Host System Incentive Optimization for Energy Balance
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Solution Overview
Problem
Existing optimization systems for individual energy systems, such as EV power stations and industrial electric power storage, do not consider the overall optimal balance of multiple systems, leading to a decrease in optimization effectiveness when systems are operated collectively.
Innovation Solution
An optimization system comprising a host system that communicates with individual systems to derive and apply incentives based on optimization calculation results, ensuring the total energy supply/demand balance is maintained within a predetermined range by repeating optimization calculations until convergence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If individual systems are optimized independently, then each system achieves its own optimization goal, but the total optimization effect of all systems decreases
Solution Approach 1:
The patent merges individual system optimizations with collective optimization by having the host system aggregate optimization results from multiple individual systems and generate unified incentives. This combining approach ensures that individual system optimizations contribute to overall system optimization, resolving the contradiction between individual optimization effectiveness and total optimization effect.
Solution Approach 2:
The patent implements a feedback mechanism where the host system receives optimization results from individual systems, calculates collective incentives, and feeds these incentives back to individual systems. This closed-loop feedback ensures that individual optimizations are aligned with collective goals, preventing the degradation of total optimization effect while maintaining individual system autonomy.
2Productivity
If collective optimization is implemented across multiple systems, then total optimization effect is improved, but system complexity and coordination difficulty increase
Solution Approach 1:
The patent segments the optimization process into two independent but coordinated parts: individual system optimization (performed by each system independently) and collective incentive calculation (performed by the host system). This segmentation reduces host system complexity by avoiding the need for the host to directly control or model each individual system's optimization, while still achieving total optimization effect through incentive alignment.
Solution Approach 2:
The patent introduces incentives as an intermediary mechanism between individual system optimizations and collective optimization goals. Instead of direct complex coordination, the host system uses incentives as a mediator to align individual system behaviors with collective objectives, significantly reducing coordination complexity while maintaining total optimization effectiveness.
3Measurement precision
If iterative optimization calculations are performed, then optimization precision is improved, but calculation time and energy consumption increase
Solution Approach 1:
The patent performs preliminary individual system optimizations before collective incentive calculations. Each individual system independently completes its optimization calculations first, providing ready-made optimization results to the host system. This preliminary action reduces the computational burden during the collective optimization phase, achieving high precision without excessive total calculation time.
Solution Approach 2:
The patent implements iterative optimization only when necessary - performing individual system optimizations independently first, then applying collective incentive adjustments. This partial iteration approach achieves sufficient optimization precision without the excessive calculation time that would result from continuous full-system iterative optimization, balancing precision and time consumption.
Data Source
AI summary
Provided is an optimization system (1) including: a plurality of individual systems (20); and a host system (12) configured to communicate to and from the individual systems (20). Each of the individual systems (20) includes: a device (electric device (30)) which is connected to an energy source (electric power system (22)), and is configured to receive energy from the energy source, or transmit energy to the energy source; and an optimization calculation module (50) configured to execute optimization calculation so that an objective function is minimized under a state in which parameters of the energy through the device are set to the objective function and a constraint condition, respectively. The host system (12) includes a host calculation module (70) configured to derive an incentive based on a plurality of optimization calculation results each derived by a corresponding one of the individual systems (20). The optimization calculation module (50) is configured to again execute the optimization calculation based on the incentive derived by the host calculation module (70).