Method for adjusting a climate system
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Solution Overview
Problem
Existing heating systems in large buildings face challenges in maintaining optimal fluid flow and temperature distribution due to deviations from modeled behavior caused by changes in system components and external influences, leading to inefficiencies and the need for costly and time-consuming manual adjustments.
Innovation Solution
An iterative simulation method using software to anticipate and adjust radiator flow changes by determining significant Cv-value changes, allowing for precise adjustments while minimizing impact on other parts of the system, using measurements like temperature differences across radiators to determine necessary flow adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If fixed flow regulators with defined Cv-values are installed throughout the system, then flow control precision is improved, but system adaptability deteriorates when components are replaced or external conditions change
Solution Approach 1:
The system measures actual room temperatures and compares them to target temperatures, then uses this feedback to identify which radiators require flow adjustments. This closed-loop feedback mechanism allows the system to adapt to changes in components or external conditions while maintaining precise flow control through the fixed Cv-value regulators.
Solution Approach 2:
The control method performs preliminary identification of affected radiators by simulating flow changes in the mathematical model before implementing actual adjustments. This preliminary action determines which radiators will be significantly impacted by a given Cv-value change, allowing for targeted adjustments that maintain precision while adapting to system changes.
2Measurement precision
If manual adjustments are performed to correct temperature deviations, then local temperature control is improved, but system complexity and adjustment time increase
Solution Approach 1:
The system performs self-diagnosis by automatically measuring room temperatures, comparing them to targets, and identifying which radiators need adjustment. This self-service capability eliminates the need for manual inspection and adjustment by technicians, reducing adjustment time while maintaining precise temperature control through automated Cv-value modifications.
Solution Approach 2:
The system replaces manual mechanical adjustment with automated electronic control. A controller automatically determines the required Cv-value changes based on temperature measurements and model simulations, then implements adjustments electronically, substituting the time-consuming manual mechanical adjustment process with a faster automated system.
3Loss of energy
If the mathematical model is used to determine optimal Cv-values, then system efficiency is improved, but model accuracy deteriorates over time due to component changes and external influences
Solution Approach 1:
The system continuously monitors actual room temperatures and uses this feedback to detect deviations from model predictions. When temperature deviations occur that cannot be explained by normal variations, the system identifies affected radiators and adjusts their Cv-values to compensate for model inaccuracies caused by component changes or external influences, thereby maintaining system efficiency.
Solution Approach 2:
The system transitions from a static mathematical model to a dynamic adaptive model. By continuously measuring temperatures and adjusting Cv-values based on actual performance, the model adapts to changing system conditions and external influences over time, maintaining reliability and efficiency despite component replacements or environmental changes.
4Power
If system temperature is increased to compensate for sub-optimal flow control, then heating performance is improved, but energy consumption increases
Solution Approach 1:
The system measures actual room temperatures and uses this feedback to identify flow deficiencies in specific radiators. By targeting adjustments to only those radiators that are underperforming rather than increasing system temperature universally, the system maintains heating performance while avoiding the energy consumption penalty of heating the entire system to higher temperatures.
Solution Approach 2:
The system applies different Cv-value adjustments to different radiators based on their specific performance needs identified through temperature measurements. This local quality approach ensures that each radiator receives the precise flow it needs to achieve target temperatures, maintaining overall heating performance while minimizing energy consumption by avoiding unnecessary heating in already sufficient areas.
Data Source
Figure 1
Figure 2a~2b
Figure 3
AI summary
A computer implemented method for post installation adjustment of a climate system including determining a desired change of at least one radiator flow, determining a change of at least one Cv-value required to achieve the desired flow change, using a software implemented model of the system to automatically calculate a set of radiator flow changes resulting from the change of at least one Cv-value, identifying a subset of radiator flow changes from the set of radiator flow changes which have a perceivable impact on system performance, and repeating the above steps until the subset is empty. The iteration allows an operator to determine a complete set of Cv adjustments that will provide the desired radiator flow change(s) while (as far as possible) leaving other radiator flows unchanged.