Optimal processing pathway for the production of biodiesel from microalgal biomass: A superstructure based approach

Muhammad Rizwan, Jay H. Lee, Rafiqul Gani

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In this study, we propose a mixed integer nonlinear programming (MINLP) model for superstructure based optimization of biodiesel production from microalgal biomass. The proposed superstructure includes a number of major processing steps for the production of biodiesel from microalgal biomass, such as the harvesting of microalgal biomass, pretreatments including drying and cell disruption of harvested biomass, lipid extraction, transesterification, and post-transesterfication purification. The proposed model is used to find the optimal processing pathway among the large number of potential pathways that exist for the production of biodiesel from microalgae. The proposed methodology is tested by implementing on a specific case with different choices of objective functions. The MINLP model is implemented and solved in GAMS using a database built in Excel. The results from the optimization are analyzed and their significances are discussed.
Original languageEnglish
JournalComputers and Chemical Engineering
Volume58
Pages (from-to)305-314
ISSN0098-1354
DOIs
Publication statusPublished - 2013

Keywords

  • Superstructure optimization
  • Biodiesel
  • Microalgae
  • Mixed integer nonlinear programming
  • Biorefinery

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