Modelling and optimization of the downstream processing of microalgal biomass to biodiesel

B.J. Koetzier, P.M. Slegers, A.J.B. van Boxtel

Research output: Contribution to conferenceAbstract


Depleting oil reserves have forced the scientific community to consider other resources to satisfy the global fuel demand. One of the possibilities is the production of biodiesel from microalgae. The main advantages of microalgae are the high yield per area of land, it is carbon neutral and it does not compete with food crops. While the cultivation of microalgae is one of the bottlenecks in the production process, there is also a challenge in the downstream processing. This research evaluates the feasibility of various unit operations for the downstream processing of algae biomass to biodiesel. Different unit operations are considered for the harvesting, dewatering, disruption, extraction and conversion from biomass to biodiesel. First, models for the various unit operations are created based on basic mass and energy balances. Models and fits from data sets available in literature are used to describe the effect of key variables on the operations. For every unit operation a flow, algae or product concentration, temperature and pressure are given as input. The outputs of the models are the same properties for the outgoing flow and the power consumption of the unit operation. In a later step the process is optimized for the lowest power consumption and water use. An important issue to consider for the modeling is that literature on the different process steps is commonly only available for specific species of microalgae and that most experiments have been carried out on a laboratory scale. Therefore it is assumed that a similar relation holds for every alga species and that the processes scale linearly. The project looks at the mass and energy balances and that is why the time for each process is kept constant. Second, a chain of process steps is optimized to reduce the energy consumption and water use. This chain includes unit operations for harvesting, dewatering, disruption, extraction and conversion. For each step multiple options are available. The aim is to find the route of process steps with the lowest energy consumption. Other variables for optimization are resource usage or greenhouse gas emissions. The result is a framework of basic models to find out what the best route for the downstream processing is. In later research the models and optimization routines can be improved to produce an even better approximation of reality.
Original languageEnglish
Publication statusPublished - 2012
EventNBC 14 - Ede, Netherlands
Duration: 16 Apr 201218 Apr 2012


ConferenceNBC 14


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