Optimal processing pathway selection for microalgae-based biorefinery under uncertainty. (2nd November 2015)

• Record Type: Journal Article
• Authors: Rizwan, Muhammad; Zaman, Muhammad; Lee, Jay H.; Gani, Rafiqul
• Is Part Of: Computers & chemical engineering. Volume 82(2015)
• Page Start: 362
• Page End: 373
• Publication Date: 2015-11-02
• Subjects: Biofuels -- Microalgal biorefinery -- Uncertainty analysis -- Stochastic mixed integer nonlinear programming (sMINLP) -- Decision-making under uncertainty; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2015.08.002
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Identification of optimal microalgae processing pathways under uncertainty. Techno-economic uncertainties in the dataset are considered. The optimization problem is formulated as a stochastic MINLP model. Optimal processing pathways are determined under different objective functions. Optimal structures are compared with respect to different objective functions used. Abstract: We propose a systematic framework for the selection of optimal processing pathways for a microalgae-based biorefinery under techno-economic uncertainty. The proposed framework promotes robust decision making by taking into account the uncertainties that arise due to inconsistencies among and shortage in the available technical information. A stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery configurations based on a superstructure model where parameter uncertainties are modeled and included as sampled scenarios. The solution to the sMINLP problem determines the processing technologies, material flows, and product portfolio that are optimal with respect to all the sampled scenarios. The developed framework is implemented and tested on a specific case study. The optimal processing pathways selected with and without the accounting of uncertainty are compared with respect to different objectives.