Multi-technology collaborative innovation: Liquid cooling technology must overcome challenges in efficient heat transfer and system reliability. Water-saving cooling sources need to achieve low water-efficiency temperature (WET) and coordinate dry and wet cooling methods. Power supply, distribution, and energy storage must solve source-grid-load-storage matching issues and enhance full-process efficiency. Coordinating innovations across these areas is highly complex.
Intelligent PUE optimization closed loop: Intelligent control of HVAC and power systems should be based on time sequence prediction and reinforcement learning to surpass human expert-level optimization. This demands advanced algorithms and strong engineering implementation.
Technology implementation and adaptation: Hardware innovation must comply with policies and fit industry needs, while AI operations must integrate with existing platforms and tools. Successfully combining and implementing these poses significant challenges.
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