expected the chiller performs the best due to its high coefficient of performance (COP), then VRF is the second, while the RTU has the lowest energy performance, as illustrated in Fig. 9. The trend of the monthly and annual consumption of the total neighborhood is shown in Fig. 10 and 11, respectively, using DesignBuilder [19].

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Figure 9: EUI of each cooling system type (RTU, VRF, and DC) of a neighborhood.

Figure 10: The energy consumption of the three cooling systems of a neighborhood.

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Figure 11: Monthly consumption of the three-compared cooling systems of a neighborhood.

Figure 12: Energy demand of the three cooling systems on a daily basis of a neighborhood.

4. ECONOMIC AND ENVIRONMENT ANALYSIS Economic analysis Economic analyses of Al Mutlaa city air cooling systems involve assessment of Capital Investment Cost (CIC) and Operation and Maintenance Cost (OMC). The CIC of the air-cooling system includes: 1) District Cooling system Cost (DCC), which is the cost of the plant facility and its associated infrastructures and the distribution pipe network required to operate the aircooling system, and 2) the Power Plant facility Cost (PPC) which required to generate the

contributors to the CIC.

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electricity to operate the air-cooling system. The PPC and the DCC Costs are the two major

The PPC can be paid in annual installment. Therefore, the Annual Power Plant Cost (APPC)

𝐴𝑃𝑃𝐶 = 𝑃𝑃𝐶 ∗ 𝐶𝑅𝐹

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($/year) can be determined using the following equation:

(1)

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Where PPC is the power plant capital investment cost ($), and CRF is the Capital Recovery

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Factor which is a parameter that converts the PPC to a series of equal annual payments for a certain duration of time. CRF is estimated as follows: 𝑑 (1+𝑑)𝑁

(1+𝑑)𝑁 −1

(2)

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𝐶𝑅𝐹 =

Where d is the discount rate, and N is the component life cycle in years, which equates to 24 years in the case of DC system, see Table 1.

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Aside from the major CIC, there will be other significant Operation and Maintenance Cost (OMC) taken into consideration. The OMC includes the Electricity Cost (EC), Insurance Cost (IC), Water Cost (WC), Chemical Treatment Cost (CTC) and other miscellaneous items cost (MISC) consumed by the cooling system during the full cooling season including labor and spare parts. Table 2 contains unit cost data for OMC cost calculation. Assuming that the Annual Operation and Maintenance Cost (AOMC) is varying over the life cycle of the cooling system due to the inflation rate, it is estimated in ($/year) as follows:

(𝐴𝑂𝑀𝐶)𝑚 = (𝐴𝑂𝑀𝐶)1 ∗ (1 + 𝐼𝑅)𝑚−1

(3)

Where (AOMC)m is the annual operation and maintenance cost for any year (m), (AOMC)1 is the annual operation and maintenance cost for the first year, and IR is the Inflation Rate. To calculate Life Cycle Cost (LCC) of the cooling systems, the following equation is considered: 𝑁

𝐿𝐶𝐶 = 𝐷𝐶𝐶 + 𝑁 ∗ 𝐴𝑃𝑃𝐶 + ∑ (𝐴𝑂𝑀𝐶)𝑚

(4)

𝑚=1

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Where, (N) is the component life cycle in years, (DCC) is a district cooling system cost, (APPC) is the annual power plant investment cost from Eq. (1), and (AOMC) is the annual operation and maintenance cost Eq. (3). In this research, (DCC) is paid in advance and the (APPC) is paid

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as an annual installment over the life cycle of the system. The present analysis is conducted using data from the existing cooling system and form different references [20, 21 and 22].

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Tables 1 & 2 contain this data and is used for DCC, APPC, and AOMC calculation.

