“As AI workloads continue to drive higher power densities, the challenge is no longer just about providing more compute. It is about ensuring that power, cooling, controls, resilience and sustainability are engineered as an integrated system. Continued support for STDCT from partners such as Eaton enables long-duration, utility-scale studies that translate research insights into practical solutions for tropical data centre operations.” — Prof Lee Poh Seng, Head (Mechanical Engineering), and Programme Director (Sustainable Tropical Data Centre Testbed).
The Sustainable Tropical Data Centre Testbed 2.0 (STDCT 2.0) is expanding its collaboration with Eaton, which has committed about S$3 million across Phase 1 and Phase 2 of the programme. The partnership will support the validation of AI-driven, high-density data centre power architectures optimised for tropical operating conditions.
Since participating at the inception of STDCT 1.0 in 2022, Eaton has contributed equipment and engineering expertise to the testbed’s ongoing trials. For STDCT 2.0, the collaboration will deepen further, moving towards integrated, modular power solutions designed for GPU-powered workloads and next-generation deployments.
“Eaton’s expanded participation in STDCT 2.0 reflects the kind of sustained industry–academia collaboration that is essential if we are to translate research into deployable solutions for next-generation data centres,” Prof Lee added.
A key feature of this next phase is Eaton’s 2.5-megawatt medium voltage solid state transformer container, which will be showcased at Data Centre World 2026 before being installed at Jurong Island for live trials and detailed data collection.
This collaboration builds on a wider effort with JTC Corporation to transform Jurong Island into a living testbed that brings together academia and industry to evaluate and deploy sustainable innovations for tropical data centre environments. Hosted by CDE, the initiative embodies CDE’s vision of harnessing design, engineering and innovation to create solutions that are not only technically advanced, but also sustainable, practical and impactful for society. The insights generated through these trials will help inform future designs and standards for increasingly dense, AI-driven operations.
