Edge Node Power Manager Adaptive Energy Switching
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Solution Overview
Problem
The reliability of renewable energy sources in power grids is challenged by their dependency on variable input conditions, such as sunlight or wind, which can lead to inconsistencies in power supply and increased emissions compared to conventional energy sources.
Innovation Solution
A centralized edge resource orchestrator manages power distribution by utilizing a power manager that processes data on energy sources and workloads, performing trend analysis and credit optimization to allocate energy sources effectively, ensuring efficient and reliable power supply by switching between energy sources as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If renewable energy sources are used to power edge nodes, then emissions are reduced and environmental sustainability is improved, but reliability of power supply deteriorates due to variable input conditions
Solution Approach 1:
The power manager dynamically adjusts power allocation and switching between energy sources based on real-time conditions. It continuously monitors renewable energy availability and workload requirements, adapting the power supply strategy to maintain reliability while maximizing renewable energy usage. This dynamic approach allows the system to respond to variable input conditions without compromising power supply stability.
Solution Approach 2:
The power manager acts as an intermediary between renewable energy sources and edge nodes, mediating the power supply relationship. It buffers the variability of renewable sources through intelligent power allocation and switching mechanisms, decoupling the direct connection between variable renewable input and constant power requirements of edge nodes, thereby ensuring reliable power supply while maintaining high renewable energy utilization.
2Productivity
If multiple energy sources are monitored and managed to optimize renewable energy usage, then energy allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The power manager implements self-service mechanisms by automatically monitoring energy sources, evaluating their status, and making switching decisions without external intervention. The system autonomously tracks renewable energy availability, assesses workload requirements, and adjusts power allocation in real-time, reducing the need for complex external control infrastructure while maintaining high energy allocation efficiency.
Solution Approach 2:
The power manager optimizes energy allocation by continuously changing operational parameters such as power allocation ratios, switching thresholds, and monitoring frequencies based on real-time conditions. This parameter-driven approach allows the system to adapt to varying renewable energy availability and workload demands without requiring complex structural changes, thereby improving energy allocation efficiency while controlling system complexity.
3Adaptability or versatility
If power management decisions are made in real-time based on energy source and workload data, then adaptability to changing conditions is improved, but processing time and computational requirements increase
Solution Approach 1:
The power manager performs preliminary actions by pre-evaluating energy source status and establishing switching thresholds before actual power management decisions are needed. It proactively monitors renewable energy availability and pre-configures power allocation strategies, so when switching decisions are required, the system can execute them rapidly without extensive real-time computation, thereby reducing processing time while maintaining high adaptability.
4Object-generated harmful factors
If renewable energy sources with variable input are used, then environmental sustainability is improved, but power supply consistency deteriorates
Solution Approach 1:
The power manager dynamically adjusts power allocation to compensate for variability in renewable energy input. By continuously monitoring energy source status and adjusting power distribution in real-time, the system maintains consistent power supply to edge nodes despite fluctuations in renewable energy availability, thereby ensuring power supply consistency while maximizing renewable energy usage.
Solution Approach 2:
The power manager implements feedback mechanisms by continuously monitoring both energy source status and power supply conditions. This feedback loop allows the system to detect variations in renewable energy input and immediately adjust power allocation strategies to maintain consistent power delivery to edge nodes, ensuring power supply stability while maintaining high renewable energy utilization.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods are disclosed for adaptive platform power management. These improve energy source management through switching energy sources of an edge node by incorporating memory, machine readable instructions, and processor circuitry to execute the functions of: evaluate operational parameters of a first energy source connected to a node and a second energy source connected to the node; determine an energy source to run a workload of the edge node based on a comparison of a first renewability to a second renewability, the evaluation of the operational parameters, and a power requirement of the workload, wherein the preferred energy source is the first energy source or the second energy source; and cause the edge node to switch to the preferred energy source.