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In the case of DC cooling systems, several large chillers (>35,000 kW (1000RT) capacity) can meet the peak cooling demand of the neighborhood. Generally, during the peak cooling demand

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hours, the chillers operate at full capacity. A minimum of one chiller is recommended to act as a standby to ensure trouble-free operation, especially during the peak summer season. The cost estimate for the primary plant facility has been based on data from a local consultant firm (see Table 1). The unit cost of the installed capacity (i.e., US $ per kW/Refrigeration Ton (RT)) is

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chosen as a cost parameter for comparison between the different types of cooling systems. This unit cost includes all expense details of the plant facility requirements. Using unit cost from Table 1 and the cooling load for the Almutlaa city in Table 3, the capital cost for the plant facility can be determined by: 𝑃𝑙𝑎𝑛𝑡 𝐹𝑎𝑐𝑖𝑙𝑖𝑡𝑦 𝐶𝑜𝑠𝑡 = 𝑈𝐶𝑃𝐹 ∗ 𝑀𝐶𝐼

(5)

Where UCPF is the unit cost of DC plant facility ($/kW), see Table 1, and M𝐶𝐼 is the maximum capacity installed (kW), see Table 3 for the whole city (12 neighborhoods).

To determine the cost of the pipe network, establish initial grid layout and measure pipe lengths, calculate cold flows based on the cooling load for each section in neighborhood, heat and pressure losses in the grid, and calculate pipe diameters needed to meet the peak cooling energy demand. Using pipe lengths, diameters and Table 3 pipe network cost can be determined.

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An initial grid layout (transmission and distribution pipes) has been constructed [20] as shown in Figure 3. Upon initial consideration of the grid layout, mass flows in each piping branch can be calculated considering thermal and pressure losses. Results of this part of methods are pipe

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diameters needed for the estimation of investment in the DC grid and losses that occur in the grid. The following equation is used to determine cold flows: -

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𝐶𝑜𝑜𝑙𝑖𝑛𝑔 𝐿𝑜𝑎𝑑 = 𝑚̇ ∗ 𝐶𝑝 ∗ ∆𝑇

(6)

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Where 𝑚̇ is the cold water mass flow rate, 𝐶𝑝 is water specific heat, and ∆𝑇 represents the temperature difference between supply and return line of the DC network which is typically

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5.6°C. Sizing of the pipework is typically based on a maximum velocity limit to prevent excessive erosion of the pipe. Recommended velocity limits are often provided by the pipe manufacturer. These limits have been interpreted in Table 4 and applied when sizing the distribution pipework [20]. Using Table 4 and water mass flow rate the pipe diameter can be

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determined. The flowing equation represents the total capital cost of the DC grid network: 𝑘

𝐷𝐶 𝑔𝑟𝑖𝑑 𝐶𝑜𝑠𝑡 = ∑ 𝑈𝐶𝑃𝑖 ∗ 𝐿𝑖

(7)

𝑖=1

Where UCPi is the unit cost per meter of each pipe section Table 1, Li represents the length of each pipe section, and k is the total number of pipe sections. By adding the cost calculated by

Equations (4), (5) and (7) the total capital investment cost (CIC) of the DC system can be determined. The (DCC) district cooling system cost can be determined by adding the DC plant facility cost from Eq. (5) and DC grid network cost form Eq. (7) and is given by: 𝐷𝐶𝐶 = 𝑃𝑙𝑎𝑛𝑡 𝐹𝑎𝑐𝑖𝑙𝑖𝑡𝑦 𝐶𝑜𝑠𝑡 + 𝐷𝐶 𝑔𝑟𝑖𝑑 𝐶𝑜𝑠𝑡

(8)

To determine the capital cost of the power plant (PPC) the following equation is applied: 𝑃𝑃𝐶 = 𝑈𝐶𝑃𝑃 ∗ 𝑃𝐸𝑃𝐷

(9)

Where UCPP is the unit cost of the power plant ($/MW), see Table 1, and 𝑃𝐸𝑃𝐷 is the peak

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electric power demand, see Table 3. The annual operation and maintenance cost (AOMC) of the DC cooling system includes the Electricity utility Cost (EC), Insurance Cost (IC), Water Cost (WC), Chemical Treatment Cost

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(CTC) and other miscellaneous items (MISC) consumed by the cooling system during the full cooling season, including labor and spare parts. The AOMC can be calculated as follows:

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𝐴𝑂𝑀𝐶 = 𝐸𝐶 + 𝐼𝐶 + 𝑊𝐶 + 𝐶𝑇𝐶 + 𝑀𝐼𝑆𝐶

(10)

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Electricity utility Cost (EC) can be calculated by multiplying the electric utility rate in Table 2 by the annual electric power consumption in Table 3. Insurance cost (IC) is estimated by

