Data Center Cooling Capacity Prediction via Layout Analysis
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Solution Overview
Problem
Current data center management tools lack an efficient method to predict maximum cooler and rack capacities, leading to suboptimal cooling performance and energy usage.
Innovation Solution
A computer-implemented method and system that evaluates data center equipment by determining maximum cooler and rack capacities based on layout, power draw, and cooling performance, using air flows and ambient temperature to display capacity indicators and optimize cooling loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional data center management tools are used, then standardized design methodology is provided, but maximum cooler and rack capacities cannot be accurately predicted
Solution Approach 1:
The evaluation system segments the data center into discrete components (coolers, racks, equipment) and evaluates each independently while considering their interactions. This allows accurate capacity prediction for individual components without requiring complex whole-system modeling, resolving the contradiction between prediction accuracy and system complexity.
Solution Approach 2:
The system performs preliminary evaluation of cooler and rack capacities before final configuration decisions are made. By calculating maximum capacities in advance based on layout and power draw data, the system enables informed planning without requiring complex real-time analysis, thus improving prediction accuracy while managing complexity.
2Productivity
If detailed layout and power draw data are collected for accurate capacity determination, then cooling performance optimization is achieved, but data collection and processing time increases
Solution Approach 1:
The system collects and processes layout and power draw data in advance during the design and planning phases, before cooling performance optimization is needed. This preliminary data preparation eliminates the need for time-consuming data collection during operational optimization, thus achieving cooling performance improvement without significant time loss.
Solution Approach 2:
The evaluation system automatically collects and processes data from existing data center infrastructure and configuration files, minimizing manual data collection efforts. This self-service approach reduces the time required for data gathering while maintaining the accuracy needed for cooling performance optimization.
3Quantity of substance
If maximum rack capacity is increased to improve space utilization, then data center density improves, but cooling load increases beyond cooler capacity
Solution Approach 1:
The system calculates the maximum rack capacity based on the cooling capacity of available coolers and the thermal environment. This feedback mechanism ensures that rack capacity increases are matched by adequate cooling capacity, preventing situations where increased density leads to excessive cooling loads that exceed cooler capabilities.
Solution Approach 2:
The system dynamically adjusts the determined rack capacity parameters based on cooler capacity, ambient temperature, and airflow conditions. By changing these parameters to reflect actual cooling capabilities, the system optimizes space utilization while ensuring cooling loads remain within acceptable limits for the available cooling infrastructure.
Data Source
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AI summary
A system and method for evaluating equipment in a data center, the equipment including a plurality of equipment racks, and at least one cooling provider. In one aspect, a method includes receiving data regarding each of the plurality of equipment racks and the at least one cooling provider, the data including a layout of the equipment racks and the at least one cooling provider, a power draw value for each of the equipment racks, and a maximum cooler capacity value for the at least one cooling provider; storing the received data; determining cooling performance of at least one of the plurality of equipment racks based on the layout; determining a cooling load for the at least one cooler and a difference between the cooling load and the maximum cooler capacity value; for each equipment rack, determining a maximum rack capacity based on the layout and the difference between the cooling load and the maximum cooler capacity value; and displaying an indication of the maximum rack capacity for each equipment rack.