Parametric analysis and Pareto optimization of an integrated autothermal biomass gasification, solid oxide fuel cell and micro gas turbine CHP system

• Published in: International journal of hydrogen energy Vol. 40; no. 41; pp. 14202 - 14223
• Main Authors: Borji, Mehdi, Atashkari, Kazem, Ghorbani, Saba, Nariman-Zadeh, Nader
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 02.11.2015
• Subjects: Biomass gasification; CHP; Direct internal reforming planar SOFC; Multi-objective optimization; Pareto optimization; Pareto optimization; Biomass gasification; CHP; Multi-objective optimization; Direct internal reforming planar SOFC
• ISSN: 0360-3199; 1879-3487
• DOI: 10.1016/j.ijhydene.2015.08.103

Incorporation of solid oxide fuel cells (SOFC) into hybrid plants producing combined heat and power (CHP) is a sustainable and efficient alternative to conventional electricity generation. In this work an attempt is made to investigate the integration of a two-stage autothermal biomass gasification with solid oxide fuel cell and a micro gas turbine (MGT) into a CHP system. Wet wood is fed to the fixed bed downdraft gasifier and gaseous fuel is produced then after the gas cleaning process can be used by high temperature SOFCs. It is assumed that only hydrogen participates in the SOFC electrochemical reaction and the non-reacted or reformed gases are stoichiometrically oxidized in the afterburner downstream of the fuel cell stack. The integrated plant is investigated by a developed mathematical model which consists of a zero dimensional autothermal gasifier and a 1-D model of direct internal reforming planar SOFC which allows monitoring of the temperature gradients along the cell length in different operating conditions. Both gasifier and SOFC models are verified against experimental and previous numerical data available in the literature. The selected inputs are chosen to be gasification agent dictated by two parameters namely, air to steam ratio (ASTR) and modified equivalence ratio (ERm), average current density, the fuel utilization factor, air ratio and SOFC inlet temperature. The effects of these selective parameters are studied on cooled gas efficiency of the first layer of the plant, temperature gradients, electric efficiency, and power of the fuel cell, the electric and CHP efficiencies, and the total electric power of the plant. Parametric analysis reveals that the decreased ASTR and increased ERm have positive effect on the cooled gas efficiency of the gasification process and total electric efficiency of the CHP plant while the inverse effect on the total CHP efficiency and output power of the hybrid system is shown. Besides, the investigations show increasing of the cell average current density can improve the total CHP efficiency of the cycle but leads to negative effect on the system electric efficiency. The results of such extensive parametric analysis necessitate the application of multi-objective optimization procedure. Non-dominated sorting genetic algorithm is used for Pareto based optimization of CHP plant in two steps. Firstly, the optimal values of the modified equivalence ratio (ERm) and air to steam ratio (ASTR) of the gasification process considering cooled gas and CHP efficiencies of the plant as two conflicting objectives are obtained. Secondly, the considered conflicting objectives are the total electric power, electric and CHP efficiencies of the plant and the design variables are average current density, fuel utilization factor, air ratio, and inlet temperatures of the SOFC. Furthermore, two conditions namely, SOFC operating voltage and PEN (Positive electrode/Electrolyte/Negative electrode) structure temperature gradients along the cell length are considered. It is shown that some interesting and important relationships among optimal performance parameters and design variables involved in the CHP plant can be discovered by Pareto based multi-objective optimization of the hybrid system. •Evaluation of a micro CHP plant based on SOFC is performed.•Steady state modeling and extensive parametric analysis is conducted.•Total electric efficiency over 41% and CHP efficiency over 61% is achieved.•Two-step Pareto based multi-objective optimization is performed.