Vehicular Power Management via Dual Decomposition
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Solution Overview
Problem
Existing vehicular power management systems face challenges in predicting and optimizing power demand in complex systems with many independent loads, leading to suboptimal configurations and potential overload conditions, as prior methods like load shedding are simplistic and do not fully utilize the capabilities of multiple power sources and loads.
Innovation Solution
A power management control system utilizing a dual decomposition method that treats total energy usage as sub-problems for each unit, solved using a shortest path algorithm and coordinated with a sub-gradient update rule to achieve optimal or near-optimal source and load allocation, balancing operational costs and utilities across the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load shedding is used to avoid overload conditions, then system reliability is improved, but power system efficiency deteriorates due to suboptimal load configuration
Solution Approach 1:
The patent segments the power system into multiple independent sources and loads, each with its own controller. The system controller divides the overall power management problem into sub-problems for each source-load pair, allowing individual optimization while maintaining system-wide reliability through coordinated control.
Solution Approach 2:
The patent changes the control parameter from simple load shedding (binary on/off) to continuous power allocation ratios. By optimizing the power allocation ratio for each source-load pair and using Lagrange multipliers to enforce power balance constraints, the system achieves both reliability and efficiency improvements.
2Productivity
If complex optimization algorithms are used to optimize power allocation, then power system efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent decomposes the complex global optimization problem into independent sub-problems for each source-load pair. Each sub-problem can be solved separately using simple algorithms, and the results are coordinated through the system controller, reducing overall computational complexity while maintaining optimization benefits.
Solution Approach 2:
The system controller acts as an intermediary that coordinates between individual source and load controllers. It receives power allocation requests, applies Lagrange multipliers to enforce power balance, and distributes optimized allocation ratios, simplifying the computational burden on individual components.
3Adaptability or versatility
If distributed control is implemented across multiple units, then system adaptability is improved, but coordination complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the system controller receives power allocation data from individual sources and loads, compares it against system-wide power balance constraints, and adjusts allocation ratios accordingly. This feedback loop enables adaptive coordination without requiring complex centralized control.
Solution Approach 2:
The system controller serves multiple functions: it coordinates power allocation, enforces power balance constraints through Lagrange multipliers, and adapts to changing system conditions. This multi-functional approach simplifies the coordination architecture while maintaining system adaptability.
Data Source
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AI summary
A system to control a power distribution system (102) includes a system controller (110) configured to determine an allocation of power during a first time period for each of a plurality of subsystems. The system also includes a subsystem controller (130) communicatively coupled to the system controller. The subsystem controller is associated with a device (144) and configured to receive power allocation data indicating the allocation of power for the device from the system controller. The subsystem controller is further configured to receive operation request data indicating a request to operate the device and produce a model operation of the device for a second time period based on the power allocation data, the operation request data, and a cost-utility function associated with the device. The subsystem controller is also configured to communicate, to the system controller, projected power demand data associated with the modeled operation of the device during the second time period.