Method and device for controlling air conditioner, and computer readable storage medium
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Solution Overview
Problem
Central air conditioners face inefficiencies and high power consumption due to untimely adjustments in response to changing environmental parameters and load demands, leading to discomfort and energy wastage.
Innovation Solution
An air conditioner control method and device that acquires a predicted load by determining operation parameters of indoor units, adjusts the operating status of outdoor units based on an efficient outdoor unit combination, and controls valves and water pumps to optimize cooling tower operations, ensuring timely adjustments to match varying load demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual control method is used by management personnel, then operation simplicity is maintained, but adjustment speed and responsiveness to load changes deteriorate
Solution Approach 1:
The system performs self-service by automatically detecting indoor unit startup/shutdown events, predicting load changes, and adjusting outdoor unit combinations without manual intervention. The control system serves itself by making real-time decisions based on operational parameters and predicted load, eliminating the need for manual control while achieving rapid adjustment.
Solution Approach 2:
The system implements feedback by continuously monitoring operational parameters of indoor units, using this feedback to predict load changes, and automatically adjusting outdoor unit configurations. The feedback loop enables the system to respond dynamically to changing conditions, achieving both automation and rapid adjustment speed.
2Device complexity
If outdoor units are not及时调整 according to load demand, then system complexity is reduced, but energy consumption increases
Solution Approach 1:
The system performs preliminary action by predicting future load changes based on current operational parameters before the actual load change occurs. This allows the system to pre-adjust outdoor unit combinations in anticipation of upcoming demand changes, optimizing energy consumption proactively rather than reactively.
Solution Approach 2:
The system applies dynamics by making outdoor unit combinations adjustable and adaptable based on predicted load requirements. Rather than using a fixed configuration, the system dynamically reconfigures which outdoor units are active, matching system capacity to actual demand and avoiding energy waste from over-provisioning.
3Loss of energy
If timely adjustment of outdoor units is implemented based on predicted load, then energy efficiency is improved, but control system complexity increases
Solution Approach 1:
The control system performs self-service by automatically executing the complex task of predicting load and adjusting outdoor unit combinations without requiring external complex control infrastructure. The system uses its own operational data to make intelligent decisions, achieving energy efficiency through automated intelligence rather than complex external control systems.
Solution Approach 2:
The system replaces mechanical/manual control adjustments with automated electronic control and prediction algorithms. Instead of physically adjusting units based on manual intervention or complex mechanical systems, the patent uses computational prediction and electronic control signals to optimize outdoor unit operation, reducing the need for complex physical adjustment mechanisms.
4Reliability
If host adjustment takes more than 1 hour manually, then system reliability is maintained through careful manual operation, but user comfort and energy efficiency deteriorate
Solution Approach 1:
The system uses feedback from real-time monitoring of indoor unit operational parameters to automatically trigger and execute outdoor unit adjustments. This feedback mechanism ensures reliable operation by continuously validating system state and making adjustments only when and when needed, eliminating long manual adjustment times while maintaining operational reliability through automated decision-making.
Solution Approach 2:
The system performs self-service by automatically detecting when adjustments are needed and executing them without human intervention. This eliminates the 1+ hour manual adjustment time while maintaining reliability, as the automated system uses the same operational criteria that would guide a careful manual operator, but executes adjustments immediately and consistently.
Data Source
Figure 1~2
AI summary
A method and device for controlling an air conditioner, and a computer readable storage medium. The method for controlling an air conditioner comprises the following steps: upon detecting a power-on or power-off command corresponding to an internal unit of a central air conditioner, acquiring a current predicted load of the central air conditioner; determining whether the predicted load meets an external unit change condition; and if so, adjusting an operating state of an external unit of the central air conditioner on the basis of the predicted load.