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multiplying the annual insurance rate in Table 2 by power plant cost (PPC) which is calculated before. Water cost (WC) is calculated by multiplying water cost rate by unit annual water consumption in Table 2 by annual cooling load demand (MWh) in Table 3. Chemical treatment cost (CTC) can be determined by multiplying the annual chemical treatment unit cost in Table

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2 by annual cooling load demand (kWh) in Table 3. To calculate the miscellaneous items (MISC), the annual plant facility operation and maintenance unit cost in Table 2 is multiplied by maximum capacity installed (kW) in Table 3. To calculate Life Cycle Cost (LCC) of the cooling system Eq. (4) is used. Where, the DCC, in this equation, can be determined from Eq. (8), the APPC is calculated using Eqs. (1&9) and AOMC is determined from Eq. (10).

To study the feasibility of implementing DC systems in comparison to other residential cooling systems, rooftop (RTU) and variable refrigerant flow (VRF) systems, the Life Cycle Cost (LCC) is determined for RTU and VRF systems. The calculation steps used to calculate LCC of DC system will be followed by the LCC of the other two systems (RTU & VRF). The data required for these calculations are available in Tables 3 and 5. It is worth noting here that the component life cycles (N) for RTU and VRF systems are 8 and 12 years, respectively. To compare the annually total accumulated cost over 24 years of life cycle , of the three cooling

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systems, which includes CIC and AOMC. Throughout the calculation of LCC, the units of the RTU and VRF systems are rebuild at the end of the life cycle of each system with half the price of the new units assuming only mechancial components such as compressors and fan motors

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are replaced. As shown in Figure 12 that the annaully accumlated total cost of DC system is more than the RTU system over the first 8 years. After that, this cost starts to be decrease for

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DC system comparing with the other systems over the lif-span (24 years). In the end of the lifespan, the annaully accumlated total cost of DC system is significantly less than the other

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systems which are around 5.28×10³ and 3.44×10³ M$ less than RTU and VRF systems, respectively. It is clear that the DC system is more superior in performance and cost comparing

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with RTU and VRF systems. The cost of each component of the three cooling systems for the life cycle of 24 years is illustrated in Fig. 13. As shown in the figure, the electrical utility component cost is the predominant cost. The electrical utility cost of the RTU system is the

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highest at 16.4 M$ and then the electrical utility cost for the VRF system at 12.5 M$. While, the electrical utility cost for the DC system is the cheapest, and it is around 10.6 M$. In addition, the cost of the DC in respect of supply energy by power plant is almost half the other system. Reversely, the RTU show less than DC in system cost but the VRF is the highest. Moreover, the RTU and VRF both are less in the running cost than DC by almost half and one third, respectively. The final compared component is the insurance which relatively minimal to the total cost.

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Figure 13: Total accumulated cost for the three cooling systems every year.

Figure 14: Cost of each component for the three cooling systems

Impact on the Environment Many greenhouse gasses contribute to environmental pollution. CO2 is the main contributor to global warming, and for this reason, only CO2 emissions are considered in the present work. As such, the environmental impact of each new technology is determined by the amount of avoided CO2 emissions when it is being implemented. According to an IEA study [23], Kuwait has one of the highest carbon emissions intensity in the Middle East and North Africa (MENA) region due to its high reliance on oil to produce electricity and desalinate water. Kuwait generates 870 of gCO₂ for each kWh of electricity, significantly higher than the world average of

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573 gCO₂/kWh. It should be noted that countries that utilize natural gas to generate a significant portion of their electricity have low carbon emissions intensity. For instance, the share of natural

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gas in the total electricity generated in Qatar is over 85% [24].

In this study, the estimated avoided CO2 emission is based on plant emission factor (Kuwait)

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of 870 gCO2/kWh. Using this plant emission factor and the annual electric consumption Table

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3, the annual CO2 emission for the three cooling systems is estimated and presented in Figure 14. As seen in the figure using the DC system yields a reduction of annual CO2 emission at least 500 metric Ton compared to other cooling systems. This reduction in CO2 emission, over

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the cooling system life cycle, is equivalent to 35,000 metric Ton compared to the RTU system and 11,000 metric Ton compared to the VRF system. This result reflects the impact of

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implementing DC cooling system on improving the environment.

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Figure 15: Annual CO₂ Emission for the three Cooling Systems.

