Air-conditioning operation condition generation apparatus, air-conditioning operation condition generation method and air-conditioning system
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Solution Overview
Problem
In coordinated air-conditioning systems, achieving a uniform desired temperature across a facility is challenging due to variations in thermal properties and heat loads, as well as individual perceptions of comfort, making it difficult to determine optimal control settings for multiple air conditioners without considering their interactions.
Innovation Solution
An air-conditioning operation condition generation apparatus that generates trial conditions for multiple air conditioners, evaluates their performance, and adjusts settings based on feedback to achieve a targeted state in a target space without relying on simulation, by using a trial-and-error method to determine optimal operation conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a targeted temperature is set for the entire facility, then the overall air-conditioning control is simplified, but the targeted temperature may not be reached at some parts due to thermal property and heat load variations
Solution Approach 1:
The facility is divided into multiple measurement points or zones, and temperature control is optimized for each zone independently. The system determines setting values for each air conditioner based on local temperature measurements and thermal properties of specific areas, rather than applying a uniform temperature target across the entire facility.
Solution Approach 2:
Different air conditioners or control strategies are applied to different areas of the facility based on their specific thermal properties and heat loads. Each area receives customized control parameters determined through trial evaluations that consider local conditions, achieving uniform temperature distribution despite facility-wide variations.
2Manufacturing precision
If fine control is performed to handle local air-conditioning requests, then local temperature requirements can be addressed, but the task becomes complex due to thermal properties, heat loads, and interactions between multiple air conditioners
Solution Approach 1:
The system uses measured temperature values from various locations in the facility to determine optimal setting values for air conditioners. Trial conditions are evaluated based on actual temperature measurements, and control parameters are adjusted iteratively to achieve desired temperature distribution, reducing the complexity of manual fine-tuning.
Solution Approach 2:
The system automatically determines and adjusts control parameters (setting values) for each air conditioner based on trial evaluations. By changing parameters systematically through automated trial-and-error processes rather than manual adjustment, the system handles local control requirements without increasing operational complexity.
3Manufacturing precision
If trial-and-error method is used to determine optimal operation conditions, then precise temperature control can be achieved, but time and computational resources are required for iterative testing and evaluation
Solution Approach 1:
The system performs trial evaluations using predetermined trial conditions that are designed to efficiently determine optimal setting values. By preparing and executing structured trial sequences in advance rather than ad-hoc adjustments, the system reduces the time required for optimization while maintaining precision.
Solution Approach 2:
The system uses measured temperature data and thermal property information to create models or representations of facility behavior. These models allow the system to predict outcomes of different setting combinations without requiring extensive physical trials, reducing the time and computational resources needed for optimization.
Data Source
AI summary
An air-conditioning operation condition generation apparatus as an aspect of the present invention generates trial conditions for multiple air conditioners associated with a target space of air-conditioning control, evaluates a trial performed by coordination of the plurality of air conditioners under the trial conditions, and generates actual operation conditions for the plurality of air conditioners to achieve a targeted state in the target space on the basis of evaluation of the trial.