Power Management Server for Multi-Entity Battery Allocation
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Solution Overview
Problem
Existing power management systems face challenges in efficiently allocating charge and discharge power among multiple facilities sharing a storage battery apparatus, especially when requests are received in a short period, leading to constraints such as remaining charge or power storage amounts, which can result in unfair allocation and inability to handle all requests.
Innovation Solution
A power management server and method that receive requests from multiple entities, monitor power usage, estimate future remaining power storage, and determine allocated power amounts based on usage patterns and constraint conditions, ensuring fair allocation by prioritizing facilities with lower power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If power allocation is based on simple request processing without considering usage patterns, then processing speed is fast, but allocation fairness deteriorates
Solution Approach 1:
The system performs preliminary estimation of future remaining power storage amounts and preliminary determination of allocation ratios based on power usage patterns before final power allocation. This advance preparation enables both fast processing and fair allocation by pre-calculating key parameters.
Solution Approach 2:
The system monitors actual power usage by each entity and feeds this information back into the allocation ratio determination. The allocation ratios are dynamically adjusted based on feedback regarding power usage patterns, ensuring fairness while maintaining processing efficiency.
2Measurement precision
If all requests are processed individually with detailed monitoring, then allocation accuracy is high, but processing time increases
Solution Approach 1:
The system applies partial monitoring and estimation by focusing on key parameters such as power usage patterns and allocation ratios rather than tracking every detail of power consumption. This selective approach maintains sufficient accuracy while reducing processing time.
Solution Approach 2:
The system performs preliminary estimation of future power storage states and preliminary determination of allocation ratios before final allocation decisions. This advance calculation of key parameters enables accurate allocation without the need for exhaustive real-time analysis of all requests.
3Reliability
If power storage constraints are strictly enforced without considering future estimates, then constraint satisfaction is guaranteed, but request fulfillment capability deteriorates
Solution Approach 1:
The system performs preliminary estimation of future remaining power storage amounts before making allocation decisions. This advance estimation enables the system to anticipate future constraint violations and adjust current allocations accordingly, maintaining both constraint satisfaction and request fulfillment capability.
Solution Approach 2:
The system dynamically adjusts power allocations based on estimated future power storage states. Rather than applying static constraints, the allocation ratios are adaptively modified according to projected power availability, enabling the system to satisfy constraints while maximizing request fulfillment.
Data Source
AI summary
A power management server comprises a controller configured to manage a storage battery apparatus shared by a plurality of entities, and a receiver configured to receive requests each including an information element indicating a requested amount of power including at least one of a virtual discharge amount and a virtual charge amount of the storage battery apparatus. The controller is configured to manage power usage of the storage battery apparatus for each of the plurality of entities. The controller is configured to manage a virtual remaining power storage amount of the storage battery apparatus for each of the plurality of entities. The controller is configured to determine an allocated amount of power for the requested amount of power based on the power usage, when a constraint condition is satisfied by duplication of the requests.