Power Controller for Dynamic Component Performance Under Power Variability
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Solution Overview
Problem
Data centers face challenges with power fluctuations and variability from renewable sources, leading to inefficiencies and the need for expensive storage or overprovisioning solutions to maintain stable voltage and current.
Innovation Solution
Implementing a power controller module and system operation optimization manager to monitor and adjust the performance of electronic components in response to power fluctuations, allowing nodes to transition between operation levels and prioritize tasks based on availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If storage solutions or overprovisioning are used to maintain stable voltage and current, then power stability is improved, but cost increases
Solution Approach 1:
The system dynamically adjusts component performance levels based on real-time power availability. The power controller monitors power supply conditions and automatically transitions components between different performance levels (e.g., operational modes, clock speeds) to match available power, eliminating the need for expensive static overprovisioning or storage solutions while maintaining stability.
Solution Approach 2:
The invention changes operational parameters of electronic components (such as processing speed, power consumption levels) in response to power availability fluctuations. By adjusting these parameters dynamically, the system maintains stable operation without requiring additional storage infrastructure or overprovisioning, thus reducing cost while preserving stability.
2Use of energy by moving object
If renewable power sources are used, then environmental efficiency is improved, but power variability increases
Solution Approach 1:
The system changes component performance parameters in response to power availability from renewable sources. When power is abundant, components operate at higher performance levels; when power is scarce, performance is reduced. This dynamic parameter adjustment allows the system to embrace renewable energy variability rather than resist it, maintaining operational efficiency while improving environmental sustainability.
Solution Approach 2:
The power controller continuously adapts system performance to match real-time power availability from renewable sources. This dynamic adaptation allows the data center to fully utilize variable renewable power without requiring stabilization infrastructure, thereby improving environmental efficiency while managing power variability through flexible operational adjustments.
3Use of energy by moving object
If power is reduced to match renewable energy availability, then environmental sustainability is improved, but operational performance decreases
Solution Approach 1:
The system dynamically adjusts operational performance levels to match renewable power availability. Performance is not fixed but continuously adapts to power conditions, allowing the system to maximize productivity when power is available and reduce performance when power is scarce. This dynamic approach ensures environmental sustainability while maintaining operational performance as close to optimal as possible under varying conditions.
Solution Approach 2:
The invention changes operational parameters (processing speed, power consumption) in response to power availability. By adjusting these parameters dynamically, the system can reduce performance only when necessary to match renewable power availability, rather than operating at reduced performance continuously. This maintains environmental sustainability while preserving operational performance during favorable conditions.
Data Source
AI summary
In an example implementation consistent with the features disclosed herein, a computer-implemented method includes monitoring power available to a plurality of nodes. Each node corresponding to an electronic component, device, or group of devices. The method includes detecting that the power available to the nodes is outside a power range within which all of the nodes can operate at a full operation level. When the power available to the node is outside the power range, allocation of the available power amongst the nodes is determined and at least some of the nodes are signaled to transition to a mode that utilizes less power.