Sustainable design and synthesis of algae-based biorefinery for simultaneous hydrocarbon biofuel production and carbon sequestration

The superstructure optimization of algae‐based hydrocarbon biorefinery with sequestration of CO2 from power plant flue gas is proposed. The major processing steps include carbon capture, algae growth, dewatering, lipid extraction and power generation, and algal biorefinery. We propose a multiobjecti...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:AIChE journal Jg. 59; H. 5; S. 1599 - 1621
Hauptverfasser: Gebreslassie, Berhane H., Waymire, Randall, You, Fengqi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Blackwell Publishing Ltd 01.05.2013
American Institute of Chemical Engineers
Schlagworte:
Algae
Biofuels
Biorefineries
biorefinery
Carbon capture and storage
Carbon sequestration
Chemical engineering
Chemical reactors
Climate change
Dewatering
Economics
Energy balance
Environmental impact
Environmental performance
Flow rates
Flue gas
Global warming
Hydrocarbons
mixed-integer nonlinear programming
multiobjective
Nonlinear programming
Optimization
Refining
superstructure
sustainability
Sustainable design
ISSN:0001-1541, 1547-5905
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The superstructure optimization of algae‐based hydrocarbon biorefinery with sequestration of CO2 from power plant flue gas is proposed. The major processing steps include carbon capture, algae growth, dewatering, lipid extraction and power generation, and algal biorefinery. We propose a multiobjective mixed‐integer nonlinear programming (MINLP) model that simultaneously maximizes the net present value (NPV) and minimizes the global warming potential (GWP) subject to technology selection constraints, mass balance constraints, energy balance constraints, technoeconomic analysis constraints, and environmental impact constraints. The model simultaneously determines the optimal decisions that include production capacity, size of each processing unit, mass flow rates at each stage of the process, utility consumption, economic, and environmental performances. We propose a two‐stage heuristic solution algorithm to solve the nonconvex MINLP model. Finally, the bicriteria optimization problem is solved with ε‐constraint method, and the resulting Pareto‐optimal curve reveals the trade‐off between the economic and environmental criteria. The results show that for maximum NPV, the optimal process design uses direct flue gas, a tubular photobioreactor for algae growth, a filtration dewatering unit, and a hydroprocessing pathway leading to 47.1 MM gallons of green diesel production per year at $6.33/gal corresponding to GWP of 108.7 kg CO2‐eq per gallon. © 2013 American Institute of Chemical Engineers AIChE J, 59: 1599–1621, 2013
Bibliographie:Northwestern University (ISEN)
istex:4FEEDAFDE219D6D1A42C07D7F090FB15A2167B73
ArticleID:AIC14075
ark:/67375/WNG-BTPGKXFH-3
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.14075