TY - JOUR
T1 - Addressing supply uncertainties using multi-period stochastic economic evaluation
T2 - A graph-theoretic aided element targeting approach
AU - Lo, Shirleen Lee Yuen
AU - Lim, Chun Hsion
AU - Benjamin, Michael Francis D.
AU - Lam, Hon Loong
AU - Sunarso, Jaka
AU - How, Bing Shen
N1 - Funding Information:
This work was financially supported by Swinburne University of Technology Sarawak Campus via Full Fee-Waiver Studentship and Research Supervision Grant ( 2-5545 RSG ). B.S. How would like to acknowledge the financial support given by the Ministry of Higher Education (MOHE) , Malaysia under Fundamental Research Grant Scheme [grant number: FRGS/1/2020/TK0/SWIN/03/3 ].
Publisher Copyright:
© 2022 The Authors
PY - 2022/10
Y1 - 2022/10
N2 - The challenges to commercialize biomass industry includes biomass supply shortage which is dependent on geographical location and seasonality. Most of the present biomass supply chain studies had not considered incorporation of supply chain uncertainties that may lead to overestimation of financial performance. Therefore, a hybrid framework was proposed via integration of stochastic Monte Carlo Simulation model with element targeting approach (Biomass Element Life Cycle Analysis, BELCA-P-graph model) to perform scheduling and economic analysis for the biomass supply chain. The BELCA-P-graph model aimed to generate a baseline for the feedstock ratio of each input biomass. This was then input into the stochastic model, capable of estimating the financial probability of the supply chain while incorporating supply chain uncertainties (i.e., biomass element characteristics, transportation-related parameters, raw material pricing, biomass availability, market demand, and selling price of final product). Results showed that biomass shortage had decreased the mean Net Present Value (NPV) of the base case scenario (without consideration biomass supply shortage) by 1.39%–12.21%. Storage capacity consideration had decreased the mean NPV by 11.59%–12.21%. The sensitivity analysis found that syngas demand and syngas selling price uncertainty offered significant impact on the mean NPV outcome.
AB - The challenges to commercialize biomass industry includes biomass supply shortage which is dependent on geographical location and seasonality. Most of the present biomass supply chain studies had not considered incorporation of supply chain uncertainties that may lead to overestimation of financial performance. Therefore, a hybrid framework was proposed via integration of stochastic Monte Carlo Simulation model with element targeting approach (Biomass Element Life Cycle Analysis, BELCA-P-graph model) to perform scheduling and economic analysis for the biomass supply chain. The BELCA-P-graph model aimed to generate a baseline for the feedstock ratio of each input biomass. This was then input into the stochastic model, capable of estimating the financial probability of the supply chain while incorporating supply chain uncertainties (i.e., biomass element characteristics, transportation-related parameters, raw material pricing, biomass availability, market demand, and selling price of final product). Results showed that biomass shortage had decreased the mean Net Present Value (NPV) of the base case scenario (without consideration biomass supply shortage) by 1.39%–12.21%. Storage capacity consideration had decreased the mean NPV by 11.59%–12.21%. The sensitivity analysis found that syngas demand and syngas selling price uncertainty offered significant impact on the mean NPV outcome.
KW - Biomass element life cycle analysis
KW - Monte Carlo
KW - Multi-period operation
KW - P-graph
KW - Uncertainties
UR - http://www.scopus.com/inward/record.url?scp=85137283704&partnerID=8YFLogxK
U2 - 10.1016/j.clet.2022.100554
DO - 10.1016/j.clet.2022.100554
M3 - Article
AN - SCOPUS:85137283704
SN - 2666-7908
VL - 10
JO - Cleaner Engineering and Technology
JF - Cleaner Engineering and Technology
M1 - 100554
ER -