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5. CONCLUSION

The current study has shown that a significant cutback in a residential house electrical

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consumption can be achieved by using DC cooling system. Also, a remarkable reduction in peak electric power consumption, total cost, and CO2 emissions are obtained. The DC peak electric power consumption is the lowest and it is 49.6% less than the RTU or VRF. The VRF is only 1.4% less than the RTU because both systems are rejecting the heat from the

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refrigeration cycle using the air-cooled condenser. On the other hand, the DC shows lower peak electric power consumption due to the technique of rejecting the heat through the water-cooled condenser. Moreover, the annual electric power consumption of the DC is less than RTU and VRF by 55% and 18.4%, respectively. Interestingly, the energy use intensity of cooling system (EUI-CS) per house reduced to a value of 93 for DC system while the values for VRF and RTU systems are 110, and 140 kWh/m².year, respectively.

The total Cost (M$), over the life cycle of the cooling systems, indicates that significant saving in total cost is achieved. The total cost is reduced from 22,669 M$ for RTU and 20,829 M$ for VRF systems to 17,395 M$ for DC system, which is equivalent to 30.3% and 19.7% reduction in cost by using DC in comparing to RTU and VRF, respectively. It is important to mention here that the number of cooling units, over the life cycle, required to cool the Almutlaa city residential area is extremely different for the three cooling systems. In addition, using RTU system needs 660,200 cooling units, the VRF system needs 220,800 cooling units while DC system needs only 624 Units. This has a large influence on the amount of labor hours needed

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to service, maintain, operate the units, and space needed by cooling system on the roof of the residential building. Also, the huge number of spare parts required for RTU and VRF systems.

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Besides, as the number of units increases the higher risk of refrigerant leakage increases.

Ultimately, the amount of CO₂ emissions, (over life cycle) has fallen from 101,520 metric Ton

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using RTU system to 66,448 metric Ton using DC system, which is a reduction of 52.8 %.

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ACKNOWLEGMENT

This work was funded by the Public Authority for Applied Education and Training, Kuwait

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under project number TS-17-09.

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References

[1] IEA. Key world energy statistics. Report for the Organization for Economic Cooperation and Development. Paris (France); 2014. [2] Ministry of Electricity and Water (MEW), Statistical Data Book 2012 – Electricity and Water (2012) [3] MEW Energy Conservation Code of Practice, MEW/R-6/2010 (second ed.), Ministry of Electricity and Water, Kuwait (2010). [4] Frederiksen S, Werner S. District heating and cooling. Lund Studentlitteratur; 2013. [5] Dincer I, Rosen MA. Exergy: energy, environment and sustainable development. Oxford, UK: Elsevier; 2007. [6] Summerton J. District heating comes to town: the social shaping of an energy system. Linkoping Stud Art Sci 1992;80:220–319. [7] Marinova M, Beaudry C, Taoussi A, Trepanier M, Paris J. Economic assessment of rural district heating by bio-steam supplied by a paper mill in Canada. Bull Sci, Technol Soc 2008;28(2):159–73.

[8] ASHRAE. HVAC applications. American society of heating, refrigeration and air- conditioning engineers; 1999. [9] Nijjar SJ, Fung AS, Hughes L, Taherian H. District heating system design for rural Nova Scotia communities using building simulation and energy usage databases. Trans Can Soc Mech Eng 2009;33(1):51–64. [10] Bruelisauer M, Meggers F, Leibundgut H. Choosing heat sinks for cooling in tropical climates. Front Archit Res 2013;2:292–300. http://dx.doi.org/10.1016/j.foar.2013. 05.004. [11] Difs K, Danestig M, Trygg L. Increased use of district heating in industrial processes: impact on heat load duration. Appl Energy 2009;86:2327–34. [12] Lo A, Lau B, Cheng V, Cheung P. Challenges of district cooling system (DCS) Implementation in Hong Kong. World SB14; 2014. p. 1–9. [13] Sven Werner, International review of district heating and cooling, Energy 137 (2017), 617-631 [14] A. E. Hajiah, F. Alghimlas and G.P. Maheshwari, Suitability of District Cooling for Kuwait, 10th International Symposium on District Heating and Cooling: September 3 - 5, 2006, Conti-Campus, Hanover University of Technology, Hanover/Germany. 2014

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[15] Schrecengost R., The world’s largest CHW plant: Pearl of Qatar plantengineering.com/single-article/the-worlds-largest-chw-plant-pearl-ofqatar/d3cb500f6facb8fe09a03dedcce8cfa6.html > [accessed March 22, 2017].

