Control device, air conditioner and control method thereof
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Solution Overview
Problem
Existing HVAC systems face inefficiencies in energy consumption when there are no occupants or when the number of occupants is low, as current methods either turn off the system or use setback controls, which can lead to higher energy usage upon restart or inefficient temperature control.
Innovation Solution
A control device and method that utilize a processor to predict indoor temperatures over time using a trained temperature prediction model, generate candidate setting temperatures, create temperature control schedules, predict energy consumption using an energy prediction model, and identify an optimal temperature control schedule to minimize energy usage during power-saving operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the HVAC system is controlled in a setback method at a certain temperature, then the system maintains continuous operation, but energy is not consumed efficiently
Solution Approach 1:
The system dynamically adjusts the temperature setpoint based on the predicted duration of unoccupied periods. For short unoccupied periods, the system maintains continuous operation with minimal adjustments. For longer unoccupied periods, the system implements more aggressive temperature adjustments or shutdowns, optimizing energy efficiency while maintaining reliability.
2Ease of operation
If the HVAC system uses traditional control methods in buildings with no skilled manager, then the system operates without expert knowledge, but control efficiency deteriorates
Solution Approach 1:
The system performs self-service by automatically detecting occupancy status through sensors and algorithms, predicting unoccupied periods, and adjusting temperature settings without requiring skilled manual intervention. This maintains ease of operation while significantly improving control efficiency through intelligent automation.
Solution Approach 2:
The system implements feedback loops where sensors continuously monitor occupancy status, temperature conditions, and energy consumption. This feedback information is used by the control algorithm to continuously optimize temperature adjustments, improving control efficiency without requiring skilled operators.
Data Source
AI summary
A control device, an air conditioner, and a control method thereof are provided. The control device includes a communication interface configured to communicate with an external device, and a processor configured to control the communication interface to receive indoor and outdoor environment information and user control information, and the processor is configured to predict an indoor temperature over time through a temperature prediction model based on the received indoor and outdoor environment information and the user control information, obtain a corresponding candidate setting temperatures, obtain temperature control schedules, predict energy consumptions of the obtained temperature control schedules, respectively, through a trained energy prediction model, identify a temperature control schedule with the smallest predicted energy consumption as an optimal temperature control schedule, and transmit control information over time to an air conditioner during a pre-set power saving operation time based on the identified optimal temperature control schedule.