Thermal load estimating device and air conditioning control system
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Solution Overview
Problem
Conventional thermal load estimating devices for air conditioning systems cannot accurately estimate real-time thermal loads in buildings, as they rely on pre-defined patterns and fail to account for momentary variations.
Innovation Solution
A thermal load estimating device that uses a combination of off-line generated thermal load patterns and real-time power consumption data to estimate thermal loads in units of a room, incorporating factors like occupancy, lighting, and device power consumption, allowing for dynamic control of air conditioning systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-defined thermal load patterns are used for estimation, then the device complexity is reduced and ease of operation is improved, but the measurement precision of real-time thermal load cannot be achieved
Solution Approach 1:
The system performs preliminary actions by pre-calculating thermal load patterns based on building information model data before real-time operation. These pre-computed patterns are stored and ready for rapid retrieval and combination with real-time power consumption data, enabling accurate real-time estimation without complex computational overhead during operation.
Solution Approach 2:
The patent introduces an intermediary approach by combining pre-defined thermal load patterns with real-time power consumption measurements. This intermediary method bridges the gap between simple pattern-based estimation and complex real-time calculation, achieving accurate thermal load estimation through a balanced integration of both approaches.
2Adaptability or versatility
If standard thermal load patterns are prepared in advance, then the ease of manufacture and deployment is improved, but the adaptability to momentary varying thermal load cannot be achieved
Solution Approach 1:
The system implements dynamics by making the thermal load estimation adaptive to real-time conditions. Pre-defined patterns are dynamically combined with current power consumption data to reflect momentary variations in thermal load, allowing the system to adapt to changing conditions while maintaining a structured approach based on building information models.
Solution Approach 2:
The patent applies parameter changes by modifying the estimation approach based on real-time power consumption measurements. The system adjusts the thermal load estimation by incorporating actual power consumption data into the pre-defined patterns, enabling the system to respond to parameter changes in the building's thermal environment.
3Measurement precision
If real-time power consumption data is integrated with thermal load patterns, then the measurement precision of thermal load is improved, but the device complexity increases
Solution Approach 1:
The system applies segmentation by dividing the thermal load estimation process into distinct components: pre-calculated thermal load patterns based on building information models, real-time power consumption measurements, and a combination layer that integrates these elements. This segmentation allows each component to be processed independently and efficiently, reducing overall system complexity.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring real-time power consumption data and using it to adjust the thermal load estimation. The system incorporates feedback loops that compare estimated thermal load with actual power consumption measurements, enabling continuous refinement and improvement of estimation accuracy while maintaining manageable system complexity through structured feedback processing.
Data Source
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AI summary
A thermal load estimating device according to an embodiment receives actual power consumption of various types of devices installed in a room, a thermal load pattern of a time-series maximum thermal load of the room, and power consumption of the various types of devices in the room; estimates a thermal load of the room at appropriate time based on the actual power consumption, the thermal load pattern, and the power consumption; and outputs an estimated thermal-load value as a result of estimation.