Robust multi-objective optimization of gasifier and solid oxide fuel cell plant for electricity production using wood

Abstract

Biomass is an attractive renewable and stored energy that can be converted to transportation fuels, chemicals and electricity using bio-chemical and thermo-chemical conversion routes. Notably, biofuels have relatively lower greenhouse gas emissions compared to the fossil fuels. A biomass gasifier can convert lignocellulosic biomass such as wood into syngas, which can be used in Solid Oxide Fuel Cell (SOFC) to produce heat and electricity. SOFC has very good thermodynamic conversion efficiency for converting methane or hydrogen into electricity, and integration of SOFC with gasifier gives heat integration opportunities that allow one to design systems with electricity production efficiencies as high as 70%. Generally, process design and operational optimization problems have conflicting performance objectives, and Multi-Objective Optimization (MOO) methods are applied to quantify the trade-offs among the objectives and to obtain the optimal values of design and operating parameters. This study optimizes biomass gasifier and SOFC plant for annual profit and annualized capital cost, simultaneously. A Pareto front has been obtained by solving MOO problem, and then net flow method is used to identify some optimal solutions from the Pareto front for the implementation into next phase. The constructed composite curves, which notify maximum amount of possible heat recovery, and first law efficiency also indicate better performance of the integrated plant. Uncertainty of market and operating parameters has been added to the optimization problem, and robust MOO of the integrated plant has been performed, which retains less sensitive Pareto solutions during the optimization. Finally, Pareto solutions obtained via normal and robust MOO approaches are considered for uncertainty analysis, and Pareto solutions obtained via robust MOO found to be less sensitive.