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Abstract:
Active-passive phase change heat storage technologies have been obtained extensive application to decrease greenhouse's demands for fossil energy during off-seasons. To develop the utilization ratio of solar energy in solar greenhouses during winter, the active-passive ventilation wall with latent heat storage (APVW-L) was introduced and could be integrated into greenhouse's back-wall. However, system design and operation parameters are subjected to numerous factors, including its structure, material performance and outdoor meteorological parameters. To achieve optimization in the energy performance of this system, this study used finite element analysis and lumped parameter analysis to establish coupled energy balance equations of the APVW-L and the air inside vertical air passages, and the cubic spline interpolation was used to calculate the continuous relationship between phase change material's equivalent specific heat capacity and temperature. This modeling method of the APVW-L was accurately validated against the measured data, and then used in the optimization design and operation strategy of the APVW-L in the greenhouses. This study demonstrated that the optimized APVW-L could store 5.36 MJ/(m(2).day) of solar energy in Beijing. Compared to the identical conventional greenhouses, after midnight, the experimental greenhouse having APVW-L increased the back-wall's interior surface temperature by 2.2-3.4 degrees C, and the average indoor air temperature by 0.8-1.4 degrees C. This study provides methods for the APVW-L's optimization design and its operation strategy, even for the rationalization of the near-zero energy consumption of the solar greenhouse during winter. (C) 2021 Elsevier B.V. All rights reserved.
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Source :
ENERGY AND BUILDINGS
ISSN: 0378-7788
Year: 2021
Volume: 238
6 . 7 0 0
JCR@2022
ESI Discipline: ENGINEERING;
ESI HC Threshold:87
JCR Journal Grade:1
Cited Count:
WoS CC Cited Count: 30
SCOPUS Cited Count: 31
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 5
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