Energy Storage Pool Scheduling for Battery Wear Leveling
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Solution Overview
Problem
Existing battery backup systems in data centers operate independently, leading to uneven wear and waste of resources, resulting in increased operation and maintenance workload and costs.
Innovation Solution
A resource scheduling method and apparatus for an energy storage device pool that dynamically allocates power resources based on demand, implementing wear leveling and pooling management to ensure even usage and extended device lifespan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If backup batteries are fixedly installed in each cabinet to supply power independently, then data center reliability is ensured, but operation and maintenance workload increases and resources are wasted due to uneven wear
Solution Approach 1:
Multiple independent battery backup systems in different cabinets are merged into a unified energy storage device pool. The scheduling device coordinates resource allocation across all cabinets, combining previously isolated systems into a collaborative network that shares power resources and reduces overall complexity.
Solution Approach 2:
Energy storage devices in the pool are designed to serve multiple functions and multiple cabinets simultaneously. A single energy storage device can supply power to different cabinets at different times, making the system universal rather than dedicated to a single cabinet, thereby reducing total device count and maintenance burden.
2Reliability
If backup batteries are fixedly installed in each cabinet, then power supply reliability is ensured, but resource utilization is inefficient due to uneven wear and lack of unified management
Solution Approach 1:
The system transitions from static, fixed battery assignments to dynamic resource allocation. The scheduling device continuously monitors power demands and energy storage states, dynamically adjusting which energy storage devices supply power to which cabinets based on real-time conditions, thereby optimizing resource utilization and preventing uneven wear.
Solution Approach 2:
The scheduling device implements feedback mechanisms by monitoring the states of energy storage devices and power consumption patterns. Based on this feedback, it adjusts resource allocation decisions to balance wear across devices and optimize energy utilization, ensuring no single device is overused while maintaining reliable power supply.
3Reliability
If independent battery backup systems are used in each cabinet, then cabinet-level power reliability is achieved, but costs increase due to inability to implement unified management
Solution Approach 1:
Multiple cabinet-level backup systems are merged into a unified energy storage pool, reducing the total quantity of battery devices needed. By combining resources, the system achieves the same or better reliability coverage across all cabinets while reducing overall costs through shared infrastructure and optimized device utilization.
Data Source
AI summary
A resource scheduling method is provided. The energy storage device pool includes at least one energy storage device. One example method includes: receiving a resource scheduling application request, determining a target energy storage device from the energy storage device pool based on the resource scheduling application request, and allocating an electric power resource to a power consumption device by using the target energy storage device.