[16] IDEA Industry News. Johnson controls supplies energy efficient York chillers in first district cooling project in Kuwait 2015 < http://www.districtenergy.org/blog/ 2015/02/03/johnson-controls-supplies-energyefficient-york-chillers-in-first- district-cooling-project-in-kuwait/ > ; n.d. [accessed March 22, 2017]. [17] Reihav C, Werner S. Profitability of sparse district heating. Appl Energy 2008;85:867–77.

[18] Nilsson SF, Reihav C, Lygnerud K, Werner S. Sparse district-heating in Sweden. Appl Energy 2008;85:555– 64.

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[19] DesignBuilder Software, V5.5., DesignBuilder Software Ltd (www.designbuilder.co.uk), Gloucestershire, UK, 2018.

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[20] Parsons Brinckerhoff, Al Mutlaa District Cooling Concept Design Report, 3514170A-BEL,2015 www.pbworld.com. [21] CEDRO, Army Sustainability Workshop, Presented by Lebanon Green Building Council, http://www.cedroundp.org/content/uploads/event/160107071703727~E.AliBerro-Higheffeciencyplumpingfixtures.pdf

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[22] Magdi Rashad, FVB Energy INC, Minneapolis, USA, 2019, Personal Communication. [23] IEA. IEA Statistics: CO2 emissions from fuel combustion. 2012ed. Report for the Organization for Economic Cooperation and Development. Paris(France); 2012.

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[24] Oxford Business Group, The Report – Kuwait (2015) www.oxfordbusinessgroup.com/country/Kuwait.

Table 1: Unit Capital Cost Parameters for DC System

Parameter

Selected Values

Remarks

Unit Cost of DC Plant Facility (UCPF)

$5250/kW ($1500/RT)

Installed kW (RT)

Unit Cost of Pipe Network (UCP)

CP = 1.87D + 479.69 ($/m)

D pipe diameter (mm)

Energy Transfer Unit (ETU)

$700/ kW ($200/ RT)

Installed kW (RT)

Unit Cost of Power Station (UCPP)

1,335 ($/kW)

Combined Cycle

Discount Rate (d) %

3

Inflation Rate (IR) %

1.5

Life Cycle (N)

24

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Years

Table 2: Operation & Maintenance Unit Cost Parameters for DC System

Parameter

Selected Values $118/MWh

Water Cost Rate

$3/3.7 m³ ($3/1000 gallons)

Including everything. (O&M cost, labour cost, etc.)

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Electric Utility Rate

Remarks

(Installed kW/RT) Including everything except water & electricity

Annual Chemical Treatment Cost

$0.00875/kWh ($0.0025/RT-h)

Annual cooling load

Annual Insurance Rate %

0.75

% of total CIC cost

0.44/MWh

Annual Cooling load

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Annual Water Consumption (1000 gallons)

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$175/kW ($50/RT)

Annual plant facility of O&M Cost

Table 3: Almutlaa City Cooling Load & Electric Power Consumption.

RTU

VRF

DC

Units

Peak Cooling Load Demand

4,348.8

4,348.8

4,348.8

MW

Maximum Capacity Installed (MCI)

5,047.2

3,949.2

3,511.2

MW

Annual Cooling Load Demand

12,153.6

12,069.6

11,709.6 GWh/year

Peak Electric Power Demand (PEPD) 1,761.6

1,737.6

888.0

MW

Annual Electric Power Consumption

4,861.2

3,711.6

3,134.4

GWh/year

Number of Cooling Units

220,800

110,400

624

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Parameters

Table 4: Recommended Maximum Velocity

125 - 80

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< 80

3.5 2.5

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150 +

Maximum Velocity

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Pipe Diameter (mm)

1

Table 5: Capital and Operation & Maintenance Cost Parameters for RTU and VRF Systems

RTU

VRF

Remarks

Price for Indoor & Outdoor Units

$600/RT

$2650/RT

Installed RT

Annual Maintenance & Labour & Spare Parts

$270

$160

Per outdoor units

Life Cycle (N)

8

12

Years

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Parameter