Heating system with optimizing function for operating parameters
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Solution Overview
Problem
Existing heating systems suffer from inefficient operation due to improper commissioning, leading to temperature oscillations and inadequate energy supply to heat consuming devices, with manual parameter tuning being time-consuming and cumbersome.
Innovation Solution
A method utilizing a parametrized model, or digital twin, of the heating system to simulate and optimize controller parameters, ensuring steady-state operation by monitoring secondary side supply temperature and adjusting settings to minimize oscillations and achieve optimal energy delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual parameter tuning is performed to optimize controller operation, then control accuracy and system stability are improved, but time consumption and operational disruption increase
Solution Approach 1:
The system performs preliminary simulation and optimization of controller parameters using a digital twin model before applying changes to the actual heating system. This allows parameter tuning to be prepared in advance without disrupting real system operation, resolving the contradiction between achieving optimal control and avoiding operational disruption.
Solution Approach 2:
A digital twin (parametrized model) of the heating system is created to replicate system behavior. This copy allows for virtual testing and parameter optimization without affecting the physical system, enabling thorough tuning without time loss or operational disruption in the real system.
2Stability of the object's composition
If manual parameter tuning is performed to eliminate oscillations, then system stability is improved, but operational complexity and time consumption increase
Solution Approach 1:
The system automatically detects temperature oscillations and initiates simulation-based parameter optimization without requiring manual intervention. The digital twin autonomously performs parameter tuning to eliminate oscillations, reducing both operational complexity and time consumption while maintaining temperature stability.
Solution Approach 2:
The system continuously monitors temperature parameters and provides feedback on oscillation detection. This feedback triggers automatic simulation and parameter adjustment cycles, creating a closed-loop system that maintains temperature stability without complex manual tuning procedures.
3Productivity
If comprehensive parameter optimization is performed to ensure optimal energy delivery, then system efficiency is improved, but computational requirements and system complexity increase
Solution Approach 1:
A parametrized model (digital twin) of the heat exchanging unit is created to replicate system behavior. This virtual copy allows for comprehensive parameter optimization and simulation without increasing the complexity of the physical control system, enabling efficient energy delivery through virtual testing and optimization.
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
Enables efficient and reliable control of heating systems by automatically tuning controller parameters without disrupting operation, reducing oscillations and ensuring consistent energy supply to heat consuming devices.
Implementation Method 1
In the heat exchanging unit, heat exchange takes place between a primary side fluid and a secondary side fluid
Implementation Method 2
heat exchange takes place in the heat exchanging unit between a primary side fluid and a secondary side fluid
Implementation Method 3
heat exchange takes place in the heat exchanging unit between a primary side fluid and a secondary side fluid
Data Source
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AI summary
A method for controlling a heating system (1) consists in : - determining whether or not oscillations are occurring in a secondary side supply temperature, T22, - In the case that oscillations are occurring in the secondary side supply temperature, T22, a simulation procedure is initiated, in which a parametrized model (210) of at least the heat exchanging unit (2) is provided (120), operational data is measured in the heating system (1) and provided to the parametrized model (210); an operating point where the heat exchanging unit (2) operates at steady state is estimated, by means of the parametrized model (210). - based on the provided measured operational data, at least one operating parameter for the controller which is defined by the estimated operating point is provided to the controller (5) and the heating system (1) is operated based on the provided at least one operating parameter.