TY - GEN
T1 - Linear programming modelling of an integrated sugarcane microalgal biofuel plant
AU - Gue, Ivan Henderson V.
AU - Ubando, Aristotle T.
AU - Aguilar, Kyle Darryl T.
AU - Manrique, Robby B.
AU - Cuello, Joel L.
AU - Culaba, Alvin B.
N1 - Funding Information:
A Inventory Matrix x Decision Vector y Product Vector i ithResource pi Price of ith Resource RE Overall Revenue Stream of ISMB Plant ACKNOWLEDGEMENT This study is supported by the U.S. Agency for International Development (USAID) through its Science, Technology, Research, and Innovation for Development (STRIDE) Program with USAID Contract No. AID-492-A-13-00011.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - One of the current trends for sustainable energy production is microalgal biofuel. It offers a fast-growing feedstock with high oil yield per land area. The current challenge of microalgal biofuel is in its economic competitiveness, because of its high production costs relative to fossil-based fuels. Unique solutions have been proposed to address this issue. One solution focuses on the integration of its production process with another industrial process, such as integration to sugarcane mills. The integration of microalgal biofuel production to the sugar industry can act as a support for the former to be an attractive investment. Several studies have assessed such integration can lead to reduced fossil fuel dependence and reduced environmental impacts. In this study, we utilize linear programming modeling to generate two optimized designs of an integrated system. Both designs focus on maximizing the revenue of the integrated plant. The latter is designed to maximize the revenue with zero carbon emission. Results yield for the prior design had an increased revenue for the sugarcane mill by 4.23% with a drawback of a 7-fold increase in carbon emission. The latter design is able to achieve zero carbon emission with a reduced revenue of 7.68%. This study aims to provide plant designers a methodology to synthesize and assess the integration of a microalgae biofuel plant with the sugarcane ethanol plant.
AB - One of the current trends for sustainable energy production is microalgal biofuel. It offers a fast-growing feedstock with high oil yield per land area. The current challenge of microalgal biofuel is in its economic competitiveness, because of its high production costs relative to fossil-based fuels. Unique solutions have been proposed to address this issue. One solution focuses on the integration of its production process with another industrial process, such as integration to sugarcane mills. The integration of microalgal biofuel production to the sugar industry can act as a support for the former to be an attractive investment. Several studies have assessed such integration can lead to reduced fossil fuel dependence and reduced environmental impacts. In this study, we utilize linear programming modeling to generate two optimized designs of an integrated system. Both designs focus on maximizing the revenue of the integrated plant. The latter is designed to maximize the revenue with zero carbon emission. Results yield for the prior design had an increased revenue for the sugarcane mill by 4.23% with a drawback of a 7-fold increase in carbon emission. The latter design is able to achieve zero carbon emission with a reduced revenue of 7.68%. This study aims to provide plant designers a methodology to synthesize and assess the integration of a microalgae biofuel plant with the sugarcane ethanol plant.
KW - biodiesel
KW - ethanol
KW - linear programming
KW - microalgae
KW - sugarcane mill
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U2 - 10.1109/HNICEM.2017.8269448
DO - 10.1109/HNICEM.2017.8269448
M3 - Conference contribution
AN - SCOPUS:85047752684
T3 - HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management
SP - 1
EP - 5
BT - HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2017
Y2 - 29 November 2017 through 1 December 2017
ER -