Adaptive Dispatching in Low-Voltage Distribution for Voltage Fluctuations
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Solution Overview
Problem
Existing optimization scheduling methods for flexible interconnected low-voltage power distribution regions suffer from subjective weight coefficient determination, leading to suboptimal solutions and complex models, and fail to adapt to system operation status and voltage fluctuations effectively.
Innovation Solution
A self-adaptive optimization scheduling method that dynamically updates weight coefficients based on system operation status and voltage fluctuations, using a multi-objective optimization model with a second-order cone programming approach and adaptive relaxation gap to ensure system stability and economic performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional single-objective transformation method is used to solve multi-objective optimization, then the problem can be simplified into single-objective problem, but the optimal solution cannot be obtained due to subjective influence of weight parameter selection
Solution Approach 1:
The patent applies dynamics by transforming fixed weight coefficients into dynamic adaptive weight coefficients that automatically adjust based on system operating conditions. The weight coefficients are updated in real-time according to voltage deviations and system states, enabling the optimization model to adapt to changing conditions without subjective intervention, thus resolving the contradiction between model simplicity and solution optimality.
Solution Approach 2:
The patent implements self-service through the construction of an adaptive weight coefficient determination model that automatically determines optimal weights based on system operating conditions. The model uses voltage deviations, system states, and operational requirements to self-adjust weight coefficients without external subjective input, eliminating the need for manual weight parameter selection while maintaining model simplicity.
2Adaptability or versatility
If Pareto theory is used to solve multi-objective problems, then comprehensive solution space can be explored, but the utilization rate of solution space is low and local optimal solutions are easily obtained
Solution Approach 1:
The patent applies feedback by continuously monitoring system operating conditions, voltage deviations, and constraint satisfaction levels, then using this feedback to dynamically adjust weight coefficients. This feedback mechanism guides the optimization process toward globally optimal solutions while maintaining high solution space utilization, avoiding the local optimal trap that plagues traditional Pareto-based methods.
Solution Approach 2:
The patent implements parameter changes by transforming static weight parameters into dynamic parameters that change based on system conditions. The adaptive weight coefficients are continuously updated according to voltage deviations, system states, and operational requirements, enabling the optimization algorithm to efficiently explore the solution space and converge to optimal solutions without getting trapped in local optima.
3Reliability
If game theory is used for multi-objective optimization, then decision-making interactions can be studied, but the model and solution become relatively complex and are restricted by rationality assumptions
Solution Approach 1:
The patent implements self-service by creating an autonomous weight determination model that automatically adjusts optimization weights based on system conditions without requiring complex game-theoretic models or rationality assumptions. The system self-determines optimal weights using voltage deviations, operational states, and constraint information, achieving objective decision-making while maintaining model simplicity.
Solution Approach 2:
The patent applies mechanics substitution by replacing the complex mechanical/game-theoretic decision-making framework with a streamlined adaptive optimization approach. Instead of using elaborate game-theoretic models to study decision interactions, the patent substitutes a direct adaptive weight adjustment mechanism that achieves the same objective decision-making goal with significantly reduced model complexity.
4Ease of manufacture
If fixed weight coefficients are used in multi-objective optimization, then the model is simple to implement, but the solution cannot adapt to system operation status and voltage fluctuations
Solution Approach 1:
The patent applies dynamics by transforming static weight coefficients into dynamic adaptive weight coefficients that automatically adjust based on system operating conditions. The weight coefficients are updated in real-time according to voltage deviations and system states, enabling the optimization model to adapt to changing conditions while maintaining implementation simplicity through an automated determination model.
Solution Approach 2:
The patent implements parameter changes by transforming fixed weight parameters into variable parameters that change based on system conditions. The adaptive weight coefficients are continuously updated according to voltage deviations, system states, and operational requirements, enabling the model to adapt to different operating scenarios without increasing implementation complexity.
Data Source
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AI summary
A self-adaptive optimal dispatching method is applied to the flexible interconnected low-voltage power distribution regions, which includes : firstly, classifying the operating states of the system based on the voltage deviation during the system operation process; secondly, establishing a multi-objective optimization model for the safety, economy and reliability of the system operation; based on different operating states of the system, constructing the weight coefficients of the multi-objective optimization function according to the range of the voltage deviation; finally, designing a second-order cone optimization method with gradually tightening relaxation gaps, which can quickly and accurately obtain the optimal dispatching scheme for the flexible interconnected low-voltage distribution stations.