Smart window control device, smart window control method, and smart window control program
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Solution Overview
Problem
The existing smart window control systems experience a significant time lag between adjusting transmittance to regulate sunlight and heat, and the actual change in building temperature, which affects the load on the air conditioning system.
Innovation Solution
The smart window control device uses a temperature transition prediction model based on outdoor temperature, solar irradiance, and past transmittance data to predict and adjust transmittance patterns, minimizing the time lag and optimizing temperature control during prediction and normal modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If transmittance control is applied to adjust sunlight and heat entering the building, then the temperature control effect is improved, but a significant time lag occurs between control action and actual temperature change
Solution Approach 1:
The system performs preliminary actions by predicting future temperature trends and adjusting transmittance in advance before the temperature deviation occurs. The prediction unit forecasts temperature changes based on historical data and environmental factors, allowing the control unit to proactively adjust smart window transmittance to prevent temperature deviations rather than reacting after they occur, thereby reducing the effective time lag.
Solution Approach 2:
The system implements feedback mechanisms where the actual temperature measurements are continuously compared with predicted temperature values. The prediction unit uses this feedback to refine its models and improve future predictions. The control unit adjusts transmittance based on the difference between actual and predicted temperatures, creating a closed-loop control system that continuously optimizes performance and reduces time lag through adaptive adjustment.
2Loss of energy
If transmittance control is adjusted to reduce load on air conditioning system, then energy efficiency is improved, but the control precision is reduced due to time lag
Solution Approach 1:
By predicting temperature trends in advance and adjusting transmittance proactively, the system maintains precise temperature control without waiting for temperature deviations to occur. This preliminary action allows the air conditioning system to operate at reduced capacity while still achieving the desired temperature precision, thereby reducing energy consumption without sacrificing control accuracy.
Solution Approach 2:
The continuous feedback loop compares actual temperature with predicted temperature and adjusts transmittance accordingly. This feedback mechanism ensures that even with reduced air conditioning load, the system maintains precise temperature control by making real-time adjustments to smart window transmittance based on the temperature deviation between actual and predicted values.
3Device complexity
If conventional smart window control is used without prediction, then device complexity is reduced, but the overall system effectiveness is worsened due to inability to account for time lag
Solution Approach 1:
The system introduces a prediction unit as an intermediary component that bridges the gap between simple transmittance control and effective temperature management. This intermediary uses historical temperature data and environmental parameters to forecast future temperature trends, enabling the control unit to make informed decisions that account for time lag. The added complexity of the prediction unit is justified by the significant improvement in temperature control effectiveness and reliability.
Data Source
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AI summary
The load on an air conditioning system is reduced. A smart window control device controls transmittance of a smart window provided as a window of a space where a temperature is controlled by an air conditioning system in accordance with a set temperature. The smart window control device includes an obtaining unit configured to obtain a predicted value of external environment information about outside of the space in an interval between first time and second time, the second time being when a predetermined time period has elapsed from the first time, a calculating unit configured to calculate transition of the temperature of the space in the interval based on the predicted value of the external environment information in the interval, and a transmittance control unit configured to control the transmittance of the smart window so that the temperature of the space in the interval transitions based on the calculated transition of the temperature.