Data Center HVAC Control Using Real-Time Thermal Load Prediction
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Solution Overview
Problem
Existing thermal conditioning systems for data centers often fail to optimize energy usage efficiently, as they rely on fixed temperature setpoints and do not account for varying heat loads across different areas of the data center.
Innovation Solution
A thermal optimization control system that processes real-time and predicted IT load data to dynamically adjust the thermal management of data centers, optimizing the operation of HVAC systems to reduce energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If fixed temperature setpoints are used for thermal conditioning, then the HVAC system operates simply and reliably, but energy usage increases due to inability to adapt to varying thermal loads
Solution Approach 1:
The patent implements dynamic thermal management by transitioning from fixed temperature setpoints to variable setpoints that adapt in real-time to actual thermal loads. The system continuously monitors IT equipment power consumption and adjusts HVAC parameters (temperature, humidity, airflow) dynamically, allowing the system to respond to varying thermal conditions while optimizing energy usage.
Solution Approach 2:
The system employs feedback mechanisms by monitoring IT load data, thermal conditions, and HVAC performance in real-time. This feedback loop enables the system to adjust thermal conditioning strategies based on actual equipment needs, preventing energy waste during low-load periods while ensuring adequate cooling during high-demand periods.
2Use of energy by stationary object
If uniform thermal conditioning is applied across all data center areas, then the HVAC system is simple to operate, but energy efficiency decreases due to ignoring local thermal variations
Solution Approach 1:
The patent applies local quality by implementing zone-based thermal management where different areas of the data center receive customized thermal conditioning based on their specific thermal loads and requirements. The system divides the data center into multiple zones, each with independent temperature and humidity control, allowing optimized energy usage in each location rather than applying uniform conditioning across the entire facility.
Solution Approach 2:
The system segments the data center thermal management into independent controllable zones based on IT equipment distribution and thermal characteristics. Each zone can be controlled separately with its own setpoints and parameters, enabling granular optimization of energy usage while maintaining overall system manageability through centralized control architecture.
3Use of energy by stationary object
If real-time thermal optimization is implemented, then energy usage is reduced, but system complexity and measurement requirements increase
Solution Approach 1:
The patent introduces an intermediary thermal optimization control system that acts as a mediator between IT load monitoring and HVAC control. This intermediary layer processes thermal data, predicts future thermal conditions, and generates optimized setpoints for the HVAC system, thereby reducing the complexity burden on both the monitoring and control systems while enabling sophisticated energy optimization.
Solution Approach 2:
The system performs preliminary actions by predicting future thermal loads based on historical data and IT workload patterns. This allows the HVAC system to proactively adjust settings in anticipation of thermal changes, optimizing energy usage before peak loads occur and reducing the need for complex real-time reactive control.
Data Source
AI summary
A thermal optimization control includes processing circuitry. The processing circuitry is operable to receive information from a building housing at least one computer server, with the information including at least current thermal load. The processing circuitry is operable to control an associated HVAC system for at least an area of the building where the at least one computer server is housed. The processing circuity is operable to optimize the operation of the HVAC system based upon the current and an expected upcoming thermal load on the area of the building where the server is received to reduce energy usage by the HVAC system. A method and building are also disclosed.