Department of Chemical Engineering, Birla Institute of Technology and Science Pilani, K. K. Birla Goa campus, Zuarinagar, Goa 403726, India.
Bioresour Technol. 2024 Apr;398:130523. doi: 10.1016/j.biortech.2024.130523. Epub 2024 Mar 2.
This work presents dynamic optimization strategies of batch hydrothermal liquefaction of two microalgal species, Aurantiochytrium sp. KRS101 and Nannochloropsis sp. to optimize the reactor temperature profiles. Three dynamic optimization problems are solved to maximize the endpoint biocrude yield, minimize the final time, and minimize the reactor thermal energy. The biocrude maximization and time minimization problems demonstrated 11% and 6.18% increment in the optimal biocrude yields and reduction of 78.2% and 61.66% in batch times compared to the base cases for the microalgae with higher lipid and protein fractions, respectively. The energy minimization problem revealed a significant reduction in the reactor thermal energies to generate the targeted biocrude yields compared to the biocrude maximization. Therefore, the identified optimal temperature trajectories outperformed the conventional fixed temperature profiles and could improve the overall economics of the batch bio-oil production from the algal-based biorefineries by significantly enhancing the reactor performance.
本工作提出了两种微藻（金黄裸藻 KRS101 和盐生杜氏藻）分批水热液化的动态优化策略，以优化反应器温度曲线。解决了三个动态优化问题，以最大化终点生物油产率、最小化最终时间和最小化反应器热能。与基础案例相比，生物油最大化和时间最小化问题分别使脂质和蛋白质含量较高的微藻的最佳生物油产率提高了 11%和 6.18%，并将批次时间缩短了 78.2%和 61.66%。能量最小化问题表明，与生物油最大化相比，生成目标生物油产率时反应器热能显著降低。因此，与传统的固定温度曲线相比，所确定的最佳温度轨迹可以通过显著提高反应器性能来提高基于藻类的生物炼制厂的批生物油生产的整体经济性。
