(186g) A Multi-Objective MILP Model for Spatio-Temporal Design and Operation of Multi-Product Oil Palm Value Chains

The economic potential of oil palm is realised due to its abundance, cheapness and versatility in producing different oleochemicals and energy products [1]. The oil palm fruit or fresh fruit bunch (FFB) can be processed to produce crude palm oil (CPO) and kernel palm oil (KPO). These can be converted into oleochemicals and energy products in which side products such as palm oil mill effluent (POME) and empty fruit bunches (EFB) can be converted further to valuable products. Palm-oil derived products are useful in different applications such as in power generation, agriculture and polymer industries. Considering a wide range of applications for oil palm, it is important to consider techniques for design and operation of palm oil value chains to maximise its economic and environmental benefits.

In this conference, a spatio-temporal mixed integer linear program (MILP) model for planning and designing multi-product value chains [2-3] for oil palm will be presented. A value chain includes all activities from pretreatment of raw materials to distribution of final products and waste management [4]. Due to the presence of different options in each stage of the value chain in oil palm industry, a mathematical model is necessary to gain important insights for large-scale planning. Spatial and temporal decision factors are considered by the model to optimise different scenarios in oil palm sectors. Spatial factors include identifying locations for oil palm plantations and processing facilities and location of demand. Temporal factors are considered in order to optimise the schedule of different processing and transportation operations. The model gives important insights on other aspects such as how much production is needed and how it will be allocated and transported. These decisions will depend on decision maker’s objectives including profit maximisation and GHG emissions minimisation. A case study using Peninsular Malaysian oil palm sectors is used to illustrate the model, which is implemented in AIMMS and solved using the CPLEX solver. In order to capture the spatial-dependencies of the problem, Peninsular Malaysia is represented as a grid of 50 km squares and candidate locations for oil palm plantation are modelled in GIS. The planning horizon for the problem is up to 2050 in order to illustrate the model’s capability to provide insights about the long-term evolution of the system, optimising the investments in technologies and infrastructures required in each decade.

References:

[1] A. Abdulrazik, M. Elsholkami, A. Elkamel, L. Simon (2017). Multi-products productions from Malaysian oil palm empty fruit bunch (EFB): Analyzing economic potentials from the optimal biomass supply chain, Journal of Cleaner Production, 168, 131-148, 2017.

[2] S. Samsatli, N.J. Samsatli (2017). A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies. Applied Energy. DOI: 10.1016/j.apenergy.2017.09.055.

[3] S. Samsatli, N.J. Samsatli, N. Shah (2015). BVCM: a comprehensive and flexible toolkit for whole-system biomass value chain analysis and optimisation - mathematical formulation. Applied Energy, 147, 131-160.

[4] S.M. Jarvis, S. Samsatli (2018). Technologies and infrastructures underpinning future CO₂ value chains: a comprehensive review and comparative analysis. Renewable & Sustainable Energy Reviews, 85, 46-68.