Networked Air Conditioning Benchmarking for Energy-Saving Control
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Solution Overview
Problem
Existing air conditioning systems lack the ability to determine and actively adopt the most energy-efficient operation patterns, leading to suboptimal energy saving opportunities.
Innovation Solution
An energy saving support apparatus connected to multiple air conditioning systems via a network, which receives data on installation environments and power consumption, groups systems by similarity, selects the most energy-efficient systems, and transmits performance benchmarks to others in the same group, providing information for energy savings and detecting potential abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If air conditioning systems operate independently with stored operation patterns, then each system maintains operational autonomy, but energy saving opportunities are lost due to inability to share best practices
Solution Approach 1:
The energy saving support apparatus collects operation data from multiple air conditioning systems, analyzes energy consumption patterns, and feeds back optimal operation patterns to systems that need improvement. This closed-loop feedback mechanism enables continuous energy optimization across the network by sharing proven energy-saving experiences from high-performing systems.
Solution Approach 2:
The support apparatus serves multiple functions: it acts as a data collection center, analysis engine, and distribution hub for energy-saving information. By creating a universal platform that handles all these functions, the system enables energy optimization across diverse air conditioning installations without requiring individual systems to develop their own optimization capabilities.
2Ease of operation
If operation patterns are stored and reused, then operational simplicity is maintained, but adaptability to find more efficient patterns is reduced
Solution Approach 1:
Air conditioning systems automatically receive and apply optimized operation patterns from the support apparatus without requiring manual intervention. The systems self-adjust their operation based on received recommendations, maintaining ease of operation while adapting to more efficient patterns through automated updates.
Solution Approach 2:
The support apparatus pre-analyzes operation data from multiple systems to identify optimal patterns before distributing them to individual systems. This preliminary analysis ensures that when patterns are distributed, they are already optimized and ready for immediate implementation, combining analytical adaptability with operational simplicity.
3Loss of energy
If each system determines its own operation patterns independently, then system autonomy is preserved, but energy efficiency is suboptimal due to lack of comparative analysis
Solution Approach 1:
The energy analysis and optimization function is extracted from individual air conditioning systems and centralized in the support apparatus. This separation allows individual systems to remain simple while the centralized system handles the complex task of comparative analysis and optimization pattern generation across the entire network.
Solution Approach 2:
The energy saving support apparatus acts as an intermediary between multiple air conditioning systems, collecting data from all systems, performing comparative analysis, and distributing optimized patterns. This intermediary role enables energy efficiency improvements without requiring direct complex interactions between individual systems.
Data Source
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AI summary
Information contributing to energy saving is provided to an air conditioning system. There is provided an energy saving support apparatus connected to a plurality of air conditioning systems via a network, and includes a receiving section (81) that receives data on an installation environment of each of the air conditioning systems, input data and an intermediate value in control calculation, and power consumption, a group creation section (82) that groups the air conditioning systems, which are approximate to one another in installation environment, using the data on the installation environment received by the receiving section (81), a selection section (83) that selects the air conditioning system having the lowest power consumption or having the highest coefficient of performance among the air conditioning systems belonging to the same group, and a transmission section (84) that transmits an intermediate value of the air conditioning system selected by the selection section (83) to the other air conditioning systems belonging to the same group.