Method and device for internet-supported optimization of the parameters of heating control
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Solution Overview
Problem
HVAC systems often operate with non-optimal control parameters, leading to inefficient energy use and potential undersupply of heating or cooling, requiring expert knowledge for adjustment and rarely being optimized beyond initial installation or when thermal discomfort occurs.
Innovation Solution
A method and system for internet-based optimization of HVAC system control parameters, using sensors to record relevant system states and transmit data to a central server for processing, which calculates and updates optimized parameters for automatic or user-driven adjustments, ensuring efficient and energy-saving operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If control parameters are manually adjusted by users, then control quality can be increased, but this requires expert knowledge and increases operational complexity
Solution Approach 1:
The system performs self-optimization of control parameters by automatically recording operational data, analyzing performance, and adjusting parameters without requiring expert intervention. The HVAC system serves itself by implementing adaptive control that continuously improves its own performance based on recorded data and analysis.
Solution Approach 2:
The system implements continuous feedback loops where operational data is recorded, analyzed, and used to adjust control parameters. The feedback mechanism compares actual performance with optimal performance and automatically modifies parameters to close the gap, enabling continuous improvement without expert involvement.
2Ease of operation
If control parameters are automatically adjusted by identification and adaptation processes, then heating engineers and customers are freed from optimization tasks, but the system complexity increases
Solution Approach 1:
The system introduces an intermediary optimization module that acts as a bridge between the control system and the user. This intermediary automatically handles the complex parameter optimization tasks, translating operational data into optimized control parameters without requiring users to understand the underlying complexity.
Solution Approach 2:
The patent replaces manual mechanical adjustment of control parameters with automated electronic identification and adaptation processes. The system uses electronic data recording, analysis, and automatic parameter adjustment to substitute the manual optimization process, reducing operational complexity while managing system complexity through automation.
3Ease of operation
If heating systems are rarely adjusted after installation, then operational simplicity is maintained, but energy consumption increases beyond necessary levels
Solution Approach 1:
The system implements continuous optimization of control parameters through automated data recording and analysis. Instead of rare manual adjustments, the system continuously monitors operational data, analyzes performance trends, and adjusts parameters to maintain optimal energy efficiency throughout the system's operation.
Solution Approach 2:
The system transitions from static control parameters set at installation to dynamic parameters that automatically adapt to changing operational conditions. The automated optimization process enables the heating system to dynamically adjust its control parameters based on recorded data, maintaining energy efficiency without requiring manual intervention.
Data Source
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AI summary
The present invention relates to a method for determining a set of optimized regulation parameters (Θ k ) for a controller (3) or a control system for an HVAC (heating, ventilation, air-conditioning and cooling) system (2). In a first method step, an exterior temperature (T A ), an actual room temperature (T R ) of a room (9), a supply temperature (T VL ), a specified target room temperature (T R,W ) and a specified target supply temperature (T VL,W ) are detected. A data packet is generated from the measurement values detected (T A , T R , T R,W , T VL , T VL,W ) and a time (t k ) of detection, which data packet (D k ) is transmitted over an Internet connection to a server (8) where the data packet (D k ) is stored on a storage medium (6, 7) connected to the server (8). In the next method step, a set of optimized control parameters (Θ k ) is calculated using the measurement values (T A , T R , T R,W , T VL , T VL,W ) of the transmitted and stored data packet (D k ) and using measured values (T A , T R , T R,W , T VL , T VL,W ) of a plurality of further data packets (D 0...k-1) generated at earlier times (t 0...k-1) of a specified period (Δt) and/or at least one of a plurality of previously determined sets of optimized control parameters (Θ k -1) by carrying out a calculation algorithm on the server (8). In the subsequent method, step the calculated set of optimized control parameters (Θ k ) is stored on the storage medium (6, 7) connected to the server (8) and is transmitted via the Internet connection to the controller (3) or the control system of the HVAC system (2) or to a user (B) of the HVAC system (2).