Power Delivery Network Load Allocation With Hierarchical Optimization

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Solution Overview

Problem

Existing power delivery networks face suboptimal optimization due to the use of different mathematical models for controllable and non-controllable power sources, leading to inefficiencies in cost, reliability, scalability, and computing time.

Innovation Solution

A method that divides the optimization problem into hierarchically structured nonlinear and mixed-integer linear optimization problems, addressing the load distribution between a first power delivery device and a group of devices, using specific mathematical methods tailored to their physical configurations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If a single mathematical model is used for optimizing power delivery network operation, then the optimization can be performed with a unified approach, but the optimization quality deteriorates when dealing with mixed controllable and non-controllable power sources

Engineering Contradiction:

ImproveEase of optimization implementationVSAvoidOptimization quality

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The patent segments the power delivery network into two distinct groups: controllable power delivery devices and non-controllable power delivery devices. Each group is optimized using a specialized mathematical model tailored to its characteristics, rather than applying a single unified model to all devices. This segmentation allows the system to leverage the strengths of different optimization approaches for different device types.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies different mathematical models (different local qualities) to different parts of the system based on their specific characteristics. Controllable devices use one optimization model while non-controllable devices use another, ensuring that each subset receives the most appropriate optimization approach for its nature.

Inventive Principle:

Principle #3Local quality

2Reliability

If different mathematical models are used for controllable and non-controllable power delivery devices, then the optimization quality improves, but the device complexity of the optimization system increases

Engineering Contradiction:

ImproveOptimization qualityVSAvoidOptimization system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

By dividing the optimization problem into separate segments for controllable and non-controllable devices, the system manages complexity through modularization. Each segment can be developed, tested, and maintained independently, reducing the overall system complexity despite using multiple mathematical models.

Inventive Principle:

Principle #1Segmentation

3Reliability

If different mathematical models are used for optimizing power delivery network, then the optimization quality improves, but the computing time increases

Engineering Contradiction:

ImproveOptimization qualityVSAvoidComputing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

Segmenting the optimization problem allows parallel processing of different device groups, potentially reducing total computing time. Each mathematical model can be executed independently on its designated subset of devices, improving computational efficiency.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies optimization only where necessary and appropriate for each device type, rather than applying a comprehensive complex model to all devices. This partial action approach achieves sufficient optimization quality without the excessive computing time that would result from universal application of the most rigorous model.

Inventive Principle:

Principle #16Partial or excessive action

4Adaptability or versatility

If different mathematical models are used for power delivery optimization, then the optimization adapts better to physical configurations, but the software maintainability deteriorates

Engineering Contradiction:

ImproveAdaptability to physical configurationsVSAvoidSoftware maintainability

Core Design Contradiction:

Adaptability or versatilityVSEase of repair

Solution Approach 1:

Segmentation creates modular software components that can be independently maintained. Each mathematical model becomes a separate, well-defined module with specific input/output interfaces, making the software easier to maintain despite the diversity of models used.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250226691A1Method for operating a power delivery network, control device for implementing such a method and power delivery network including such a control device

Publication Date: 2025.07.10 ROLLS ROYCE SOLUTIONS GMBH

AI summary

A method for operating a power delivery network, including: detecting a load demand on the power delivery network; detecting a first power delivery information by a first power delivery device and a second power delivery information by a power delivery group; determining—based on a load demand, the first power delivery information, and the second power delivery information—a first load distribution by way of a nonlinear optimization, the first load distribution including a first partial load for the first power delivery device and a second partial load for the power delivery group; determining, by way of a mixed-integer linear optimization, a second load distribution through which the second partial load is distributed between second power delivery devices of the power delivery group; operating the power delivery network with the first load distribution; and operating the power delivery group with the second load distribution.