Simulation of a Venlo-type greenhouse for tomato crop cultivated
from 10Dec-22Nov (weather data from TMY)
Simulation of greenhouse
climate
This example intends to
illustrate the simulation of a greenhouse climate. The greenhouse
is built by interconnecting all of the energy and mass Flows presents in a greenhouse
to their related Components. As
it can be distinguished, the greenhouse modeled in this example
consists of two levels of heating circuits, roof windows (but not
side vents), natural ventilation (no forced ventilation) and a
movable thermal screen. It should be noted that, when the screen is
drawn, the air of the greenhouse is divided in two zones, i.e.
below and above the screen. These zones are modeled separately
(models air and air_Top) and their climate is assumed to be
homogeneous. The models parameters have been set to typical values
for Venlo-type greenhouse construction design dedicated to tomato
crop cultivation. The greenhouse floor area and the mean greenhouse
height are set in two individual block sources.
The simulated greenhouse is
located in Belgium and the simulation period is from December 10th
to November 22nd. Two data files are required:
- Weather data:
The input weather data for the simulation period is extracted from
a TMY for Brussels and can be found in ‘Greenhouses/Resources/Data/10Dec-22Nov.txt’.
The file contains data for the outside air temperature, air
pressure, wind speed and global irradiation. The sky temperature,
previously computed in a Python script, is also included in this
file.
- Climate control
set-points: The temperature and CO2 set-points for the
simulation period are calculated according to the strategy
presented in the online documentation and can be found in ‘Greenhouses/Resources/Data/SP_10Dec-22Nov.txt’.
These '.txt' files are
accessed by means of TMY_and_control and SP_new,
which are two CombiTimeTables models from the Modelica Standard
Library.
The goal of this
example is to show the energy flows interacting in a greenhouse.
Thus, no generation units are included. Instead, the heating pipes
are connected to a water source and sink model. The model includes
the following controls:
- PID_Mdot: A PI
controller adjusts the output mass flow rate of the water source
connected to the heating pipes by comparing the air temperature
set-point and present value.
- PID_CO2: A PI
controller adjusts the output of the CO2 external source by
comparing the actual CO2 concentration of the air to its
set-point.
- Ctrl_SC: A
state graph adjusts the screen closure (SC) according to the
strategy presented in Control_ThScreen.
The real inputs must be connected to the air relative humidity, the
outdoor temperature, the indoor air temperature set-point and the
usable hours of the screen. The usable hours are 1h30 before dusk,
1h30 after dawn and during night.
- vents: A PI
controller adjusts the opening of the windows according to the
strategy presented in Uvents_RH_T_Mdot.
The opening depends mainly on the indoor air relative humidity and
temperature.
- OnOff: controls
the ON/OFF operation of the supplementary lighting according to the
strategy presented in Control Systems. The control output,
previously computed in a Python script, is input as a .txt file by
means of the TMY_and_control
CombiTimeTable.
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