Data Center Cooling Capacity Management for High Density Equipment
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Solution Overview
Problem
Current data center management tools inadequately address cooling performance analysis, leading to over-design and inefficiency due to the inability to accurately determine cooling needs at a granular level, especially with high power density equipment, resulting in hot spots and potential equipment failures.
Innovation Solution
A system and method that determine cooling capacity and power requirements at specific equipment enclosures within a data center, using airflow measurements, temperature data, and weighted summation of airflow sources to provide real-time feedback on remaining cooling and power capacity, enabling precise placement of new equipment and optimization of cooling systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized data centers use high power density equipment to increase computing capacity, then productivity and computing power are improved, but cooling requirements and heat generation increase significantly
Solution Approach 1:
The patent segments the data center into multiple zones with different cooling requirements based on equipment power density. By dividing the facility into distinct thermal zones and assigning different cooling strategies to each zone, the system optimizes cooling capacity allocation rather than uniformly over-provisioning the entire facility.
Solution Approach 2:
The patent implements local quality by providing differentiated cooling solutions tailored to specific equipment zones. High power density equipment receives targeted cooling resources while low power density areas receive proportionally less cooling capacity, matching cooling provision to actual local heat generation patterns.
2Reliability
If data centers are designed with sufficient cooling capacity to handle peak loads, then reliability is improved, but device complexity and cost increase due to over-design
Solution Approach 1:
The patent implements dynamic cooling capacity allocation that adjusts cooling provision based on real-time equipment power consumption and thermal conditions. Rather than static over-provisioning, the system continuously monitors and adapts cooling capacity to match actual demand, maintaining reliability while reducing complexity.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor equipment power density, temperature, and cooling performance to continuously optimize cooling capacity allocation. This closed-loop control ensures adequate cooling for peak loads while preventing over-design through real-time adjustment based on actual operational conditions.
3Measurement precision
If existing cooling design tools use computational fluid dynamics to model cooling performance, then measurement precision is improved, but loss of time and cost increase due to complexity
Solution Approach 1:
The patent employs simplified analytical models and estimation techniques that provide sufficiently accurate cooling performance predictions without the computational burden of full CFD analysis. These lighter-weight tools deliver acceptable precision for design decisions while dramatically reducing time and cost requirements.
Solution Approach 2:
The patent changes the approach from detailed spatial CFD modeling to parameter-based thermal zone analysis. By focusing on key thermal parameters and aggregate cooling performance rather than detailed fluid dynamics, the system achieves adequate measurement precision for design purposes while reducing computational complexity and time requirements.
4Ease of operation
If data centers allocate cooling capacity uniformly across all equipment, then ease of operation is improved, but productivity decreases due to inefficient cooling resource utilization
Solution Approach 1:
The patent creates a universal cooling management framework that automatically adapts to different equipment types and power density zones. The system provides a unified approach that simplifies operation while internally optimizing cooling allocation based on local requirements, eliminating the need for complex manual configuration.
Solution Approach 2:
The patent implements self-service cooling allocation where the cooling system automatically adjusts capacity distribution based on monitored equipment power consumption and thermal conditions. This autonomous optimization improves cooling efficiency without requiring manual intervention, maintaining ease of operation while eliminating waste from uniform allocation.
Data Source
AI summary
Systems, methods and non-transitory computer-readable mediums are provided for determining data center resource requirements, such as cooling and power requirements, and for monitoring performance of data center resource systems, such as cooling and power systems, in data centers. At least one aspect provides a system and method that enables a data center operator to determine available data center resources, such as power and cooling, at specific areas and enclosures in a data center to assist in locating new equipment in the data center.