Computer-implemented method for adjusting at least one parameter with respect to a heating device
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Solution Overview
Problem
Existing methods for setting heat pump parameters are inefficient and unreliable, often leading to suboptimal energy efficiency and user comfort due to manual adjustments without adequate consideration of efficiency or sustainability, and lack of coordination among installers and users.
Innovation Solution
A computer-implemented method for adjusting heat pump parameters using measurement data and optimization techniques to determine optimal settings, including initial and varied parameter values, data acquisition, and statistical or machine learning-based optimization to ensure efficient and reliable operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parameters are set manually by heating installers according to current best practices, then the installation process is simple and quick, but the energy efficiency and sustainability of the heat pump operation are not adequately optimized
Solution Approach 1:
The heat pump system automatically adjusts its own parameters by evaluating measurement data from multiple installations and learning from operational results, eliminating the need for manual parameter setting by installers while optimizing energy efficiency through data-driven decisions
Solution Approach 2:
The system collects measurement data from operational heat pumps, evaluates the results, and uses this feedback to automatically adjust parameters in subsequent installations, creating a continuous improvement loop that enhances energy efficiency without manual intervention
2Ease of operation
If heating installers set parameters conservatively at higher temperatures to avoid customer complaints, then user comfort is ensured, but the heat pump operates less efficiently and consumes more energy
Solution Approach 1:
The system autonomously determines optimal parameter settings by analyzing measurement data that balances user comfort requirements with energy efficiency, removing the conservative bias introduced by manual installer decisions
Solution Approach 2:
The system dynamically adjusts operational parameters based on learned patterns from measurement data, finding the optimal balance between temperature settings for user comfort and energy consumption efficiency
3Device complexity
If manual parameter adjustment is performed without coordination among installers and service companies, then each company can work independently, but the reliability and consistency of parameter settings cannot be guaranteed
Solution Approach 1:
The system provides a universal parameter setting mechanism that works across different installations and companies, ensuring consistent and reliable parameter determination through automated evaluation of measurement data from multiple sources
Solution Approach 2:
By collecting and evaluating measurement data from various installations in a centralized manner, the system ensures reliable parameter settings are achieved through coordinated learning, eliminating the need for direct company-to-company coordination
4Adaptability or versatility
If users change parameters independently without assessing consequences, then user requirements can be dynamically adjusted, but the efficiency and sustainability of heat pump operation deteriorate
Solution Approach 1:
The system automatically monitors and adjusts parameters based on operational data, maintaining adaptability to user needs while preventing efficiency deterioration through continuous evaluation and correction of parameter settings
Data Source
Figure 1

AI summary
The invention relates to a computer-implemented method for setting at least one parameter with respect to a heating device, comprising the steps of: a. setting the heating device with at least one first value of the at least one parameter (S1); b. setting the heating device with at least one second value of the at least one parameter (S2), wherein the at least one second value is determined by varying the at least one first value (S3); c. acquiring measurement data for the respective settings of the at least two settings (S4), wherein the measurement data each comprise at least one measured value and at least one target value; d. determining an optimal value from the plurality of values by means of an optimization approach based on the measurement data (S5); and e. providing the optimal value of the at least one parameter (S6). The invention further relates to a technical system and a corresponding computer program product.