Article. Energy in fokus - from Kyoto to Copenhagen. - AgroTech

Article. Energy in fokus - from Kyoto to Copenhagen. - AgroTech

Martin Lykke Rytter Jensen and Bo Nørregaard Jørgensen, University of Southern Denmark, The Maersk Mc-Kinney Moller Institute,

Campusvej 55, DK-5230 Odense M, Denmark

Oliver Körner, AgroTech, Højbakkegaard Allé 21, DK-2630 Taastrup, Denmark, Carl-Otto Ottosen, University of Aarhus,

Faculty of Agricultural Sciences, Department of Horticulture, Kirstinebjergvej 10, Postboks 102, DK-5792 Aarslev, Denmark

is caused by lack of CO2. The graph also shows the maximum photosynthesis we can expect in the

near future (green dashed line). This photosynthesis is continuously calculated based on irradiation

data from the most current weather forecast. When a cloudy day is expected, the control system wil

automatically turn on artificial light earlier in an attempt to achieve a specified light sum. The

PREDICT – A component-based

software platform for

dynamic climate control

grower can use the forecast to see how much artificial light will be needed and potentially adapt the

light strategy before it is executed. The transition of this version of the PREDICT software into

commercial greenhouses was planned as a three-phase process. In the first phase, the software was

tested and demonstrated to growers in a greenhouse research facility. Here, the software gives the

growers advice on optimal climate control with respect to production rate. In the second phase, the

software was installed at Danish Growers. To start with, the software runs in simulated mode; that is

the software only computes the climate set points, it does not effectuate them. The primary purpose

of this phase is to allow the growers to become familiar with the software, how it operates, and understand

the effect of dynamic climate control. The final phase is active control where the PRE-

DICT software takes control of the climate based on overall goals set by the grower. Through the

The dynamic model-based development climate of COa new that maximises component-based photosynthesis software at the platform Proven for successful dynamic in climate small setups, control, the the PRE-


control concept IntelliGrow DICT has project been has present contributed light level with in the extended greenhouse. knowledge The next of step the was implication to try the of IntelliGrow increasing conthe


developed in Denmark since straction 1996. The level result of climate is then control. translated This to set knowledge points appli- is crucial cept in for commercial developing greenhouses. the next Howe- generation of

concept aims at improving intelligent the energy climate-control cable by the components.

specific climate computer. ver, whereas the original IntelliGrow soft-

efficiency of greenhouse production by Combined with temperature integration ware was designed as a research prototype

adjusting the greenhouse climate References dynami- control, this optimization reduces the use applicable to an experimental setting, the

cally to the present weather Hansen situation. JM, To Ehler of additional N, Karlsen heating P, Høgh-Schmidt of the greenhouse. K, Rosenqvist move towards E. (1996). full-scale A computer production controlled in

do so, IntelliGrow incorporates chamber a determisystem

The designed concept has for been greenhouse proved to microclimate work in commercial modelling greenhouses and control. required Acta a Hort. new

nistic leaf-photosynthesis model 440:310-315.

based on climate-chamber experiments (Hansen et software platform. For this reason, the

Farquhar et al. (1980) and Gijzen Aaslyng, (1994) J.M., al., Lund, 1996) J.B., as well Ehler, as in N. small and Rosenqvist, greenhouse E. PREDICT (2003) project IntelliGrow: was undertaken a greenhouse in 2006. compo-

as presented by Körner (2004) nent-based to ensure climate experiments control with system. many different Environmental cultivars Modelling The primary & goal Software of the 18: PREDICT 657-666 project

maximum photosynthetic performance. Gijzen H. By (1994) of pot Ontwikkeling plants (Aaslyng van et al., een 2003), simulatiemodel resul- was voor to provide transpiratie such a en software wateropname platform. en van

using this model, it is possible een to integral deter- gewasmodel. ting in energy (Development savings up to 40%, of a depen- simulation A primary model design for transpiration concern of the and PREDICT water uptake

mine the combination of temperature and an and integral ding crop on model), the season. AB-DLO, Wageningen, The project Netherlands. focused on advancing pp. 90. the original

Farquhar G.D., Von Caemmerer S., Berry J.A. (1980) A biochemical model of photosynthetic CO2

assimilation in leaves of C3 species. Planta 149:78-90.

Körner O. (2004) Evaluation of crop photosynthesis models for dynamic climate control. Acta

Horticulturae 654:295-302.

Figure 1.


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