Central Plant Control Modeling via Bidirectional Cycle Detection
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Solution Overview
Problem
Existing methods for formulating mathematical models to optimize the operation of central plants are manual and time-consuming, making it challenging to efficiently allocate energy loads across assets, especially in the presence of real-time pricing from utilities.
Innovation Solution
An automated method that receives an input model describing the physical layout of a central plant, creates a net list to identify interconnected systems, discovers cycles, and generates groups of equipment to formulate an optimization problem that minimizes operational costs, including revenue from incentive programs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual methods are used to formulate mathematical models for optimization, then the models can be created with detailed consideration of system constraints, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system automatically formulates optimization models by having the software itself parse plant diagrams, identify equipment connections, and generate mathematical formulations without requiring manual intervention. The asset allocator autonomously creates the optimization problem structure, constraints, and objective functions based on the input plant configuration data.
Solution Approach 2:
The patent replaces the manual mechanical process of model formulation with an automated computational system. Instead of engineers manually creating mathematical models, the system uses software algorithms to automatically generate optimization models from plant diagrams, substituting human cognitive and manual work with automated information processing.
2Productivity
If automated methods are used to formulate optimization models, then the process becomes efficient and rapid, but the complexity of the system increases
Solution Approach 1:
The patent introduces an intermediary plant diagram as a standardized input format that bridges the gap between complex plant configurations and the automated optimization model formulation. The diagram serves as a mediator that captures system topology and constraints in a structured way, allowing the asset allocator to automatically parse and translate it into mathematical models without requiring complex interpretation logic.
3Measurement precision
If detailed plant layouts are manually analyzed to create optimization models, then accurate representation of system connections is achieved, but the process becomes cumbersome and error-prone
Solution Approach 1:
The system creates a digital copy or representation of the plant layout through the plant diagram input. Instead of manually analyzing physical plant configurations, the user provides a diagrammatic copy that captures the essential topology and connections, which the asset allocator then automatically translates into optimization models, eliminating manual analysis errors.
Data Source
AI summary
A control system operates equipment to consume, produce, or store one or more resources. The control system obtains modeling input describing a physical layout of the equipment. The modeling input may indicate a bidirectional connection between the equipment or a bidirectional port of the equipment. The control system determines one or more cycles formed by the equipment based on the modeling input. A cycle may include a path of directed connections between the equipment that forms a closed loop. The control system formulates a control problem using the one or more cycles formed by the equipment and operates the equipment according to the control problem.