TY - JOUR
T1 - Functional-unit-based life cycle optimization of sustainable biomass-to-electricity supply chain with economic and environmental tradeoffs
AU - Yue, Dajun
AU - You, Fengqi
PY - 2014/1/1
Y1 - 2014/1/1
N2 - We propose a novel multi-objective optimization model for the sustainable design and operation of bio-electricity supply chain networks, which simultaneously optimizes the economic and environmental impacts. The proposed model covers the cradle-to-gate life cycle of bio-electricity including biomass cultivation and harvesting, feedstock pretreatment, energy conversion, biopower generation, as well as transportation and storage. We formulate the problem as a multi-objective mixed-integer linear fractional program (MILFP) following the functional-unit based life cycle optimization approach. The geographical dispersion and seasonality of biomass supply are captured and handled by the spatially explicit and multi-period features of the model. The multi- objective optimization is accomplished via ε-constraint method to obtain the approximate Pareto frontiers, which reveal the tradeoff between economic performance and concerns about environmental impacts. Tailored solution methods are proposed for the effective global optimization of the resulting MILFP problem. A county-level case study on potential bio-electricity supply chain in Illinois is provided to demonstrate the application of both modelling framework and solution methods.
AB - We propose a novel multi-objective optimization model for the sustainable design and operation of bio-electricity supply chain networks, which simultaneously optimizes the economic and environmental impacts. The proposed model covers the cradle-to-gate life cycle of bio-electricity including biomass cultivation and harvesting, feedstock pretreatment, energy conversion, biopower generation, as well as transportation and storage. We formulate the problem as a multi-objective mixed-integer linear fractional program (MILFP) following the functional-unit based life cycle optimization approach. The geographical dispersion and seasonality of biomass supply are captured and handled by the spatially explicit and multi-period features of the model. The multi- objective optimization is accomplished via ε-constraint method to obtain the approximate Pareto frontiers, which reveal the tradeoff between economic performance and concerns about environmental impacts. Tailored solution methods are proposed for the effective global optimization of the resulting MILFP problem. A county-level case study on potential bio-electricity supply chain in Illinois is provided to demonstrate the application of both modelling framework and solution methods.
KW - Biopower supply chain
KW - Life cycle optimization
KW - MILFP
KW - Sustainability
UR - http://www.scopus.com/inward/record.url?scp=84904350524&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904350524&partnerID=8YFLogxK
U2 - 10.1016/B978-0-444-63433-7.50093-6
DO - 10.1016/B978-0-444-63433-7.50093-6
M3 - Article
AN - SCOPUS:84904350524
SN - 1570-7946
VL - 34
SP - 651
EP - 656
JO - Computer Aided Chemical Engineering
JF - Computer Aided Chemical Engineering
ER -