Multi-objective optimization and performance evaluation of an integrated dedicated outdoor air system with sensible cooling unit for passive houses

초록

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. © 2023 Elsevier B.V.

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