TY - GEN
T1 - Optimal Synthesis of Algal Biorefineries for Biofuel Production Based on Techno-Economic and Environmental Efficiency
AU - Culaba, Alvin B.
AU - Juan, Jayne Lois G.San
AU - Ching, Phoebe Mae L.
AU - Mayol, Andres Philip
AU - Sybingco, Edwin
AU - Ubando, Aristotle
N1 - Funding Information:
ACKNOWLEDGMENTS The authors would like to acknowledge the financial support from the National Research Council of the Philippines (NRCP), De La Salle University’s University Research Coordination Office (URCO), and Department of Science and Technology – Engineering Research and Development for Technology (DOST-ERDT).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Biomass derived from microalgae is an emerging technology and attractive alternative source for biofuels. However, its exclusive production cannot be feasibly commercialized because of economic and environmental sustainability issues. The biorefinery concept allows microalgae to be efficiently converted into biofuels and other high-valued products, such as cosmetics, nutraceuticals, and pharmaceuticals. Nonetheless, this venture would require large capital investments that must be strategically scheduled across the lives of the investments, while keeping a reliable forecast of market growth. A multi-period multi-objective mixed integer non-linear programming (MINLP) model is proposed in this study to determine optimal investment schedule and operational decisions that would simultaneously maximize the net present value (NPV) and minimize the greenhouse gas (GHG) emissions of an algal biorefinery. An illustrative case study and scenario analyses demonstrate the validity and the capabilities of the proposed model.
AB - Biomass derived from microalgae is an emerging technology and attractive alternative source for biofuels. However, its exclusive production cannot be feasibly commercialized because of economic and environmental sustainability issues. The biorefinery concept allows microalgae to be efficiently converted into biofuels and other high-valued products, such as cosmetics, nutraceuticals, and pharmaceuticals. Nonetheless, this venture would require large capital investments that must be strategically scheduled across the lives of the investments, while keeping a reliable forecast of market growth. A multi-period multi-objective mixed integer non-linear programming (MINLP) model is proposed in this study to determine optimal investment schedule and operational decisions that would simultaneously maximize the net present value (NPV) and minimize the greenhouse gas (GHG) emissions of an algal biorefinery. An illustrative case study and scenario analyses demonstrate the validity and the capabilities of the proposed model.
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U2 - 10.1109/HNICEM48295.2019.9072730
DO - 10.1109/HNICEM48295.2019.9072730
M3 - Conference contribution
AN - SCOPUS:85084744043
T3 - 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019
BT - 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019
Y2 - 29 November 2019 through 1 December 2019
ER -