Space-saving high-density modular data systems and energy-efficient cooling systems
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Solution Overview
Problem
Traditional data center cooling systems are inefficient, requiring large initial and operational costs, and are not adaptable to fluctuating IT loads or high-density data centers, often wasting energy by cooling the entire facility rather than specific areas and struggling with geographical limitations.
Innovation Solution
The modular data pod system with a close-coupled cooling system that uses polygonal shapes to efficiently arrange server racks, allowing for natural convection and mechanical assistance to cool specific areas, reducing mechanical refrigeration capacity and energy consumption, and being deployable in various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If traditional large-scale cooling infrastructures are used, then the entire data center can be cooled, but the initial capital, operation, and maintenance costs are high
Solution Approach 1:
The patent divides the data center into multiple modular cooling zones, each with its own cooling infrastructure. This allows selective cooling of only the areas that require it, rather than cooling the entire facility. The modular approach enables independent operation and optimization of each cooling zone, reducing overall energy consumption and operational costs.
Solution Approach 2:
The patent implements localized cooling systems that provide different cooling intensities and methods to different areas based on their specific thermal loads and requirements. High-density computing areas receive more aggressive cooling, while low-density areas use passive or minimal cooling, optimizing energy usage according to local conditions.
2Temperature
If traditional chiller plants are designed to cool the entire data center, then full coverage is achieved, but energy is wasted on areas that do not need cooling
Solution Approach 1:
The data center is segmented into multiple thermal zones with independent cooling control. Each zone can be cooled independently based on its actual thermal load, preventing energy waste from cooling empty or low-density areas. The segmentation allows for dynamic activation and deactivation of cooling zones based on real-time requirements.
Solution Approach 2:
The cooling system is designed to be dynamically adjustable, with cooling capacity and activation status changing based on real-time thermal loads and operational requirements. This dynamic approach allows the system to adapt to fluctuating demands and avoid unnecessary energy consumption during periods of low load.
3Temperature
If traditional cooling systems are designed based on peak power consumption capacity, then sufficient cooling is provided, but efficiency drops significantly during load fluctuations
Solution Approach 1:
The cooling system is designed with dynamic capacity adjustment capabilities, allowing each modular zone to scale its cooling output according to actual thermal loads. This prevents the efficiency loss associated with operating oversized cooling equipment at partial load, as each zone operates at or near optimal capacity regardless of overall data center load fluctuations.
Solution Approach 2:
The modular cooling zones are pre-configured with appropriate cooling capacities for their designated functions, allowing them to activate immediately at optimal efficiency when needed, rather than requiring the entire system to be scaled up or down in response to load changes.
4Use of energy by stationary object
If air-cooled free cooling systems are used, then reduced cooling costs are achieved, but the system operates only in cool, dry-climate environments
Solution Approach 1:
The modular cooling system is designed to accommodate multiple cooling methods and configurations within a unified framework. Each modular zone can be equipped with appropriate cooling technology based on local environmental conditions, making the overall system adaptable to various geographical locations and climate types while maintaining cost efficiency.
Solution Approach 2:
The system allows for parameter adjustments in cooling methodology and intensity based on environmental conditions. In cool, dry climates, passive air-cooled free cooling is utilized for maximum energy efficiency. In other environments, the system can transition to active cooling methods with refrigerants or liquid cooling, maintaining operational effectiveness across diverse geographical conditions.
5Adaptability or versatility
If adiabatic-assisted cooling systems are used, then expanded geographical reach is achieved, but the systems are incapable of providing sufficient cooling to high density data centers
Solution Approach 1:
The patent combines multiple cooling methodologies within a single modular system architecture. Adiabatic cooling, free cooling, and active refrigeration systems can be integrated and operated simultaneously or independently within different modular zones, allowing the system to achieve both geographical adaptability and sufficient cooling capacity for high-density areas.
Solution Approach 2:
Different cooling methods are applied to different areas based on their specific requirements. High-density computing zones receive intensive active cooling, while lower-density areas may use adiabatic or passive cooling methods. This localized approach ensures sufficient cooling capacity where needed while maintaining geographical adaptability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution provides a cost-effective, energy-efficient, and scalable cooling system that can handle high-density data centers, reducing energy waste and operational costs while maintaining efficient cooling performance across different geographical conditions.
Implementation Method 1
allowing for natural convection and mechanical assistance to cool specific areas
Implementation Method 2
allowing for natural convection and mechanical assistance to cool specific areas
Data Source
AI summary
A space-saving, high-density modular data pod system and an energy-efficient cooling system are disclosed. The modular data pod system includes a central free-cooling system and a plurality of modular data pods, each of which includes a heat exchange assembly coupled to the central free-cooling system, and a distributed mechanical cooling system coupled to the heat exchange assembly. The modular data pods include a data enclosure having at least five walls arranged in the shape of a polygon, a plurality of computer racks arranged in a circular or U-shaped pattern, and a cover to create hot and cold aisles, and an air circulator configured to continuously circulate air between the hot and cold aisles. Each modular data pod also includes an auxiliary enclosure containing a common fluid and electrical circuit section that is configured to connect to adjacent common fluid and electrical circuit sections to form a common fluid and electrical circuit that connects to the central free-cooling system. The auxiliary enclosure contains at least a portion of the distributed mechanical cooling system, which is configured to trim the cooling performed by the central free-cooling system.