Application of teaching-learning-based optimization algorithm in designing 100 kW power plant using pyrolysis of oil palm empty fruit bunches

Abstract

Importance of the work: Empty fruit bunches (EFBs) from the palm oil milling process have the potential to be used as a source of energy.
Objectives: To optimize the environmental impact and economic profitability of utilization of biofuel production from the EFB fast pyrolysis process.
Materials & Methods: The biodiesel power plant from the EFB fast pyrolysis process was modelled using the Aspen Plus program and optimized using the MATLAB program. The multi-objective teaching-learning-based optimization algorithm was used to maximize the net present value (NPV) while minimizing the CO2 emission of a biodiesel power plant in each case.
Results: The optimization results showed that the best case from the economic aspect was an NPV of USD million 14.233 with 59,755 t CO2/yr, while the best case in terms of minimizing environmental impact was with the lowest CO2 emission equivalent of 58,770 t CO2/yr and an NPV of USD million 12.008. The difference between these two scenarios regarding the CO2 emission was slight (1.65%), while for the NPV, it was high (15.63%).
Main finding: Both cases produced higher CO2 emissions than from direct combustion. However, they were still environmentally friendly since they reduced the CO2 emission equivalent compared to using the EFB as landfill and produced valuable products, while
enhancing energy conservation by up to 100 kW.