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Optimising Data Center Locations in Australia

Project Info

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Team Name


TeamDataCentersAuditors


Team Members


3 members with unpublished profiles.

Project Description


The project uses a data-driven framework to assess and rank the optimal locations around Australia based on environmental and operational factors. The analysis includes multiple datasets from bushfire risk, electricity pricing (RRP) and transmission line characteristics to generate scores from attributes such as risk, cost, capability and reliability. The resulting score would highlight the optimal site that balances between efficiency, operational resilience and cost, providing insights for major data-center planning.


#optimisation #efficiency #geolocation #australia #cost optimisation #weather #transmission lines #data centers

Data Story


NATIONAL ELECTRICITY INFRASTRUCTURE

Source:https://digital.atlas.gov.au/datasets/70f23e91102a4d6899a776d093fa08ef_2/explore

Description of Use: Used to retrieve and display electricity infrastructure components (transmission lines and substations) in the Data Centre Frontier prototype. Once imported, the data is used to calculate distances from proposed data centre sites to the nearest transmission line or substation, contributing to the grid sub score.

AUSTRALIAN BUSHFIRE SATELLITE DATA

Source: https://www.kaggle.com/datasets/nagarajbhat/australian-bush-fire-satellite-data-nasa

Description of Use: Used to retrieve satellite-derived bushfire data, including brightness, confidence, and Fire Radiative Power (FRP). This data is then used to assess fire risk around proposed data centre locations and calculate the bushfire sub score in the Data Centre Frontier prototype.

SUBMARINE CABLE DATA [WEB SCRAPING]

Source: https://www.submarinecablemap.com/

Description of Use: Used to retrieve information on submarine cable locations and connectivity. This data informs the data centre network connectivity analysis and is incorporated into the network resilience sub score in the Data Centre Frontier prototype.

DATA CENTER DATASET [WEB SCRAPING]

Source: https://www.datacentermap.com/?utm_source=chatgpt.com

Description of Use: Used to retrieve locations and specifications of existing data centres across Australia. This data supports site selection by allowing comparison of proximity to other facilities, and contributes to the operational efficiency and redundancy scoring in the Data Centre Frontier prototype.

AUSTRALIAN WEATHER DATA

Source: https://www.kaggle.com/datasets/arunavakrchakraborty/australia-weather-data

Description of Use: Used to retrieve historical and current weather conditions, including temperature, rainfall, and wind patterns. This data is used to evaluate environmental risks, cooling requirements, and power efficiency, contributing to the environmental sub score in the Data Centre Frontier prototype.

INTERNET EXCHANGE POINTS (IXPS)

Source: https://www.internetexchangemap.com/?utm_source=chatgpt.com

Description of Use: Used to retrieve locations of internet exchange points across Australia. Data is incorporated to assess connectivity potential and network latency for proposed data centre sites, contributing to the connectivity sub score.

AUSTRALIAN POSTCODE DATA

Source: https://github.com/Elkfox/Australian-Postcode-Data/tree/master?utm_source=chatgpt.com

Description of Use: Used to retrieve postcode boundaries and associated demographic information. This data helps assess regional population density and accessibility for proposed data centre sites, contributing to the logistics and operational sub score in the Data Centre Frontier prototype.


Evidence of Work

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Team DataSets

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Challenge Entries

Data Centres: A Cornerstone of Australia's AI Future

How can we analyse Australia's infrastructure, energy, and geographic data to select locations and operational strategies that will position Australia as the Asia-Pacific's leading AI and cloud computing hub?

#Data-centres-for-2050

Eligibility: Open to all. Teams should use at least one government dataset in their solution, with preference for creative combinations across different data types (infrastructure, energy, telecommunications, geographic, climate, economic, or planning data). Proposals should include clear methodologies for data integration, analysis algorithms, and implementation planning with consideration of real-world deployment challenges

Go to Challenge | 14 teams have entered this challenge.