Power Transfer Regulation Using Weighted Supply Optimization
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Solution Overview
Problem
In decentralized power supply systems, there is a need for efficient regulation of electrical power transfer between geographically distributed power supply units and consumption units to ensure stable operation, balancing supply and demand in real-time, while also considering preferences for renewable energy sources and operator preferences.
Innovation Solution
A method and device for regulating power transfer by providing data sets on minimum and maximum power supply, power requirements, and weightings of power supply units and consumption units, using a target function for optimization that includes these parameters to optimize power distribution, prioritize renewable energy sources, and account for operator preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If power transfer is regulated based only on supply and demand using heuristic methods, then the regulation can be implemented simply, but the optimization of power distribution considering renewable energy preferences and operator preferences cannot be achieved
Solution Approach 1:
The patent transforms the regulation approach by changing the parameters from simple supply-demand balancing to a comprehensive optimization function that includes multiple parameters: supply limits, demand requirements, renewable energy weights, operator preferences, and cost factors. This allows the system to achieve both simplicity through automated calculation and high optimization efficiency by considering multiple criteria simultaneously.
Solution Approach 2:
The patent replaces heuristic regulation methods with a mathematical optimization approach. Instead of using rule-based or experience-driven regulation, the system employs an objective function with defined parameters and constraints that can be solved algorithmically, substituting mechanical/heuristic processes with computational optimization.
2Productivity
If an optimization method with target function is used to consider multiple parameters including renewable energy preferences, then the power distribution optimization is improved, but the complexity of the regulation system increases
Solution Approach 1:
The patent implements a self-service optimization system where the regulating device automatically calculates the optimal power distribution by itself using the defined objective function and parameters. The system does not require complex manual intervention or multiple separate control devices, as the optimization is performed autonomously through mathematical computation, thereby reducing operational complexity despite the comprehensive parameter consideration.
Solution Approach 2:
The patent creates a universal regulation framework that can handle multiple objectives (renewable energy promotion, operator preferences, cost optimization, supply-demand balancing) within a single optimization function. This multi-functional approach consolidates what would otherwise require multiple separate regulation systems into one unified device, reducing overall system complexity.
3Productivity
If weightings of power supply units are introduced to prioritize renewable energy sources, then the promotion of renewable energy is improved, but the difficulty of detecting and measuring preferences and requirements increases
Solution Approach 1:
The patent applies preliminary action by requiring all preferences, requirements, and weightings to be input into the system in advance. The operator specifies renewable energy weights, preference factors, and constraints before the optimization process begins. This pre-input approach simplifies the detection and measurement process, as all parameters are captured upfront rather than requiring continuous real-time detection of dynamic preferences.
Data Source
AI summary
Various embodiments include a method for regulating an electrical power transfer between two power supply units and a power consumption unit comprising: providing a first data set with information regarding a minimum and maximum electrical power supply rate for each of the two power supply units; providing a second data set with information regarding a power requirement of the power consumption unit and a weighting of each of the power supply units; providing a target function for an optimization method, wherein the target function includes the first data set, the second data set, and the weightings of the power supply units as parameters; and regulating the power transfer by means of an extremalization of the target function.