Air conditioning system, air conditioning apparatus, and control method
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Solution Overview
Problem
In air conditioning systems, frequent switching between thermo-ON and thermo-OFF states in indoor units leads to repeated stopping and restarting of the compressor, resulting in increased power consumption, especially in air-conditioned spaces with small loads.
Innovation Solution
The air conditioning system incorporates a server device with predicting units to forecast room temperature and thermo-ON/OFF switching times for indoor units, allowing the control device to manage compressor operation based on these predictions, thereby reducing compressor stoppages and restarts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the compressor is stopped when all indoor units are in thermo-OFF state, then power consumption is reduced, but frequent restarting increases power consumption
Solution Approach 1:
The system performs preliminary actions by predicting future thermo-ON/OFF switching times of indoor units before they actually occur. The server device uses machine learning models to forecast when indoor units will switch states, allowing the control device to proactively adjust compressor operation timing to avoid frequent stoppages and restarts, thereby reducing power consumption while maintaining operational stability
Solution Approach 2:
The system implements feedback mechanisms where the server device continuously receives actual operation data from indoor units, updates prediction models based on deviations between predicted and actual switching times, and refines future predictions. This closed-loop feedback ensures the system adapts to changing conditions and optimizes compressor control to minimize frequent restarts
2Loss of energy
If the compressor runs at low speed to avoid stopping, then restarting frequency is reduced, but room temperature may deviate from set temperature
Solution Approach 1:
The system predicts future thermo-ON/OFF switching times of indoor units and proactively schedules compressor operation to coincide with these predicted events. By advancing or delaying compressor start/stop timing based on predictions, the system maintains adequate cooling/heating capacity without requiring continuous low-speed operation, thus preserving temperature control accuracy while reducing power consumption
Solution Approach 2:
The system dynamically adjusts compressor operation timing and speed based on real-time conditions and predicted future states. Rather than maintaining a fixed low speed, the compressor operates at variable speeds and timings optimized for each predicted thermo-ON/OFF event, ensuring adequate temperature control while minimizing energy consumption
3Productivity
If the compressor stops and restarts frequently to match indoor unit thermo-ON/OFF switching, then energy efficiency is maintained, but power consumption increases due to frequent restarts
Solution Approach 1:
The system performs preliminary prediction of indoor unit thermo-ON/OFF switching times using machine learning models. By knowing future switching events in advance, the control device can optimize compressor operation to minimize the number of stoppages and restarts, thereby reducing the energy penalty associated with frequent motor startup while still maintaining efficient air conditioning operation during active periods
Solution Approach 2:
The system strives to maintain continuous compressor operation by predicting and overlapping thermo-ON periods of multiple indoor units. When predictions indicate that indoor unit thermo-ON events will occur in sequence rather than simultaneously, the system adjusts timing to extend continuous operation, eliminating idle periods and avoiding the energy waste of repeated restarts
Data Source
AI summary
An air conditioning system includes an outdoor unit, multiple indoor units, a control device and a server device. The server device includes a first predicting unit that predicts room temperature of an air-conditioned space, by using a plurality of operation state amounts relating to air conditioning operation; and a second predicting unit that predicts a point of time when each indoor unit out of the indoor units is switched to thermo-ON and a point of time when it is switched to thermo-OFF, by using the room temperature predicted and set temperature that is a target temperature of the air conditioning operation. The control device includes a control unit that controls driving of the compressor according to the point of time when each of the indoor unit is switched to the thermo-ON or the thermo-OFF, by using a prediction result of the second predicting unit.