Development of a Building Energy Simulation Model for Control of Multi-Span Greenhouse Microclimate
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ID: 110530
2020
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Abstract
In this study, we propose a building energy simulation model of a multi-span greenhouse using a transient system simulation program to simulate greenhouse microenvironments. The proposed model allows daily and seasonal control of screens, roof vents, and heating setpoints according to crop needs. The proposed model was used to investigate the effect of different thermal screens, natural ventilation, and heating setpoint controls on annual and maximum heating loads of a greenhouse. The experiments and winter season weather conditions of greenhouses in Taean Gun (latitude 36.88° N, longitude 126.24° E, elevation 45 m) Chungcheongnam-do, South Korea was used for validation of our model. Nash–Sutcliffe efficiency coefficients of 0.87 and 0.71 showed good correlation between the computed and experimental results; thus, the proposed model is appropriate for performing greenhouse thermal simulations. The results showed that the heating loads of the triple-layered screen were 70% and 40% lower than that of the single-screen and double-screen greenhouses, respectively. Moreover, the maximum heating loads without a screen and for single-, double-, and the triple-layered screens were 0.65, 0.46, 0.41, and 0.34 MJ m−2, respectively. The analysis of different screens showed that Ph-77 (shading screen) combined with Ph-super (thermal screen) had the least heating requirements. The heating setpoint analysis predicted that using the designed day- and nighttime heating control setpoints can result in 3%, 15%, 14%, 15%, and 40% less heating load than when using the fixed value temperature control for November, December, January, February, and March, respectively.
| Reference Key |
rasheed2020agronomydevelopment
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| Authors | Adnan Rasheed;Cheul Soon Kwak;Wook Ho Na;Jong Won Lee;Hyeon Tae Kim;Hyun Woo Lee;Rasheed, Adnan;Kwak, Cheul Soon;Na, Wook Ho;Lee, Jong Won;Kim, Hyeon Tae;Lee, Hyun Woo; |
| Journal | agronomy |
| Year | 2020 |
| DOI |
10.3390/agronomy10091236
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| URL | |
| Keywords |
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