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Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia

Authors :
Harahap, F.
Leduc, S.
Mesfun, S.
Khatiwada, D.
Kraxner, F.
Silveira, S.
Harahap, F.
Leduc, S.
Mesfun, S.
Khatiwada, D.
Kraxner, F.
Silveira, S.
Publication Year :
2019

Abstract

Significant amounts of biomass residues were generated in Indonesia. While untreated, residues emit greenhouse gases during the decomposition process. On the other hand, if efficiently utilized, these residues could be used to produce value-added products. This study investigates opportunities for harnessing the full potential of palm oil residues (i.e., empty fruit bunches, kernel shells, fiber, and mill effluent). As far as we are aware, the study is the first attempt to model the palm oil supply chain in a geographically explicit way while considering regional infrastructures in Sumatra Island, Indonesia. The BeWhere model, a mixed integer linear programming model for energy system optimization, was used to assess the costs and benefits of optimizing the regional palm oil supply chain. Different scenarios were investigated, considering current policies and new practices leading to improved yields in small-scale plantations and power grid connectivity. The study shows that a more efficient palm oil supply chain can pave the way for the country to meet up to 50% of its national bioenergy targets by 2025, and emission reductions of up to 40 MtCO2eq/year. As much as 50% of the electricity demand in Sumatra could be met if residues are efficiently used and grid connections are available. We recommend that system improvements be done in stages. In the short to medium term, improving the smallholder plantation yield is the most optimal way to maximize regional economic gains from the palm oil industry. In the medium to long term, improving electricity grid connection to palm oil mills could bring higher economic value as excess electricity is commercialized.

Details

Database :
OAIster
Notes :
text, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1157293248
Document Type :
Electronic Resource