부산대학교 도서관

TRNSYS is a common tool that has been recently used to model and simulate greenhouse energy demand and utilization using building energy simulation (BES). Previously, a single thermal point was used for validation without considering the distribution of greenhouse climate parameters, especially the temperature. Often, temperature variation leads to thermal stratification, which has prompted researchers to propose volume discretization in dynamic greenhouse simulation. The effect of surface characterization defined by TRNSYS on the accuracy of such discretized BES model needs to be investigated. Therefore, the objectives of this study are to develop discretized BES models based on surface characterization defined in TRNSYS and to determine the best model under a free-floating regime. The combination of these factors, namely, the number of layers [double (D) and single (S)], geometry mode [3D and manual (M)], and layer type [massless (M) and no glazing window (W)], led to the development of five models: D_3D_M, D_3D_W, D_M_M, S_3D_W, and S_M_M. The simulation was performed in a standard radiation mode, and the output parameters were temperature and relative humidity (RH). R2 and the root square mean error (RSME) were used to check the fitness and degree of deviation, respectively, to validate the models. Analysis of variance (ANOVA) was employed to investigate the significant difference among the models. In contrast, contour plots were used to compare the distribution pattern between the significant models and experimental data. Validation of the models showed that the obtained R2 values ranged from 0.86 to 0.95, and the RSME values for the temperature were between 2.64℃ and 3.91℃. These values were 0.91-0.93 and 19.72%-30.32% for RH. The ANOVA (p < 0.05) result exhibited significant differences between the S-scenario models and experimental central points in temperature and RH. The D- and S-layer scenarios with a 3D geometry and massless layer exhibited similar distribution with their corresponding experimental greenhouses. Hence, 3D_M was regarded as the best combination in the discretized BES model.