Low Temperature Thermal Grid Control Using Dynamic Algorithm Selection
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Solution Overview
Problem
Existing low temperature thermal grids face challenges in efficiently managing temperature variations and balancing heating and cooling demands, leading to inefficiencies in energy use and performance.
Innovation Solution
A method for controlling thermal grids by dynamically selecting control algorithms based on grid demand balance indicators, adjusting temperature boundaries, and implementing merit order control to optimize the use of energy sources, including passive and active energy sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single control algorithm is used for the thermal grid, then the control system is simple, but it cannot efficiently handle varying temperature regions and demand conditions
Solution Approach 1:
The control system dynamically switches between different control algorithms (balanced and unbalanced) based on the current temperature region and grid demand balance indicator. This dynamic adaptation allows the system to optimize performance for different operating conditions while maintaining overall system simplicity through automated algorithm selection.
Solution Approach 2:
The system changes the control algorithm parameter based on the determined temperature region and grid demand balance. By monitoring temperature thresholds and demand indicators, the system selects appropriate control algorithms to handle balanced and unbalanced conditions optimally.
2Stability of the object's composition
If temperature boundaries are fixed, then the control system is stable, but it cannot optimize energy management under varying demand conditions
Solution Approach 1:
Temperature boundaries are dynamically adjusted based on the determined temperature region and grid demand balance indicator. The system transitions between fixed boundary modes (stable operation) and adaptive boundary modes (optimized energy management) to balance stability and efficiency requirements.
3Device complexity
If the thermal grid operates without dynamic algorithm selection, then the system structure is simple, but energy losses increase due to suboptimal control
Solution Approach 1:
The system uses feedback from temperature sensors and grid demand balance indicators to determine the current operating region. Based on this feedback, the appropriate control algorithm is selected and applied, creating a closed-loop control system that minimizes energy losses through adaptive optimization.
Solution Approach 2:
The control system automatically selects and applies the appropriate control algorithm based on current conditions without requiring manual intervention. This self-service capability ensures optimal energy management while maintaining system simplicity through automated decision-making.
Data Source
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AI summary
A method for a thermal grid (100) is provided. The thermal grid (100) comprises a warm pipe (10) and a cold pipe (20), and the method comprises: determining a grid demand balance indicator value (5), associating a current temperature region for the warm pipe (10) and/or the cold pipe (20) of the thermal grid (100) as a balanced temperature region (115) or as an unbalanced temperature region (110, 120) based on the grid demand balance indicator value (5), selecting a balanced control algorithm or an unbalanced control algorithm for the thermal grid based on the current temperature region, and controlling the thermal grid by the selected control algorithm.