Modeling and simulation of vegetable oil processes

Special Symposium - Innovations in Food Technology (LMC Congress)

Flexible Production, PAT & Modelling (Food-3a)

Ing Ana Martinho
Technical University of Denmark
CAPEC, Dpt. of Chemical Engineering
2800 Lyngby
Denmark

Prof Henrique Matos
Instituto Superior Técnico
DEQB
Av. Rovisco Pais
1049-001 Lisboa
Portugal

Prof Rafiqul Gani
Technical University of Denmark
CAPEC, Department of Chemical Engineering
Soltofts Square, Building 229
DK-2800 Lyngby
Denmark

Ing Bent Sarup
Alfa Laval Copenhagen A\S
Oil and Protein Technology, Process Engineering Dep.
Maskinvej 5, DK-2860 Søborg
Denmark

Ing William Youngreen
Alfa Laval Copenhagen A\S
Oil and Protein Technology, Process Engineering Dep.
Maskinvej 5, DK-2860 Søborg
Denmark

Keywords: modeling, simulation, validation, recovery optimization, solvent-based extraction, vegetable oil.

The object of this work is modeling, simulation and optimization of a vegetable oil production process. A solvent-based extraction process for the production of vegetable oil from soybean has been studied with special emphasis on the solvent recovery section of the process. This solvent recovery section includes four parts: an oil recovery part, where the solvent is evaporated from the oil to concentrate the crude vegetable oil; a condensation system where the solvent vapors (recovered from the oil recovery and the desolventization of the meal) are condensed; a mineral oil system where a mineral oil is used to capture solvent mixed with the non-condensable vapors; and a water-solvent separation, where pure solvent is recovered by decantation. The main compounds representing the vegetable oil (soybean oil) usually consist of free fatty acids, triglycerides, tocopherols and sterols. Except for the free fatty acids, most of the other compounds are usually not available in the databases of commercial simulators, and therefore, the ICAS-ProPred software has been used to generate the pure compound data and insert them into the database of a commercial simulator (ProII). The next step has been simulation of the process to validate the process models by matching the steady state data (mass and energy balance) with industrial data. The final step has been to apply the validated process simulation model to optimize the solvent recovery efficiency by adjusting operational variables such as pressure and temperature as well as the type of solvent. The presentation will highlight the modeling and simulation steps together with the optimization of the process in terms of solvent recovery.

Presented Wednesday 19, 16:05 to 16:20, in session Flexible Production, PAT & Modelling (Food-3a).