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Thermal Control Strategy for the Sustainable Use of Large Classrooms Responding to User Demands in a School Building
In order to respond to the needs of education, the importance of various learning activities other than subject courses is gradually increasing in schools. Therefore, classrooms in schools are organized in a variable form depending on the educational situations and demands, and it is necessary to improve their energy efficiency in the operation without compromising indoor thermal quality. This study examines the efficiency of thermal control models that can perform cooling and heating energy supply when using one large classroom composed of two architectural modules. Through an adaptive process, a proposed model determines the efficient heating and cooling air supply according to the room conditions derived from the occupant schedules. The model optimizes the condition of supply air in order to mitigate users’ thermal comfort. Then, the results from this adaptive process are trained by iterative learning using a neural network, and a newly improved model derived from the learning process is tested to achieve both energy use and thermal comfort improvement. As a result, it is confirmed that the proposed learning model shows about 2.78% improvement in energy efficiency and about 72.73% improvement in thermal comfort consistency as compared to the thermostat control. This model can help to efficiently operate school buildings by increasing the usability of various classrooms.
Thermal Control Strategy for the Sustainable Use of Large Classrooms Responding to User Demands in a School Building
In order to respond to the needs of education, the importance of various learning activities other than subject courses is gradually increasing in schools. Therefore, classrooms in schools are organized in a variable form depending on the educational situations and demands, and it is necessary to improve their energy efficiency in the operation without compromising indoor thermal quality. This study examines the efficiency of thermal control models that can perform cooling and heating energy supply when using one large classroom composed of two architectural modules. Through an adaptive process, a proposed model determines the efficient heating and cooling air supply according to the room conditions derived from the occupant schedules. The model optimizes the condition of supply air in order to mitigate users’ thermal comfort. Then, the results from this adaptive process are trained by iterative learning using a neural network, and a newly improved model derived from the learning process is tested to achieve both energy use and thermal comfort improvement. As a result, it is confirmed that the proposed learning model shows about 2.78% improvement in energy efficiency and about 72.73% improvement in thermal comfort consistency as compared to the thermostat control. This model can help to efficiently operate school buildings by increasing the usability of various classrooms.
Thermal Control Strategy for the Sustainable Use of Large Classrooms Responding to User Demands in a School Building
Jonghoon Ahn (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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