Superstructure optimization of biodiesel production from microalgal biomass

Muhammad Rizwan, Jay H. Lee, Rafiqul Gani

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-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 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 study. 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
Title of host publicationProceedings of the 10th IFAC International Symposium on Dynamics and Control of Process Systems
PublisherElsevier
Publication date2013
Pages111-116
ISBN (Print)9781629937267
Publication statusPublished - 2013
Event10th IFAC International Symposium on Dynamics and Control of Process Systems - Mumbai, India
Duration: 18 Dec 201320 Dec 2013
Conference number: 10

Conference

Conference10th IFAC International Symposium on Dynamics and Control of Process Systems
Number10
CountryIndia
CityMumbai
Period18/12/201320/12/2013

Keywords

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

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