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Improvement of the Performance Balance between Thermal Comfort and Energy Use for a Building Space in the Mid-Spring Season

School of Architecture and Design Convergence, Hankyong National University, Anseong 17579, Korea
Sustainability 2020, 12(22), 9667; https://doi.org/10.3390/su12229667
Received: 21 October 2020 / Revised: 15 November 2020 / Accepted: 16 November 2020 / Published: 19 November 2020
(This article belongs to the Special Issue Thermal Behavior and Energy Efficiency of Buildings)
In thermal controls in buildings, recent statistical and data-driven approaches to optimize supply air conditions have been examined in association with several types of building spaces and patterns of energy consumption. However, many strategies may have some problems where high-control precision may increase energy use, or low energy use in systems may decrease indoor thermal quality. This study investigates a neural network algorithm with an adaptive model on how to control the supply air conditions reflecting learned data. During the process, the adaptive model complements the signals from the network to independently maintain the comfort level within setting ranges. Although the proposed model effectively optimizes energy consumption and supply air conditions, it achieves quite improved comfort levels about 14% more efficient than comparison models. Consequently, it is confirmed that a network and learning algorithm equipped with an adaptive controller properly responds to users’ comfort levels and system’s energy consumption in a single space. The improved performance in space levels can be significant in places where many spaces are systematically connected, and in places which require a high consistency of indoor thermal comfort. Another advantage of the proposed model is that it properly reduces an increase in energy consumption despite an intensive strategy is utilized to improve thermal comfort. View Full-Text
Keywords: building space; mid-spring season; human comfort; energy use; artificial neural network; adaptive model building space; mid-spring season; human comfort; energy use; artificial neural network; adaptive model
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MDPI and ACS Style

Ahn, J. Improvement of the Performance Balance between Thermal Comfort and Energy Use for a Building Space in the Mid-Spring Season. Sustainability 2020, 12, 9667. https://doi.org/10.3390/su12229667

AMA Style

Ahn J. Improvement of the Performance Balance between Thermal Comfort and Energy Use for a Building Space in the Mid-Spring Season. Sustainability. 2020; 12(22):9667. https://doi.org/10.3390/su12229667

Chicago/Turabian Style

Ahn, Jonghoon. 2020. "Improvement of the Performance Balance between Thermal Comfort and Energy Use for a Building Space in the Mid-Spring Season" Sustainability 12, no. 22: 9667. https://doi.org/10.3390/su12229667

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