Distribution System Control Policy Adaptation
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Solution Overview
Problem
Distribution systems face challenges in optimizing control policies due to uncertain and time-varying parameters, which affect the efficient processing and allocation of resources, leading to suboptimal performance and increased costs.
Innovation Solution
The method involves determining initial control policies using Continuous Linear Programming (CLP) and dynamically re-optimizing them by monitoring and approximating continuous functions associated with changeable variables, allowing for real-time adjustments to ensure optimal resource processing and allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If control policies are determined using traditional methods, then the system structure is simpler, but the adaptability to changing parameters and real-time optimization is insufficient
Solution Approach 1:
The patent implements dynamic control policies by continuously monitoring system parameters and re-optimizing control strategies in real-time. The system transitions from static to dynamic policy determination, allowing control parameters to adapt automatically to changing conditions while maintaining computational tractability through structured optimization frameworks.
Solution Approach 2:
The patent employs parameter change techniques by adjusting control parameters based on monitored system states. When parameters exceed threshold values or change beyond acceptable ranges, the system modifies control policies accordingly, enabling adaptive response to parameter variations without requiring complete system redesign.
2Adaptability or versatility
If control policies are updated frequently to adapt to changing conditions, then the adaptability improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent implements periodic monitoring and evaluation of control policies at defined intervals or triggered by parameter threshold violations. This periodic action allows the system to update policies at optimal moments rather than continuously, reducing computational burden while maintaining adaptability to significant parameter changes.
Solution Approach 2:
The system incorporates feedback mechanisms where monitored parameter values are fed back into the control optimization process. This feedback loop enables the system to learn from past performance and adjust policies more efficiently, reducing the computational complexity of real-time optimization by leveraging historical data and patterns.
3Measurement precision
If the system monitors all parameters continuously, then the measurement precision and detection capability improve, but the energy consumption and system overhead increase
Solution Approach 1:
The patent applies local quality monitoring by focusing measurement and monitoring resources on specific critical parameters rather than uniformly monitoring all system parameters. This selective monitoring approach maintains measurement precision for key parameters while reducing overall energy consumption by avoiding unnecessary monitoring of less critical components.
Solution Approach 2:
The system performs preliminary identification and classification of parameters based on their importance and impact on system performance. By pre-determining which parameters require continuous monitoring and which can be monitored less frequently, the system optimizes the balance between measurement precision and energy consumption before actual monitoring begins.
Data Source
AI summary
Aspects of the present invention disclose a method for managing the control policies associated with processing of a set of resources by a distribution system. The method includes one or more computer processors determining information associated with a configuration of a distribution system. The method further includes determining information related to a set of resource to process utilizing the distribution system. The method further includes determining respective values for a plurality of parameters related to processing the set of resources utilizing the distribution system. The method further includes selecting an initial set of control policies; The method further includes updating the initial set of control policies. The method further includes instructing the distribution system to process the set of resources utilizing the updated set of control policies.