Occupancy-Predictive Air Conditioner Control for Energy Saving
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Solution Overview
Problem
Conventional air conditioning systems using Energy Recovery Ventilators (ERV) for carbon dioxide density control in enclosed spaces rely on fixed methods, which are inefficient and fail to adapt to regular occupant schedules, leading to suboptimal energy usage and comfort.
Innovation Solution
An air conditioner system that determines an occupant's expected leaving time based on historical data and adjusts its operation mode and time accordingly, using communication with terminals and wireless access points to minimize energy consumption while maintaining comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed carbon dioxide density control methods are used, then the air conditioner operates based on predetermined thresholds, but energy consumption increases and adaptability to regular occupancy patterns decreases
Solution Approach 1:
The system performs preliminary actions by analyzing historical occupancy data to predict future occupancy patterns before they occur. The controller stores terminal information including stay times and locations, then uses this data to predict when occupants will enter or leave zones, allowing the air conditioner to proactively adjust operation modes rather than reacting to current CO2 levels alone
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring terminal locations and stay patterns, then using this information to adjust air conditioner operation. The controller receives terminal information, analyzes occupancy patterns, and feeds this back into the control decision-making process to optimize energy consumption while maintaining comfort
2Reliability
If the air conditioner operates continuously to maintain comfort, then occupant comfort is guaranteed, but energy consumption increases
Solution Approach 1:
The system applies dynamics by making the air conditioner operation flexible and adaptive rather than static. The controller dynamically adjusts operation modes based on predicted occupancy patterns, allowing the system to transition between different operational states (full operation, partial operation, or standby) according to real-time and predicted occupancy needs
Solution Approach 2:
The system changes operational parameters based on occupancy predictions. The controller modifies operation mode parameters and timing parameters according to predicted occupancy patterns, adjusting when and how the air conditioner operates to balance comfort requirements with energy conservation opportunities
3Use of energy by moving object
If the air conditioner adjusts operation based on predicted occupancy, then energy consumption decreases, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by combining terminal information collection, historical data storage, occupancy pattern analysis, prediction algorithms, and air conditioner control into a single integrated controller. This universal approach allows the same controller to perform multiple functions without requiring separate dedicated systems for each function
Data Source
AI summary
An air conditioner, according to one embodiment of the present invention, comprises: a communication unit for receiving, from a terminal staying in a zone, first information of the terminal, including information on a previous staying time of the terminal in the zone; and a control unit for determining second information of the terminal, which contains an expected leaving time of the terminal, on the basis of the first information of the terminal and determining an operating mode and an operating time of the air conditioner on the basis of the second information of the terminal, and thus energy can be saved while minimizing a decline in the sensation of comfort felt by an occupant.