Energy Installation Physical Modeling With Constraint Trees
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Solution Overview
Problem
Existing energy installation models are overly complex due to a large number of variables and constraints, leading to reduced accuracy in control set points and increased computational resources, making it difficult to optimize energy installations efficiently.
Innovation Solution
A method to determine a physical model of an energy installation by forming a tree of constraints, allocating levels to components, creating internal and external variables, and determining reduced constraints, which reduces the complexity of the model and computational resources required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the complexity of physical models of energy components is reduced to determine operating set points within reasonable time, then computational efficiency is improved, but the accuracy of generated control set points deteriorates
Solution Approach 1:
The patent segments the energy installation into a hierarchical tree structure with multiple levels. Level 1 contains leaf components (energy sources and loads), while higher levels contain aggregation components. This segmentation allows the model to process only necessary variables and constraints at each level, reducing overall computational complexity while maintaining accuracy through hierarchical aggregation.
Solution Approach 2:
The patent introduces a hierarchical dimension to the traditional flat model structure. By organizing components into multiple levels (Level 1, Level 2, etc.) with aggregation relationships, the model transforms a computationally intensive single-level problem into a multi-level hierarchical problem, reducing the number of variables and constraints that must be processed simultaneously while preserving system accuracy.
2Device complexity
If the number of variables and constraints in the physical model is reduced, then computational resources required are minimized, but the precision of the physical model deteriorates
Solution Approach 1:
The patent extracts and eliminates redundant variables and constraints from the physical model by organizing components into a hierarchical tree structure. At each level, only the necessary variables and constraints for that specific level are retained, while dependencies on variables from other levels are managed through hierarchical relationships. This extraction reduces the total number of variables and constraints while preserving the essential physical relationships.
Solution Approach 2:
The patent implements a dynamic hierarchical structure where the model adapts its complexity based on the operational context. The hierarchical aggregation allows the model to dynamically adjust which variables and constraints are active at each level, maintaining precision for critical relationships while reducing overall model complexity by inactive or less critical variables.
Data Source
AI summary
A method for determining a physical model of an energy installation from a plurality of components linked together according to one or more constraints to form a tree, called tree of constraints, each component including one or more output ports, each output port being associated with a physical quantity of which the value depends on one or more variables internal to the component and/or on one or more variables external to the component, each external variable being communicated to the component through an input port. A second aspect relates to a method for controlling an electrical installation including a first phase of determining a physical model of the installation using the described method; and a second control phase during which each set point is determined as a function of a simulation carried out using the physical model obtained during the phase of determining a physical model of the energy installation.