@inbook{634537e0c8294f06b9509347e1645050,
title = "Superstructure Optimization for the Design of an Algae Biorefinery Producing Added Value Products",
abstract = "This study presents a superstructure framework to evaluate processing pathways for the production of omega-3 and pigments in an algae biorefinery. Different stages such as cultivation, harvesting, dewatering, drying, cell distribution, and extraction are considered as processing sections in this superstructure. To simplify and speed up modelling, each of these technologies is grouped in blocks. The superstructure framework is converted to a mixed-integer nonlinear programming (MINLP) model. It has more than 6.000 constraints/variables. The model is implemented in the Advanced Interactive Multidimensional Modelling System (AIMMS) software. The CPLEX and CONOPT are the selected solvers. The most promising pathways for three types of microalgae are proposed. These have differences in the dewatering section. Furthermore, the different pathways are compared in terms of cost and performance. The results show that the Haematococcus Pluvialis biorefinery leads to the highest profits due to pigments products' high amount and price.",
keywords = "algae biorefinery, biochemical, MINLP, Superstructure optimization, techno-economic analysis, NLA",
author = "Maryam Raeisi and Jiawei Huang and Huynh, {Thien An} and Franke, {Meik B.} and Edwin Zondervan",
note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.",
year = "2022",
month = jan,
doi = "10.1016/B978-0-323-85159-6.50046-4",
language = "English",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier",
pages = "277--282",
booktitle = "Computer Aided Chemical Engineering",
}