Multi-objective optimization of a CO2/H2O capture-based ventilation and air conditioning system

Yongting Shen and Hongxing Yang

Applied Energy, 2023, vol. 344, issue C, No S0306261923006694

Abstract: Developing energy-efficient ventilation and air-conditioning (VAC) strategies is pivotal for achieving green buildings’ triple merits of high indoor air quality (IAQ), low CO2 emission, and low energy consumption. While adsorption-based carbon capture technologies show promising potential in improving IAQ and reducing AC energy consumption by directly removing excess CO2/H2O and recirculating post-captured air in buildings, current studies lack in-depth investigation into simultaneously maximizing CO2 removal capacity and minimizing AC energy consumption. This trade-off, hindering the broad application of this technology, is rendered by the intricate interplay between indoor conditions, system configuration, and more importantly, the adsorbent materials. To circumvent this trade-off, this study proposes an NSGA-II-based multi-objective optimization model on a solar-driven CO2/H2O capture-based VAC system for optimizing its techno-energetic performances. This analysis maps the green buildings’ merits into five constrained objectives and fully optimizes them by considering a wide spectrum of decision parameters. This analysis automatically optimized the trade-off between conflicting objectives for both studied adsorbents to various extents. While maintaining the same IAQ level, a 74% and 59% improvement in maximal captured CO2 mass can be achieved for Mg-MOF-74 and Zeolite13X. Compared with Mg-MOF-74, Zeolites 13X performed 55% worse in maximal CO2 removal, but 82% better in maximal energy-saving potential due to higher cyclability, stability, and lower specific energy consumption. Additionally, the proposed multi-objective optimization framework could be applied to other adsorbent materials and capture methods to guide the optimal design of CO2/H2O capture-based VAC systems for green building development.

Keywords: Carbon capture; Multi-objective optimization; Ventilation; Air conditioning; Green buildings; NSGA-II algorithm (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.apenergy.2023.121305

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