Air-Conditioning Demand Control With Grouped Shut-Off Scheduling
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Solution Overview
Problem
Existing air-conditioning control methods using intermittent shut-off operations struggle to balance power reduction with maintaining a comfortable indoor environment, especially when external and internal conditions change constantly, leading to potential comfort deterioration.
Innovation Solution
A demand control device that groups indoor units, estimates reducible power based on low power operations, predicts power consumption, and calculates targeted power reductions to distribute evenly among groups, ensuring air-conditioning control without exceeding target demand power while minimizing comfort loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If intermittent shut-off operation is performed to reduce power consumption, then power consumption amount is reduced, but indoor environmental comfort deteriorates
Solution Approach 1:
The patent divides indoor units into multiple groups and performs intermittent shut-off operations on a per-group basis rather than shutting off all units simultaneously. This segmentation allows different groups to operate at different times, ensuring that at least some units continue to provide cooling while others are shut off to reduce overall power consumption, thus balancing energy reduction with comfort maintenance.
Solution Approach 2:
The patent implements periodic intermittent shut-off operations where groups of indoor units are cyclically shut off and restarted. By calculating appropriate shut-off periods and distributing operations across multiple groups over time, the system reduces average power consumption while ensuring that cooling is periodically restored to maintain acceptable indoor environmental comfort.
2Device complexity
If constant is used for calculation expression of power amount to be reduced, then calculation is simplified, but prediction accuracy deteriorates when external conditions change
Solution Approach 1:
The patent replaces static constant values in power consumption calculations with dynamic parameters that adapt to changing external conditions. Specifically, it uses current outdoor temperature, humidity, and other environmental factors that are updated in real-time, allowing the power consumption prediction and shut-off calculation to automatically adjust when weather conditions change, thereby maintaining high prediction accuracy without excessive calculation complexity.
3Device complexity
If solar radiation amount measured N hours before demand time limit is used, then calculation is simplified, but prediction accuracy deteriorates when weather conditions change constantly
Solution Approach 1:
The patent performs preliminary calculations of power consumption and shut-off timing at the start of each demand time limit period rather than relying on outdated historical data. By calculating the required power reduction and shut-off schedule in advance based on current weather conditions and predicted load, the system ensures accurate predictions even when weather changes constantly, while keeping data processing complexity manageable through efficient algorithms.
4Object-affected harmful factors
If indoor temperature setting is changed according to number of persons, then comfort is optimized, but control complexity increases
Solution Approach 1:
The patent implements automatic detection of occupancy conditions and automated adjustment of temperature settings and shut-off schedules without requiring manual intervention. The system self-adjusts by detecting the number of persons in each room and automatically optimizing temperature settings and group shut-off timing, thereby maintaining high comfort levels while avoiding the complexity of manual control configurations.
Data Source
AI summary
There is provided air-conditioning control in a low power operation so as not to exceed a target demand power amount in a predetermined measurement period while preventing deterioration of comfortableness of a living space. There include a reducible-power-amount estimation unit configured to calculate, for each group, a reducible power amount by making indoor units perform, for each group, a shut-off operation for a minimum shut-off time in the first half of a demand time limit, and a reduced-power-amount determination unit configured to distribute, when a power consumption amount predicted by a power consumption amount prediction unit exceeds a target demand power amount after the first half of the demand time limit passes, the exceeding power amount to each zone, evenly distribute, in each zone, the distributed power amount to each group, and calculate, based on the reducible power amount of each group, a shut-off time of each group when each group performs the shut-off operation to reduce the distributed power amount.


