Cooling CM: District Cooling

In A Glance

This calculation module helps assess the potential for developing district cooling (DC) networks in a selected area. It evaluates the cooling needs and the distribution of building space to determine where a DC grid could be more cost-effective than conventional cooling methods. The module conducts a techno-economic comparison of connecting a 100 x 100 m raster cell to a DC grid versus using conventional cooling. Cells that are more economically viable for DC are identified and grouped to form a specific DC region within the city.

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Introduction

This calculation module is designed to provide local energy planners with a preliminary assessment and overview of the district cooling (DC) potential in their region, including cost estimates. The module takes advantage of the economies of scale offered by DC networks over individual cooling systems, making it particularly beneficial for areas with high cooling demands.

DC networks typically center around high-demand zones, such as hospitals, office buildings, and grocery stores. Considering this, the module identifies specific locations within a city (LAU2 region) where such high-demand sites coincide. These points, referred to as "anchor points," are potential centers for DC networks. Areas around these anchor points, possibly high residential zones, could benefit from lower cooling costs due to the economies of scale achieved by connecting to a DC network, even when including the costs of grid construction.

The feasibility of district cooling in these areas is assessed using the levelized cost of district cooling, which incorporates grid costs, pumping costs, and the costs of the cooling source. The calculation takes into account the total demand for cooling, the potential coverage of the DC network, and the costs associated with construction and operation. Comparing the levelized costs of district cooling against the levelized cost of cooling from the individual supply, the calculation module identifies feasible areas for district cooling. Additionally, it evaluates the average pipe diameters per cell and the total network length per identified region. This could also aid as a vital tool for planning the system.

This module thus identifies clusters of cells where district cooling is feasible and outlines the economic and practical benefits of establishing a DC network in those areas.

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Inputs And Outputs

Inputs

Average Electricity Price: This refers to the typical retail electricity prices, which are essential for estimating the operational costs of individual cooling systems. For district cooling (DC), these prices are adjusted downward to reflect the more favorable rates often available to larger-scale, industrial operations.
Estimated Cooling Days in a year: Enter the average number of days in your region that require cooling. Based on this, the model calculates the peak load from the annual total space cooling demand.
COP District Cooling Supply Technology: The average coefficient of performance of large-scale district cooling supply units. The default value is based on literature that represents the average values of such large systems
COP Individual Cooling Supply Technology: The average coefficient of performance of individual/conventional space cooling units like air-conditioners.
Discount Rate: Based on present market values
Lifetime-District Cooling: Total average lifetime of the overall district cooling system.
Lifetime-Individual Supply Technology: Total average lifetime of the individual supply system.
Select the cold demand density layer: Select default layers or external layers if available.
Select the gross floor area density layer: Select default layers or external layers if available.
Select the gross floor area density layer non-residential: Select default layers or external layers if available.

Advanced Inputs

Network Delta T: The difference in the supply and return temperatures of the district cooling grid.
Threshold of Non-Residential GFA Ratio: This parameter sets the threshold for identifying anchor points. Only cells with a non-residential floor area equal to or exceeding this threshold will be classified as anchor cells.
Unit CAPEX for Individual Supply System: The investment costs of the individual supply system are used to calculate the threshold LCOC of individual supply systems for a given electricity price. The average investment costs for different countries are in [Table - Individual System Costs].
Unit OPEX for Individual Supply System (Euros/MW/Year): The fixed operational costs of the individual supply system are used to calculate the threshold LCOC of individual supply systems for a given electricity price. The average investment costs for different countries are in [Table - Individual System Costs]
Unit CAPEX for District Cooling Supply System: The input is used to calculate the supply costs for the district cooling supply technologies. Average values are provided as default. Only change if more reliable local-level values are available.
Unit OPEX for Individual Supply System (Euros/MW/Year) - The input is used to calculate the supply costs for the district cooling supply technologies. Average values are provided as default. Only change if more reliable local-level values are available. Literature shows values ranging from (3,200-16,000 EUR/MWh)

Table - Individual System Costs [1]

Country	CAPEX (1000€/MW)	OPEX (€/MW/Year)
Cyprus	284.55	11382.02
Austria	285.52	11420.67
Denmark	290.57	11622.72
Estonia	291.24	11649.50
France	286.51	11460.47
Germany	287.30	11491.90
Italy	285.52	11420.69
Poland	285.52	11420.67
Romania	285.90	11436.19
Spain	283.30	11332.18
Sweden	290.56	11622.26

Output

Indicators

Were feasible locations for District Cooling identified?: Shows if feasible locations for District Cooling were identified by the CM. If no, other indicators will not be shown.
Total theoretical cooling demand in GWh within the selected zone: Total demand in the region under evaluation.
Estimated actual cooling demand in GWh within the selected zone: Considering the diffusion of space cooling technologies, the total demand that is actually ready to be connected to the district cooling network.
DC cooling potential in GWh within the selected zone: Based on the model results, the total demand in locations that are techno-economically feasible for further assessment of district cooling under pre-defined assumptions.
Total Peak Covered by District Cooling: Total peak covered by the identified feasible locations.
Potential share of district cooling from total actual demand in the selected zone: Percentage of the total demand in the region that has the potential of DC supply.
Number of Clusters Identified: Total number of identified locations feasible for district cooling under given assumptions.
Annualized Total Costs: Estimates on the total required investment for the development of the identified areas into district cooling networks. This is the sum of grid, pumping, and supply costs.
Annualized Total Grid Costs: Estimates on the grid investment required for the development of the identified areas into district cooling networks.
Total Annual Pumping Costs: Estimates on the investment in pumps required for the development of the identified areas into district cooling networks.
Total Supply Costs: Estimates on the supply investment required for the development of the identified areas into district cooling networks.
Average levelized cost of cooling for Individual Supply: Average levelized cost of cooling for supply via individual solutions. This is used as the threshold for the identification of the district cooling potential area. (It is to be noted that this value is used as a threshold to identify potential district cooling feasible areas. Areas where the cost for construction of the grid is cheaper than individual supply are characterized as potentially feasible. However, since supply and pumping costs are further added to the grid costs of the identified areas, there may be cases where the overall levelized cost of district cooling supply could be higher than the individual costs)
Average levelized cost of distribution grid in the potential feasible area: Average costs for the distribution network.
Average levelized cost of district cooling supply in the potential feasible area (network + pumping + simplified supply): Overall average levelized cost of district cooling grid for all identified potential areas.
Total pipe trench length: Total trench length to be dug, if all identified potential areas, are to be realized as a district cooling grid.

