There are three hydrogen production options for HVO: steam methane reforming (SMR), biomass gasification (BG), and electrolysis from solar energy (PVELC). It assesses the sustainability of palm‐oil‐derived biofuel blending of biodiesel (FAME), HVO, and petroleum diesel. This study aims to find the most sustainable hydrogen production technology for the production of hydrogenated vegetable oil (HVO) and biofuel blending. The trend towards increasing biofuel blending mandates in several countries has raised a sustainability trilemma, especially for biofuels derived from palm oil. Furthermore, the SOO and MOO comparison shows the effect of applying green logistics by using MOO, resulting in less GHG emissions with unnoticeable change in cost. MOO scenarios with LNG ships also performed better compared to the diesel-fueled option, it can reduce CO2 emissions by 18.5% without a significant increase in total logistic cost. The results show that in MOO scenarios, the use of LNG fueled ships and optimized routes can reduce CO2 emissions and logistic costs by 27.8% and 50.6% compared to average current crude oil logistic cases. Optimization is performed to select the best option of crude oil supply sources and the type of ships that carry crude oil to the refinery unit in each scenario. Each of the scenarios differs in objective functions and ship’s fuel type (i.e. This study investigates a case study of crude oil logistics to a refinery unit in 6 scenarios with single-objective optimization (SOO) and MOO cases. This study aims to apply the green logistics concept in crude oil transportation that considers multiple depots and heterogeneous fleets by using multi-objective optimization (MOO). GHG emissions from logistics activities are predicted to increase significantly by 2050, so they need to be controlled with the right logistics planning strategy. The comparison between constant and variable speed reveals that the variable speed is preferred to constant speed as it gives lower emissions with slight changes in cost.Ĭrude oil logistics activities, which are mostly carried out using ships, are one of the contributors to greenhouse gas (GHG) emissions. The multi-objective optimization results an 11% cost reduction and a 17% GHG emission reduction compared with the current values. For the constant speed case, the distribution routes obtained for the minimizing cost scenario tends to maximize the utilization of transit terminals while in the minimizing emissions scenario tends to deliver directly to the distribution centers, so the route decision in multi-objective optimization scenario is combination of the two. In addition, this study also investigates the effect of variable speed on cost and CO2 emissions. The optimization is performed to determine the best logistics route and the amount of products delivered using certain types of fleets to minimize transportation cost and GHG emissions using constant speed. #PANDU LOGISTIC BALIKPAPAN SOFTWARE#Multi-objective optimization is conducted using the AIMMS software to optimize a logistics system consisting of a multi-depot, multi-product, and heterogeneous fleet. A multi-objective approach is used to implement the green logistics concept. This study aims to implement a green logistics concept in the logistics distribution of petroleum products-gasoline, kerosene, and diesel-in eastern Indonesia, whose supply sources are refineries located in Balikpapan and Kasim. Managing logistics distribution routes is considered a possible approach for controlling GHG emissions. The International Maritime Organization predicts that the greenhouse gas (GHG) emissions from transportation will be increasing significantly until 2050, driven by the growth in global maritime trade. The transportation sector is one of the largest fuel consumers and pollutant contributors worldwide.
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