Heating System Load Flow Model for Parameter Uncertainty Control
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Solution Overview
Problem
The combined heat and power system requires high control precision for the heating system, but conventional heating systems fail to accurately account for parameter uncertainties such as pipeline dimensions and heat dissipation coefficients, which change over time, leading to potential safety risks and operational inefficiencies.
Innovation Solution
A method is developed to establish a load flow model for the heating system that considers the uncertainty of heat dissipation coefficients by setting them within a preset interval, using algorithms like trust region reflection or sequential quadratic programming to calculate upper and lower limits of inlet water temperatures, and controlling the system based on these limits to ensure safe and accurate operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional heating system control methods are used, then the system is simple to operate, but the control precision is insufficient for combined heat and power systems
Solution Approach 1:
The patent applies preliminary action by establishing a load flow model before control operations to calculate upper and lower limits of inlet water temperatures. This pre-calculation of temperature boundaries enables high-precision control without requiring complex real-time adjustments, as the control system operates within pre-determined safe boundaries.
Solution Approach 2:
The patent introduces an intermediary load flow model that acts as a mediator between system parameters and control decisions. This model calculates temperature limits based on pipeline parameters and heat dissipation coefficients, providing a structured framework that achieves high control precision while maintaining manageable system complexity.
2Reliability
If manufacturer-given pipeline parameters are used, then the control system is simple, but parameter uncertainties lead to inaccurate control
Solution Approach 1:
The patent applies parameter changes by transforming fixed manufacturer-given parameters into dynamic intervals. Instead of using single values for pipeline length, inner diameter, roughness, and heat dissipation coefficients, the system treats these as ranges that account for manufacturing tolerances, installation variations, and aging effects, thereby improving control accuracy without requiring complex real-time measurement systems.
Solution Approach 2:
The patent performs preliminary analysis of parameter uncertainties by establishing the load flow model with interval parameters before operation. This pre-characterization of parameter ranges allows the system to account for uncertainties without requiring complex ongoing measurements, as the model inherently incorporates these variations in its temperature limit calculations.
3Reliability
If high control precision is implemented, then safety is improved, but the control system becomes more complex
Solution Approach 1:
The patent ensures safety through preliminary action by calculating upper and lower temperature limits before control operations. These pre-determined boundaries guarantee safe operation by preventing temperatures from exceeding acceptable ranges, achieving high safety standards without requiring complex real-time monitoring and adjustment mechanisms.
Solution Approach 2:
The patent introduces the load flow model as an intermediary that systematically handles the complexity of high-precision safety control. This model translates complex thermal-hydraulic relationships into manageable temperature limits, allowing the control system to maintain high safety standards while operating with a relatively simple control architecture that merely needs to enforce these pre-calculated boundaries.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides more accurate and reliable load flow solutions, enhancing the safety and control of the heating system by accounting for parameter uncertainties, thus improving the overall performance and safety of the integrated energy system.
Implementation Method 1
The combined heat and power system includes an electricity system and a heating system coupled with each other
Implementation Method 2
load flow model of the heating system, in which the heating system includes pipelines and nodes; the nodes include loads and heating sources
Data Source
AI summary
The disclosure provides a method, an apparatus, and a storage medium for controlling a heating system in a combined heat and power system. The method includes: establishing a load flow model of the heating system, in which the heating system includes pipelines and nodes; the nodes include loads and heating sources; the load flow model includes an objective function and constraints; the objective function for maximizing and minimizing an inlet water temperature of each load or each source; solving the load flow model to obtain an upper limit and a lower limit of the inlet water temperature of each load or each source; and controlling the inlet water temperature of each load or each source based on the upper limit and the lower limit of the inlet water temperature of each load or each source.