Layers

District Cooling areas and their Potential -Shapefile: Identified areas with all aggregated above parameters per DC area.

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Method

This calculation module operating at a 100x100 meter resolution, evaluates areas where implementing district cooling is economically viable without delving into detailed design specifics. The calculation module is aimed to serve as a planning tool that identifies where district cooling could be applied effectively, guiding preliminary design and investment decisions. Providing a framework that balances technical calculations with economic considerations helps policymakers and planners optimize their strategies for cooling infrastructure development. The details of the methodology is available in [2].

Key Features:

Techno-economic Feasibility: Identifies potential zones for district cooling based on cost-effectiveness.
Pipe Sizing: Estimates necessary pipe sizes using simplified physical calculations adapted to specific cell layouts.
Open Source: Accessible on GitHub for transparency and community involvement.

Module Assumptions:

Considers a limited selection of cooling supply sources for the potential supply of district cooling.
Excludes existing infrastructure to simplify cost calculations.
The connection rate of DC is taken to be the same as the cooling technology diffusion rate in a region.
Assumes a DC as a single technology and the economic assumptions taken for different components of the grid are the same.

Granularity and Technical Details:

Operates with a fine spatial resolution to improve planning accuracy.
Considers only annual peak demand, simplifying the energy demand profile.

Cost and Network Design:

Pipe Diameter Estimation: Combines empirical data with theoretical calculations to determine suitable pipe sizes.
Network Costing: Estimates costs based on the average pipe diameter and projected network length within each cell.
Feasibility Assessments: Utilizes the levelized cost of cooling to identify economically viable areas for DC implementation.

Specific details on the methodology will soon be made available in a peer-reviewed journal paper.

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GitHub Repository Of This Calculation Module

TULEAP District Cooling

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Sample Run

The disctrict cooling calculation module only works on a LAU2 region as this a local energy supply system. Make sure you are on the correct level of area. Select Vienna for this sample run. Figure CM - District Cooling Selection of working region (LAU2)

Now select the basic input parameters. These include the following:
Electricity Price: With this value, the CM calculates the cost of supply from individual systems and then uses it as a threshold to cut off cells where the development of a DC grid is more expensive than individual supply. Use the default value of 150 EUR/MWh.
Estimated cooling days in the Year: With this value, the annual cooling need per cell is converted into peak cooling load. Use the default value of 60 days
COP District Cooling Supply Technology: This is used in calculating the operational costs of the district cooling system. Use the default value as this is the average value for Austria.
COP Individual Cooling Supply Technology: This is used in calculating the operational costs of the individual cooling system. Use the default value as this is the average value for Austria.
For the sample run we take the default values for the discount rate, lifetime district cooling and lifetime individual supply technology

Figure CM - District Cooling Selection of basic input parameters

Next we enter the advanced set of parameters. We use the default values here. The technical values of network delta T and Threshold of Non-residential GFA are standard values from the literature. The cost values represent the average values for Austria.

Figure CM - District Cooling Selection of advanced input parameters

The CM depends on 3 different raster layers as input. For the sample run we take default values. Figure CM - District Cooling Selection of layers

Now click RUN CM. Since the calculation happens on a hectare level, the CM run may take some time depending on the size of the region as well as the defined scenario. Based on our sample Run Scenario the run should take about 15- 20 secs.

Figure CM - District Cooling Run CM

Once the run is completed, you will be able to visualize the results on the map. In the results pane on the right, you will see the results on the total potential coverage, identified number of regions for district cooling as well as different cost components for implementation. Under the defined scenario for Vienna, almost 12% of the cooling need can be supplied from district cooling, fulfilling a peak load of over 440 MW at average supply costs of 192 EUR/MWh.

On clicking the regions in the map you can visualize the different parameters of the individual identified feasible area. For advanced-level users, you can go to the layers tab and scroll to the bottom to find a downloadable shape file with detailed results for each identified cluster of cells.

Figure CM - District Cooling Results

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References

[1] Mitterrutzner B, Callegher CZ, Fraboni R, Wilczynski E, Pezzutto S. Review of heating and cooling technologies for buildings: A techno-economic case study of eleven European countries. Energy 2023;284:129252. DOI: 10.1016/j.energy.2023.129252

[2] Malla, Aadit; Kranzl, Lukas. Strategic planning and viability assessment for implementing district cooling networks. Energy 2025;319:134846. DOI: 10.1016/j.energy.2025.134846

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How To Cite

Aadit Malla, in CITIWATTS-Wiki, CM District Cooling

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Authors And Reviewers

This page was written by Aadit Malla EEG-TU WIEN

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License

Creative Commons Attribution 4.0 International License

This work is licensed under a Creative Commons CC BY 4.0 International License.

SPDX-License-Identifier: CC-BY-4.0

License-Text: https://spdx.org/licenses/CC-BY-4.0.html

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Acknowledgement

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