A scheduling and planning algorithm for microalgal cultivation and harvesting for biofuel production

Microalgae is highlighted as the most feasible bioenergy feedstock because it can produce high amounts of lipids, carbohydrates, and hydrogen, which are necessary compounds for the production of various biofuels, while only requiring minimal water and land due to high photosynthetic efficiency. However, there are technical limitations that negatively influence the mass production of biofuel from algae, making it economically infeasible on a commercial scale. One of these bottlenecks exist in its cultivation. The cultivation method and system are critical in determining the amount and quality of biofuel that may be generated from the microalgae. Additionally, the peak biomass concentration, and productivities for the different compounds and nutrients within microalgae do not occur at the same time. Hence, this work proposes a planning tool for microalgae cultivation systems that incorporates species selection, and cultivation and harvesting approach selection and scheduling, while balancing the minimization of environmental impact and maximization of profit realized. The capabilities of the proposed decision support model is demonstrated through a hypothetical case study. Scenario analyses is likewise conducted to establish an understanding of system behavior and performance over time and under various conditions. The results of the computational experiments show the tools capabilities in simultaneously considering algae growth rates and compound productivities in decision making, for instance biomass species that is able to generate the most of a certain high value fuel is prioritized in cultivation and harvesting.