Abstract
Oil palm industry is one of the key contributors to the Gross Domestic Product (GDP) and Comprehensive National Strength (CNS) of Malaysia. According to the Department of Statistical Malaysia (2021), oil palm industries had contributed about 2.7% or RM 38.26 billion (equivalent to 9.45 billion USD) to Malaysia’s GDP in 2019. An abundant amount of palm-based biomass has been generated through oil palm harvesting and palm oil production. Therefore, conceptual design and modeling of the palm biomass supply chain are deemed necessary to ensure the sustainability of the oil palm industry. Nevertheless, to enhance the model reliability and robustness, stochastic modeling should be opted to incorporate various uncertainties into the supply chain model. Keeping this in mind, this chapter presents an overview of the key supply chain uncertainties that should be incorporated into the supply chain model. It is followed by three illustrative examples which cover (i) biomass selection decision, (ii) facility location decision, and (iii) policy selection decision.
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Abbreviations
- AP:
-
Action plan
- AP-1:
-
Engage in demand contract
- AP2-HS:
-
Engage in supply contract
- AP3-FI:
-
Introduce new financing incentive
- AP4-SF:
-
Substitute fossil fuel with biodiesel
- AP5-TI:
-
Introduce new tax incentive
- AP6-RF:
-
Revise Feed-in-Tariff (FiT) rate
- AP7-CM:
-
Introduce carbon management system
- BOTA:
-
Bottleneck Tree Analysis
- CAPEX:
-
Capital expenditure
- CNS:
-
Comprehensive National Strength
- DoE:
-
Design of Experiment
- EFB:
-
Empty fruit bunch
- FiT:
-
Feed-in-tariff
- GDP:
-
Gross domestic product
- GTFS:
-
Green Technology Financing Scheme
- LNG:
-
Liquefied natural gas
- MF:
-
Mesocarp fiber
- MILP:
-
Mixed Integer Linear Programming
- NPV:
-
Net present value
- OPEX:
-
Operating expenditure
- PBP:
-
Payback Period
- PCA:
-
Principal component analysis
- PKS:
-
Palm kernel shell
- g :
-
Index for synthetic gas products
- m :
-
Index for months
- t :
-
Index for years
- u :
-
Index of units
- \({\mathrm{Biomass}}_{m,t}^{\mathrm{AVAILABLE}}\) :
-
Biomass availability at month m in year t (t)
- \({\mathrm{Biomass}}_{\mathrm{EFB}}^{\mathrm{QUALITY}}\) :
-
Biomass quality for EFB
- \({\mathrm{Biomass}}_{\mathrm{PKS}}^{\mathrm{QUALITY}}\) :
-
Biomass quality for PKS
- \({\mathrm{Biomass}}_{\mathrm{MF}}^{\mathrm{QUALITY}}\) :
-
Biomass quality for MF
- \(c\) :
-
Specific heat capacity of water (J kg/K)
- \({\mathrm{Cap}}^{\mathrm{TRUCK}}\) :
-
Vehicle load limit (t)
- \({C}_{m,t}^{\mathrm{BIOMASS}}\) :
-
Unit cost of biomass at month m in year t (USD/t)
- \({C}_{t}^{\mathrm{BIOMASS}}\) :
-
Unit cost of biomass in year t (USD/t)
- \({C}_{u}^{\mathrm{CAPEX}}\) :
-
Capital cost for unit u (USD)
- \({C}^{\mathrm{CAPEX}}\) :
-
Total capital cost for the conversion process (USD)
- \({C}_{m,t}^{\mathrm{COAL}}\) :
-
Unit cost of coal at month m in year t (USD/t)
- \({C}_{t}^{\mathrm{COAL}}\) :
-
Unit cost of coal in year t (USD/t)
- \({C}^{\mathrm{CO}2}\) :
-
Compensation cost required per unit of carbon emission (USD/kg)
- \({C}^{\mathrm{ELEC}}\) :
-
Unit cost of imported power (USD/kWh)
