Process Design, Techno-Economic Modelling, and Uncertainty Analysis of Biodiesel Production from Palm Kernel Oil

This study presented ASPEN Base Case Simulation (BCS) using optimum laboratory experimental data, techno-economic predictive models, and multi-objective optimum profitability scenario of biodiesel production from palm kernel oil. The BCS was developed in ASPEN Batch Process Developer V10 environment. Predictive models for predicting and optimizing techno-economic parameters: return on investment (ROI), payback time (PBT), net present value (NPV), and production capacity (PC) were achieved in Historical Data Design of Design Expert. The Oracle Crystal Ball was used for Monte Carlo Simulation (MCS) model uncertainty and sensitivity verification. The BCS results for 3,000,000 kg/year gave batch size, production rate, production batch number 13,482.48 kg, 5.72 kg/min, and 223 batches/year respectively. The correlation coefficients of ROI, PBT, NPV, and PC predictive models are 0.969, 0.982, 0.987, and 0.987, respectively. The MCS certainty of the techno-economic models gave a negligible uncertain value (certainty = 100%). The optimum ROI, PBT, NPV, and PC were feasible at 39.9%, 2.48 years, $1,001,320, and 3,000,690 kg, respectively. Thus, ASPEN Batch Process Developer and Monte Carlo Simulation are capable of performing palm kernel biodiesel production techno-economic and sensitivity analyses.

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