Hyperbola Cooling Tower Data Center Refrigerant Control
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Solution Overview
Problem
Traditional water-side natural cooling systems in data centers face limitations in energy efficiency, struggling to meet stringent Power Usage Effectiveness (PUE) requirements, especially in regions like Beijing, with high water temperatures offering minimal improvement potential.
Innovation Solution
A cooling system incorporating a hyperbola cooling tower, compressor, condenser, primary and secondary fluorine pumps, throttling apparatus, and a server that calculates and adjusts the operation frequency of the compressor based on data information, refrigerant transportation amounts, and environmental conditions to optimize refrigerant distribution across the data center.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional water-side natural cooling system with high water temperature is adopted, then the system can provide cooling source in water-side free natural cooling manner, but the energy efficiency has limited improvement space and cannot meet PUE limiting value requirements
Solution Approach 1:
The system divides the data center into multiple cooling areas with independent evaporators and refrigerant circulation paths. Each area can be controlled independently with its own secondary fluorine pump and throttling apparatus, allowing optimized refrigerant distribution to different zones based on local cooling demands, thereby improving overall energy efficiency without requiring complete system replacement
Solution Approach 2:
The system employs dynamic control through a server that receives data from sensors throughout the system and calculates optimal compressor operation frequencies in real-time. The throttling apparatus and pumps adjust refrigerant flow dynamically based on calculated requirements, enabling the system to adapt to varying cooling loads and improve energy efficiency under different operating conditions
2Productivity
If compressor operation frequency is increased to meet refrigerant transportation requirements, then cooling capacity is improved, but energy consumption increases
Solution Approach 1:
The system implements a feedback control mechanism where sensors continuously monitor temperatures, pressures, and flow rates throughout the refrigeration system. The server receives this data, calculates the actual refrigerant transportation requirements, and adjusts the compressor operation frequency accordingly. This closed-loop feedback ensures the compressor operates at the minimum necessary frequency to meet cooling demands, optimizing the balance between productivity and energy consumption
Solution Approach 2:
The system dynamically changes the compressor's operating parameters (frequency, speed) based on real-time calculations of refrigerant transportation requirements. By adjusting these parameters continuously rather than operating at fixed speeds, the system achieves optimal productivity while minimizing energy consumption at each operating point
3Adaptability or versatility
If refrigerant transportation amount is increased to meet cooling demands in all areas, then cooling coverage is improved, but system energy consumption increases
Solution Approach 1:
The system segments the refrigerant distribution network into multiple independent zones, each with its own evaporator, secondary fluorine pump, and throttling apparatus. This allows refrigerant to be transported only to areas that require cooling, rather than forcing refrigerant through the entire system. The segmented architecture enables selective area cooling, improving adaptability while reducing energy consumption by eliminating unnecessary refrigerant circulation
Solution Approach 2:
Each cooling area is equipped with local sensors and control mechanisms (secondary fluorine pump, throttling apparatus) that enable independent adjustment of refrigerant flow based on local cooling demands. This local quality control allows the system to provide adequate cooling coverage across all areas while optimizing refrigerant distribution to match actual needs in each zone, reducing overall energy consumption
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 system significantly reduces energy consumption by dynamically adjusting refrigerant transport and compressor operation frequency, enhancing energy efficiency and meeting stringent PUE requirements.
Implementation Method 1
The condenser is configured to cool the refrigerant transported from the compressor and transport the refrigerant to the primary fluorine pump
Implementation Method 2
The evaporator is configured to release the refrigerant
Implementation Method 3
A cooling system incorporating a hyperbola cooling tower
Data Source
AI summary
The embodiments of the present application provide a cooling system for data center based on a hyperbola cooling tower. The cooling system includes a compressor, a condenser, a primary fluorine pump, a secondary fluorine pump, a throttling apparatus, an evaporator, and a server. The server is configured to receive data information uploaded from the compressor, the condenser, the primary fluorine pump, the secondary fluorine pump, the throttling apparatus, and the evaporator, calculates the operation frequency of the compressor based on the data information, and control the condenser, the primary fluorine pump, the secondary fluorine pump and the throttling apparatus to transport the refrigerant to the evaporator.