- \({C}^{\mathrm{FIT}}\) :
-
Feed-in-tariff (USD/kWh)
- \({C}_{m,t}^{\mathrm{FUEL}}\) :
-
Fuel price at month m in year t (USD/L)
- \({C}_{t}^{\mathrm{FUEL}}\) :
-
Fuel price in year t (USD/L)
- \({C}_{u,m,t}^{\mathrm{OPEX}}\) :
-
Operating cost for unit u at month m in year t (USD)
- \({C}_{t}^{\mathrm{OPEX}}\) :
-
Total operating cost for the conversion process in year t (USD)
- \({C}_{m,t}^{\mathrm{OIL}}\) :
-
Bio-oil price at month m in year t (USD/L)
- \({\mathrm{Cap}}^{\mathrm{TRUCK}}\) :
-
Vehicle load limit (t)
- \({d}^{D}\) :
-
Distance between polygeneration plant and the demand point (km)
- \({d}^{S}\) :
-
Distance between biomass supply and the polygeneration plant (km)
- \({\mathrm{Elec}}_{m,t}^{\mathrm{REQ}}\) :
-
Power demand at month m in year t (kWh)
- \({F}_{m,t}^{\mathrm{OIL}\_\mathrm{DEMAND}}\) :
-
Bio-oil demand at month m in year t (L)
- \({HV}^{\mathrm{coal}}\) :
-
Heating value of coal (MJ/kg)
- \(\mathrm{in}\) :
-
Discount rate (%)
- \(\mathrm{ITA}\) :
-
Tax exemption indicator (USD)
- \({\mathrm{LHV}}_{g}\) :
-
Low heating value of gas g (kJ/mol)
- \({\mathrm{LHV}}^{\mathrm{CHAR}}\) :
-
Low heating value of biochar (MJ/kg)
- \({\mathrm{LHV}}^{\mathrm{COAL}}\) :
-
Low heating value of coal (MJ/kg)
- \({\mathrm{MC}}_{m,t}^{\mathrm{IN}}\) :
-
Moisture content of biomass before drying (%)
- \({\mathrm{MC}}_{t}^{\mathrm{IN}}\) :
-
Moisture content of biomass before drying (wt%)
- \({\mathrm{MC}}^{\mathrm{OUT}}\) :
-
Moisture content of biomass after drying (%)
- \({\mathrm{Q}}^{\mathrm{FC}}\) :
-
Weight composition of fixed carbon of biomass (wt%)
- \({\mathrm{Q}}^{\mathrm{VM}}\) :
-
Weight composition of volatile matter of biomass (wt%)
- \({Q}^{A}\) :
-
Weight composition of ash of biomass (wt%)
- \({Q}^{MC}\) :
-
Weight composition of moisture content of biomass (wt%)
- \({Q}^{H}\) :
-
Weight composition of hydrogen of biomass (wt%)
- \({Q}^{C}\) :
-
Weight composition of carbon of biomass (wt%)
- \({Q}^{O}\) :
-
Weight composition of oxygen of biomass (wt%)
- \({Q}^{S}\) :
-
Weight composition of sulfur of biomass (wt%)
- \({\mathrm{Q}}^{\mathrm{N}}\) :
-
Weight composition of nitrogen of biomass (wt%)
- \(\mathrm{TAX}\) :
-
Corporate tax rate (%)
- \({\mathrm{Thermal}}_{m,t}^{\mathrm{REQ}}\) :
-
Heat demand at month m in year t (kWh)
- \({y}^{\mathrm{CHAR}}\) :
-
Biochar yield (%)
- \({y}^{\mathrm{CO}2\_\mathrm{COGEN}}\) :
-
CO2 emitted during co-generation unit (kg CO2/kWh)
- \({y}^{\mathrm{CO}2\_\mathrm{PY}}\) :
-
CO2 emitted during pyrolysis process (kg CO2/kg biomass)
- \({y}^{\mathrm{CO}2\_\mathrm{TR}}\) :
-
CO2 emitted during transportation (kg CO2/L fuel)
- \({y}^{\mathrm{GAS}}\) :
-
Syngas yield (%)
- \({y}_{g}^{PY}\) :
-
Molecular composition of gas g (%)
- \({y}^{\mathrm{OIL}}\) :
-
Bio-oil yield (%)
- \({\xi }^{\mathrm{COGEN}}\) :
-
Conversion efficiency of the co-generation unit (%)
- \({\xi }^{\mathrm{DRY}}\) :
-
Drying efficiency (%)
- \({\psi }^{\mathrm{FUEL}}\) :
-
Fuel consumption rate (L/km)
- \({\psi }^{\mathrm{PY}}\) :
-
Thermal energy required to try per unit mass of biomass (kWh/t)
- \({\psi }^{\mathrm{THERMAL}}\) :
-
Thermal energy required to try per unit mass of moisture (kWh/t)
