Hybrid approach for carbon-constrained planning of bioenergy supply chain network

With increasing emphasis on sustainable development, developing countries are required to adapt more sustainable approaches to energy policy-making. Bioenergy supply chain planning methodologies can provide viable frameworks for policy-making. However, current methodologies lack the ability to simultaneously consider CO2 emission reduction targets while designing a bioenergy supply chain. As such, the objective of this work is to present a hybrid methodology that combines both carbon emission pinch analysis with superstructure-based optimisation technique. The proposed methodology was demonstrated via a palm-based case study, focused on the state of Selangor, Malaysia. The case study was broken into two scenarios. The first scenario accounted for an output-driven energy policy, whereby the electricity output of the bioenergy supply chain network (BSCN) is prioritised and the corresponding emission reduction is analysed. Results from the first scenario suggests that the optimised BSCN with 5,040 TJ output could reduce CO2 emission intensity by 9.71%. The second scenario focused on an emission-driven policy. Emission-driven policy establishes the emission reduction targets first and then determines the corresponding BSCN to achieve it. Results from this scenario indicate all oil palm plantations could afford to operate on low growth factors of up to 0.8 to avoid sharp drops in possible CO2 reductions for the BSCN. This policy was explored further by conducting sensitivity analysis on the agricultural growth and biomass export factors respectively. The analyses found that the optimised BSCN experience minimal change in costs when plantations have growth factors beyond 1.1. Lastly, analysis was performed to evaluate the range of technologies chosen based on the electricity output. The analysis found that power plant technologies were favoured more as compared to combined heat and power systems. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.