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• W4386227357 abstract "Appropriate dehumidification systems are essential for passive houses to prevent thermal discomfort under high dehumidification loads. In this study, an integrated air conditioning system (IACS) consisting of a dedicated outdoor air system and sensible cooling unit is developed to manage dehumidification loads in passive houses. Multi-objective optimization of the operating conditions of the IACS is performed considering the energy consumption and thermal comfort of a passive house. A thermal comfort model is constructed using a big-data-driven machine learning method to improve prediction accuracy compared to a conventional model. Additionally, an artificial-neural-network-based metamodel is developed to estimate the performance of the IACS. The optimal operating conditions are determined based on the Pareto solution set obtained from multi-objective optimization. The optimized performance and economic feasibility of the IACS are compared to those of a conventional air conditioning system (CACS). For the IACS in a passive house, the optimal indoor set-point temperature and relative humidity were determined to be 27.01 ℃ and 50.35%, respectively. The energy-saving rates of the IACS were 15.96% and 7.53% in passive and normal houses, respectively, compared to the CACS. The IACS is more economical than the CACS based on its energy-saving effects, particularly in passive houses." @default.
• W4386227357 created "2023-08-29" @default.
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• W4386227357 date "2023-10-01" @default.
• W4386227357 modified "2023-09-29" @default.
• W4386227357 title "Multi-objective optimization and performance evaluation of an integrated dedicated outdoor air system with sensible cooling unit for passive houses" @default.
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• W4386227357 doi "https://doi.org/10.1016/j.enbuild.2023.113494" @default.
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