- \({\mathrm{Biomass}}_{m,t}^{\mathrm{DRY}}\) :
-
Flowrate of dried biomass fed into the pyrolyser at month m in year t (t)
- \({\mathrm{Biomass}}_{m,t}^{IN}\) :
-
Flowrate of biomass fed into the plant at month m in year t (t)
- \({\mathrm{Biomass}}_{t}^{\mathrm{IN}}\) :
-
Flowrate of biomass fed into the plant in year t (t)
- \({\mathrm{Biomass}}_{t}^{\mathrm{SUPPLY}}\) :
-
Biomass supply in year t (t)
- \({C}_{m,t}^{\mathrm{PENALTY}}\) :
-
Carbon penalty at month m in year t (USD)
- \({C}_{m,t}^{\mathrm{PROCURE}}\) :
-
Procurement cost at month m in year t (USD)
- \({C}_{t}^{\mathrm{PROCURE}}\) :
-
Procurement cost in year t (USD)
- \({C}_{t}^{\mathrm{SYNGAS}}\) :
-
The selling price of syngas in year t (USD)
- \({C}_{m,t}^{\mathrm{TR}}\) :
-
Transportation cost at month m in year t (USD)
- \({C}_{t}^{\mathrm{TR}}\) :
-
Transportation cost in year t (USD)
- \({CF}_{m,t}^{\mathrm{IN}}\) :
-
Input cash flow (USD)
- \({CF}_{t}^{\mathrm{IN}}\) :
-
Input cash flow in year t (USD)
- \({CF}_{m,t}^{\mathrm{OUT}}\) :
-
Output cash flow (USD)
- \({CF}_{t}^{\mathrm{OUT}}\) :
-
Output cash flow in year t (USD)
- \({\mathrm{Elec}}_{m,t}^{\mathrm{EXP}}\) :
-
Exported power at month m in year t (kWh)
- \({\mathrm{Elec}}_{m,t}^{\text{GEN}}\) :
-
Generated power at month m in year t (kWh)
- \({\mathrm{Elec}}_{m,t}^{\mathrm{IMP}}\) :
-
Imported power at month m in year t (kWh)
- \({F}_{m,t}^{\mathrm{CHAR}}\) :
-
Biochar production at month m in year t (t)
- \({F}_{m,t}^{\mathrm{COAL}}\) :
-
Coal consumption at month m in year t (t)
- \({F}_{t}^{\mathrm{COAL}}\) :
-
Coal consumption in year t (t)
- \({F}_{m,t}^{\mathrm{GAS}}\) :
-
Syngas production at month m in year t (t)
- \({F}_{m,t}^{\mathrm{OIL}}\) :
-
Bio-oil production at month m in year t (L)
- \({F}_{t}^{\mathrm{SYNGAS}}\) :
-
Syngas demand in year t (MWth)
- \({\mathrm{Q}}^{coal}\) :
-
Energy required to reduce the moisture content of biomass (MJ)
- \({S}^{\mathrm{BIOMASS}}\) :
-
Specific syngas yield (kg/kg)
- \({T}_{\mathrm{Final}}\) :
-
Temperature of biomass after drying (°C)
- \({T}_{\mathrm{Initial}}\) :
-
Temperature of biomass before drying (°C)
- \({\mathrm{NCF}}_{m,t}\) :
-
Net cash flow at month m in year t (USD)
- \({\mathrm{NCF}}_{t}\) :
-
Net cash flow in year t (USD)
- \({\mathrm{Thermal}}_{m,t}^{\mathrm{GEN}}\) :
-
Generated heat at month m in year t (kWh)
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Acknowledgements
The author would like to acknowledge the financial support from the Ministry of Higher Education under the Fundamental Research Grant Scheme [grant number: FRGS/1/2020/TK0/SWIN/03/3] and Swinburne University of Technology Sarawak via Research Supervision Grant [grant number: 2-5545 RSG].
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How, B.S., Lo, S.L.Y., Kong, K.G.H., Teng, S.Y. (2023). Stochastic Modeling for Palm Biomass Supply Chain. In: C.Y. Foo, D., Tun Abdul Aziz, M.K., Yusup, S. (eds) Sustainable Technologies for the Oil Palm Industry. Springer, Singapore. https://doi.org/10.1007/978-981-19-4847-3_6
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DOI: https://doi.org/10.1007/978-981-19-4847-3_6
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