Parametric Optimization of a Power and Biomass to Liquid Process

Abstract

In this study, a power & biomass to liquid process (PBtL) is optimized with respect to nine continuous design variables. These variables have great impact on the profitability of the process. A detailed process model is simulated using a commercial sequential-modular simulation software and optimized using the derivative-free optimization algorithm Nelder-Mead. Optimization is performed for different investment cost estimates of the solid-oxide electrolysis cell (SOEC) that provides additional hydrogen to the process. With increasing the SOEC investment cost, the profitability is reduced and there is less need for hydrogen production. By considering the investment cost of the SOEC to be 1500 $/kW, the profitability of the process is increased by 15.5%, compared to the case without optimization (Hillestad et al., 2018).