Control method and system for wide-area optimal efficiency of data center cold source system
Through layer-by-layer optimization and reverse analysis, the control parameters of the data center cooling system are determined, which solves the problem that the existing technology is difficult to reduce the energy consumption of the cooling system, minimizes the energy consumption of the cooling system, and reduces the operating costs of the data center.
CN119730201AActive Publication Date: 2025-03-28SHANGHAI EXXON CO LTD
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Patent Information
- Application Number
- CN202510222637.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-27
- Publication Date
- 2025-03-28
- Estimated Expiration
- 2045-02-27
AI Technical Summary
Technical Problem
Existing data center cooling systems have difficulties in reducing overall energy consumption, resulting in high operating costs.
Method used
By setting the overall target and finding optimization layer by layer, the energy consumption models of each cooling component are obtained, the correlation variables and non-correlated variables are determined, the system energy consumption model is fitted, and the target correlation variable value is obtained in reverse analysis as the control parameters of the cooling system.
Benefits of technology
It minimizes the operating energy consumption of the entire cooling system and effectively reduces the operating costs of the data center.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses a control method and system for wide-area optimal efficiency of a data center cold source system, and the method comprises the steps: obtaining energy consumption models of all cooling assemblies in a cooling system, determining the correlation variables between all the energy consumption models, and carrying out the transformation of the expressions of the energy consumption models based on the correlation variables, obtaining a fixed component, a variable coefficient value and corresponding energy consumption data in the energy consumption model through historical data, obtaining a plurality of system energy consumption values by adjusting the value of an associated variable, and finally, when the variable function value corresponding to each energy consumption model is a certain value, the system energy consumption value is the lowest, and at the moment, carrying out reverse analysis to obtain an input parameter corresponding to a variable function; therefore, the control parameter for realizing the lowest energy consumption of the whole cooling system can be obtained, the operation energy consumption of the whole cooling system is reduced to the lowest, and the operation cost of the data center is effectively reduced.
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